Annual Report of the US Hospital IT Market

Transcription

2013
Annual Report
of the
U. S. Hospital
IT Market
An industry report provided by
and
This historical report
of the U.S. Hospital
IT Market is brought
to you as an online
resource from the
Dorenfest Institute.
▶▶ Table of Contents
Looking Back; Looking Ahead: The Year in Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2012 Hospital IT Budget and Expenses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Financial Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Financial Decision Support Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Human Resource Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Revenue Cycle Management Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Next Generation Revenue Cycle Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Health Information Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Document Management/Electronic Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Nursing Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Ancillary Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Laboratory Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Surgical Information System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Radiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Cardiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Bar Code Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Electronic Medical Record Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
The EMR Adoption ModelSM: Measuring Clinical IT Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Ambulatory (Hospital Owned/Managed) IT Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
HIMSS Mission
To lead healthcare transformation through the effective use of health information technology.
© 2013 by the Healthcare Information and Management Systems Society and HIMSS Analytics.
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ISSN: 1949-0526
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For more information about HIMSS, please visit www.himss.org.
For more information about HIMSS Analytics, please visit www.himssanalytics.org.
▶▶ A Letter from the CEO and EVP of HIMSS and HIMSS Analytics
Dear Healthcare Executive:
Welcome to the 2013 Annual Report of the U.S. Hospital IT Market, produced jointly by the Healthcare Information and Management
Systems Society (HIMSS) and HIMSS Analytics LLC, the wholly-owned, not-for-profit market research arm of HIMSS. We are very
pleased to present this comprehensive view of the current state of IT adoption in U.S. hospitals, and hospital-owned, managed and/or leased
ambulatory practices.
From government incentives to planning a major investment in new technologies, a healthcare professional faces numerous challenges in
wading through the complicated healthcare environment.
Since the program beginning (in 2009) until November 2012, the Department of Health and Human Services (HHS) has made incentive
payments of over $9 billion to American hospitals and eligible providers authorized under the The Health Information Technology for
Economic and Clinical Health Act (HITECH). As part of the provisions of the 2009 American Recovery and Reinvestment Act (ARRA),1
the incentive payments more than double the amount paid out from the program at the same time in 2011. We at HIMSS Analytics believe
the incentive program is having an accelerating effect on healthcare IT adoption in U.S. hospitals. In 2012, 205 hospitals achieve Stage 6 on
the Electronic Medical Record Adoption ModelSM (EMRAM), up from 102 in 2011 and 80 in 2010.
Moreover, in response to questions surrounding the efficacy of the HITECH program by certain members of Congress, HIMSS mobilized
to demonstrate how the ARRA incentive program was fueling an acceleration of IT adoption in U.S. hospitals. By profiling the acute care
EMRAM scores over five quarters from time of the initial stimulus payments in Q2 of 2011 through Q3 of 2012, we showed that Stages 5
and 6 had in excess of an 80 percent growth while Stage 7 had grown 66 percent.
Stage 2 Meaningful Use regulations were finalized in September of 2012. In general, the bar set by Stage 1 has been raised for Stage 2,
although the onset of criteria was pushed out to 2014. Meaningful Use Stage 2, ICD-10 adoption, clinical and business intelligence to
support payment reform, and Meaningful Use Stages 1 and 2 quality reporting are still in effect working to maintain the “perfect storm”
of regulatory compliance facing healthcare CIOs.
From HIMSS Analytics data, we see that the number of hospitals per IDN continues to increase slightly from 6.9 to 7.0, though at
decreasing rate from previous years. We perceive that the economic uncertainty for hospitals with looming significant Medicare
reimbursement cuts may be cooling down the acquisition frenzy. However, the reductions of Medicare may be offset by new revenue from
patients with health insurance in 2014 and beyond now that the Affordable Care Act (ACA) has been substantially accepted by the Supreme
Court. Clearly, these are uncertain times for hospital CFOs.
In 2012, HIMSS Analytics produced another report in our series regarding return on investment (ROI) for healthcare IT.2 Numerous
examples of efficiency, quality and safety improvements were identified from Davies Award winners and Stage 7 hospitals. Clearly, the
naysayers who believe that healthcare IT does not have a payoff are incorrect.
We anticipate that 2012 will be seen as a year of acceleration where the stimulus provided by ARRA began to make an increasing affect
in helping U.S. hospitals reach a “tipping point” in IT investments. You can count on HIMSS Analytics and HIMSS to equip you to stay
on top of these changes, and to be your most trusted and comprehensive source of information on the adoption of IT applications, and
the progress toward implementing those applications in today’s U.S. healthcare provider environment.
We hope you find this ninth edition of the Annual Report of the U.S. Hospital IT Market informative, compelling and stimulating.
Best regards,
John P. Hoyt
Executive Vice President
HIMSS Analytics
H. Stephen Lieber
President and CEO
HIMSS
1 http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_Medicare_Incentive_Payments.pdf
2 http://www.himss.org/transformation/docs/December2012ResearchPaper.pdf
▶▶ Looking Back; Looking Ahead: The Year in Review
Years from now, historians may look back at the year 2012 and
cast it as a pivotal moment in the evolution of healthcare in the
U.S. With the Supreme Court’s five to four decision to uphold the
Affordable Care Act (ACA) or “Obamacare” and its individual
mandate requiring individuals to obtain health insurance or pay a
fine, the ruling has the potential to greatly change the healthcare
industry. Additional evidence regarding the significance of the
Supreme Court’s decision played out later in the year with the
re-election of Barack Obama. Challenged by a Republican presidential
candidate, Mitt Romney, who vowed to repeal the ACA, Americans
affirmed the move to change healthcare in the U.S. as we know it.
So as we stand on the precipice of a new era in healthcare, 2013
will no doubt prove to be interesting, as regulations are unfurled to
support the law that begins to take effect in 2014.
The past year also saw unemployment in the U.S. steadily decrease
from the nine percent level it had stubbornly fixated itself to
beginning in late 2011, landing at 7.7 percent by November 2012.1
Concurrent with that gradual improvement in unemployment, the
bellwether “housing starts” (number of new housing constructions)
statistics from the Federal government’s Housing and Urban
Development (HUD) Department showed signs of a reviving
economy. Housing starts for new residential construction increased
by 46.6 percent when comparing November 2012 with November
2011.2 Clearly there is some gradual improvement in the U.S.
economy, albeit slower than everyone would like.
The U.S. economy though, does not operate within a vacuum. Our
economic affairs influence and are influenced by those in other
parts of the world. The troubles within the European financial
markets for example, are believed to be having a detrimental effect
on the demand for U.S. goods and services, and may slow the
revitalization of the U.S. economy. Despite these external downward
pressures, the NASDAQ index, where many of the publicly held
healthcare information technology (IT) companies are traded,
showed a healthy 13.6 percent gain in 2012, while the Dow Jones
Industrial Average only eked out 7.2 percent growth.
The challenges to the U.S. economy did not let up even as the year
closed. The federal government struggled mightily to avoid a selfimposed “fiscal cliff” that would have severely cut select governmental
services and automatically instituted tax increases for many U.S.
residents. The “fiscal cliff” remedies, which were mostly resolved at
the last minute on December 31, with some key issues being deferred
two months, served to highlight the discord among lawmakers. The
closely watched consumer confidence index took a six percent drop
in December as the fiscal cliff edged closer.3 This drop could have
an effect on elective medical consumption in 2013, and is a metric
many within the healthcare community will want to watch.
Hospitals are typically a “lag indicator” of the economy as the
effects of a recession tend to hit hospitals at the end of the recessive
cycle. HIMSS AnalyticsTM data shows that in 2012 the number of
hospitals and integrated delivery networks (IDNs) that reported an
increase in their IT budgets was stable with 2011 levels. Clearly
hospitals are investing in IT, but not necessarily at an increasing
rate, according to HIMSS Analytics data through Autumn 2012.
Slow economic growth has led to greater than expected deficits
through continued transfer payments and less than projected tax
revenues at both the federal and state levels. These deficits have
added significant pressure to state Medicaid programs, and in
response, numerous federal programs are being scrutinized for
effectiveness. Efforts to reach a compromise over the automatic tax
increases from the repeal of the Bush-era tax cuts have generally
included some effort to extend unemployment benefits. But as
unemployment continues to decrease, the appetite for continued
extensions may be lessened. Again, this could have a detrimental
effect on elective medical consumption in 2013.
The ARRA funding continues to be effective in stimulating the
adoption of healthcare IT. In November 2012, more than 176,000
health care eligible providers received payment for participating in
the Medicare and Medicaid Electronic Health Record (EHR)
Incentive Programs, up from 100,000 healthcare providers in June
of 2012.4 All told, over 3,300 hospitals have received $6.05B in
Medicare incentive payments through November 2012, since the
program began issuing incentive payments in May 2011.5
ARRA funding has clearly stimulated the acute care IT industry.
Evidence of this growth can be found in the increased rate of
progression up the EMRAM scale. In 2012, HIMSS Analytics
recognized 205 hospitals achieving Stage 6, double the number
(102) that achieved Stage 6 in 2011, and 2.5 times greater than the
number achieved in 2010 (80). In October 2012, in response to
questions surrounding the efficacy of the HITECH program by
certain members of Congress, HIMSS produced an acute care
EMRAM score table detailing five quarters of data from the initial
stimulus payment in Q2 of 2011 through Q3 of 2012. Astonishingly,
that table showed that Stages 5 and 6 grew by more than 80 percent
while Stage 7 grew by 66 percent.
Another sign of the acute care IT industry’s growth is the continued
struggle healthcare providers have in recruiting and retaining
clinical system skills for the implementation and support of IT
systems. According to the U.S. Department of Labor Bureau of
Labor Statistics (BLS), the healthcare industry is expected to grow
rapidly between 2008 and 2018 in large part due to a continued
growth of our elderly population. Additionally, the national effort to
effectively deal with chronic diseases such as obesity is becoming
more prevalent and thus will continue to stoke the demand for
clinical labor. The BLS indicates that the social services and
healthcare employment sector will be the fastest growing sector
from 2008 through 2018 at 2.3 percent per year, with a clear
majority of this growth coming from the ambulatory care settings.
When providers are competing with vendors for the same clinical
IT skills, the pressure will be on the providers to be able to retain
the skills necessary to support the systems that have been deployed
and meet the growing demand of the medical staffs, nursing staff
and other clinician users.
Consolidation continues in the hospital provider market. Acquisition
and mergers of acute care providers increased slightly in 2012
compared to 2011. We perceive that access to large capital may be
constrained in this uncertain economy due to the anticipated
1 http://data.bls.gov/timeseries/LNS14000000
2 http://www.census.gov/construction/nrc/pdf/newresconst.pdf
3 http://money.cnn.com/2012/12/30/news/economy/payroll-tax-consumer/index.html?hpt=hp_t1
4 https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/DataAndReports.html
5 http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Nov_IncentiveProgramPayment_Registration_SummaryReport.pdf
2 Source: HIMSS Analytics® Database 2012 ©2013 HIMSS Analytics.
▶▶ Looking Back; Looking Ahead: The Year in Review con tinue d
reductions in Medicare and Medicaid reimbursements. However,
the ACA will also provide a new source of revenue to hospitals
as we begin our national effort to reduce the number of uninsured
consumers. These two countervailing pressures make for uncertainty,
and thus diminished appetite for debt as well as a diminished
appetite to loan.
HIMSS Analytics data shows that the number of hospitals per
IDN continued to grow, however at a much slower rate in 2012
(1.5 percent), when compared to 2011 levels (4.5 percent). HIMSS
Analytics also uncovered an interesting anomaly in the data on the
number of hospitals per IDN. The median number has stayed at
3.0 for several years, but the arithmetic mean average is now 7.0
compared to 6.9 in 2011. The large disparity between the median of
3.0 and the mean of 7.0 tells us that there are significant numbers of
very large IDNs but that their growth rate has slowed in 2012.
We see no force to prevent this trend from continuing as
hospitals choose to consolidate to weather the storm of reduced
reimbursements, Accountable Care Organizations (ACOs) and
bundled payments. The desire of the Federal Government, notably
the White House and Health and Human Services Department
(HHS), to have the ACO program succeed, may result in a
confrontation with anti-trust watch dogs in the Justice Department.
No doubt, more clarity here is needed in the market.
The NPRM (notice of proposed rule making) for Meaningful Use
Stage 2 regulations were released in February with the final rule
being published on September 4, 2012. The extensive regulations
also modified rules for Meaningful Use Stage 1. In general, the bar
for criteria to satisfy Meaningful Use Stage 1 was raised, with the
onset of criteria pushed back to 2014, the first year of applicability
and the time when a 90-day EHR reporting period is allowed. The
Stage 1 hospital requirement of 14 core measures and five of ten
menu measures has been replaced with 16 core measures and three
of six menu measures in Stage 2 for eligible hospitals. According
to the Office of the National Coordinator for Health Information
Technology (ONC), the total Federal cost of the Medicare and
Medicaid EHR Incentive Programs between 2014 and 2019 is
estimated to be $15.4 billion (these estimates include net payments
adjustments for Medicare providers who do not achieve Meaningful
Use in 2015 and subsequent years in the amount of $2.1 billion)
The Medicare ACO program continued to grow in 2012. On July 9,
2012, the Center for Medicare and Medicaid Services (CMS)
announced that 89 new organizations had been selected to
participate in the Shared Savings Program via the ACO construct.
In addition, CMS also announced 106 new organizations had been
selected to participate on January 10, 2013. ACOs are driving
hospitals to enter new partnerships with competitors in order to
manage the health of a defined population.
We believe these pilot programs will, by necessity, develop
strengths in clinical and business intelligence (C&BI) in order to
analyze the quality of their care and to drive efficiencies to meet
the payment and incentive goals. One clear objective of the ACO
program is to find a much better way of managing chronic diseases.
According to Kaiser Permanente data, five percent of their covered
population consumes fifty percent of the healthcare dollars. Clearly,
we need to find ways, through patient engagement and best-practice
modeling, to reduce consumption and the prevalence of chronic
disease. We see a continued strong growth in software, hardware
and services to meet the needs for C&BI.
The industry tension between privately funded and federally
funded health information exchanges (HIEs) remained the same in
2012. Federally funded HIEs remain challenged to find long-term
sustainable business models and revenue services outside of state
and federal funding mechanisms. However, significant inroads have
been made by many of these regional and state public HIEs in the
development of sustainability models as well as forming
relationships working alongside private HIEs.
The Nationwide Health Information Network (NwHIN) saw many
changes in 2012. The NwHIN name changed to eHealth Exchange
and oversight transitioned from ONC to Healtheway, a nonprofit–
public, private partnership. Healtheway is chartered to support the
eHealth Exchange and focus on cross-industry collaboration to
advance HIEs across the country. eHealth Exchange continues to
be a set of standards and polices that enable secure HIEs over the
Internet through a common trust agreement by the community of
eHealth Exchange participants.
Continued market growth is anticipated with all HIE initiatives.
The private market anticipates accelerated growth as private HIEs
continue to develop and open up new business channels working
with other private as well as public HIEs in their local and regional
markets. We expect to continue seeing payers and other private
organizations enter this space, as exchanges are valued as a major
source of clinical consumption data that facilitates development of
the next wave of efficacy research and resultant best practices and
protocols. In addition, we expect to see more incorporation of
financial and business information with clinical data by the HIEs.
The ARRA also provisioned the Federal Coordinating Council
for Comparative Effectiveness Research. ARRA authorized
$300 million for the Agency for Healthcare Research and Quality
(AHRQ), $400 million for the National Institutes of Health, and
$400 million for the Secretary of Health and Human Services to
support comparative effectiveness research. As hospitals implement
EHRs, a wealth of data is being collected in a way that we have
never had before. The goal of the Comparative Effectiveness
Research program is to build the tools and methodologies to utilize
this data to support clinical research, develop optimized care
protocols which can be incorporated into the clinical decision
support capabilities of EMRs, and also eventually drive pay for
performance. Hospitals and IDNs that invest in C&BI tools and
resources will be in a better position to succeed, positioning
themselves to meet the new quality and efficiency requirements.
Included in this research will be pharmaceutical efficacy data that
goes beyond Food and Drug Administration (FDA) trials.
So, looking ahead, where are we going in 2013 and beyond? It is
clear that federal policy has stimulated the adoption of healthcare
IT, and that the drive to develop a successful ACO, patient-centered
medical home and payment reform has picked up steam. The ACA
to extend healthcare access to millions was substantially upheld by
the Supreme Court. The Democratic Party picked up eight seats in
the House of Representatives, narrowing the Republican majority to
33 (234 to 201). The Democratic majority in the Senate was
strengthened with the addition of two seats, and two Senators serving
as Independents. Dealing with the deficits and the aftermath of the
“fiscal cliff” will clearly drive both parties to find ways of reducing
spending and the inexorable growth of healthcare’s portion of the
gross domestic product (GDP), which now stands at 17.6 percent.
One fact remains clear—healthcare providers will continue to be
Source: HIMSS Analytics® Database 2012
©2013 HIMSS Analytics.
3
expected to improve quality care coordination across care settings,
while simultaneously reducing costs and improving efficiency.
tasks as consolidating around a common supply chain system is
temporarily a low priority.
Now that a significant proportion of hospital providers have
demonstrated compliance with Stage 1 Meaningful Use, they have
little time to rest on their laurels. Instead, they will be faced in
rapid succession with several other major IT challenges:
• Complying with unfunded government mandates to convert to
ICD-10 diagnosis coding by October 1, 2014.
• Meeting the EHR-related Stage 2 Meaningful Use requirements
beginning in 2014.
• Addressing the organizational and process changes required to
meet the higher mandated levels of compliance with
computerized provider order entry (CPOE) and clinical decision
support (CDS) usage, as well as electronic reporting in order to
secure continued Meaningful Use payments.
We also believe we are not too far away from an uptick in revenue
cycle system replacements to meet the new demands of payment
reform. Maybe that is the next “bubble” to come after 2015.
The challenges associated with a multi-year EMR implementation
process can often cause organizations to lose sight of a critical
guiding IT principle: technology is simply a means to the end, not
an end unto itself. As we enter 2013, we see that the industry’s
attention is focused on implementing EMRs, yet the experience
of early adopters has clearly and repeatedly demonstrated that
implementing an EMR alone will not achieve cost savings, quality
improvements or revenue enhancements unless it is a component of
a broader plan with clearly defined organizational and operational
improvement objectives. The most successful organizations are
those which have used their EMR as a foundation for implementing
process change and complementary technologies—such as business
analytics and clinical decision support—to achieve improved
outcomes and reduced costs.
A growing body of literature in respected journals and conference
proceedings supports the idea that quality improvements truly can
be derived from appropriately deployed healthcare IT concomitant
with process redesign. The literature base and the HIMSS Analytics
Stage 7 award winner case studies, as well as the HIMSS Davies
Award winner case studies, are replete with examples of medication
safety improvements; cost savings when CPOE is supported by
evidence-based best practice alerts; and savings to health plans
through reduced healthcare consumption, just to name a few.
Naysayers who believe that healthcare IT investments do not drive
quality and efficiency benefits are clearly wrong. The payoff has
begun. Let us continue this progression.
However, can healthcare IT be inappropriately applied? Certainly,
inadequate training and poor usability design can feed an errorprone environment. Providers and software developers alike must
be on guard to optimize the tremendous power of healthcare IT
appropriately. EHR safety is a concern and rightly so and it has the
attention of key government agencies.
This Annual Report also demonstrates areas where healthcare IT
market activity is slow, most notably in the supply chain area and
revenue cycle. We have been stating that we expect an increase in
activity in the supply chain area due to hospital mergers and
acquisitions. The data thus far does not support that prediction.
CIOs tell us that their primary focus is to implement the systems
necessary to earn their Meaningful Use incentive payment and such
Finally, as hospitals accumulate unprecedented levels of digital
data, we see two major derivatives. First, C&BI analytics will take
on a central role to help direct hospitals toward the most effective
care protocols and efficiency. Second, hospital data centers
themselves will become increasingly taxed to support and hold all
this data. Hospitals will begin to move quickly to vendor-neutral
archiving in secure data centers off campus. Manageability and
physical space have become key issues for providers. Outsourced
data centers or entire hosting of systems in an application service
provider (ASP) model will clearly grow, harking back to the
beginning of our industry where shared models were the norm.
Years from now, healthcare IT history buffs will likely look back
on 2012 as a year when acute care IT adoption accelerated through
the momentum gathered in 2011, and spurred on by federal stimulus
dollars. But the past is merely prologue, as we expect the pace of
change to continue now that President Obama has been re-elected
and the ARRA stimulus program is not likely to be diminished
significantly. However, we could see a significant downturn in
clinical systems activity once the incentive payments cease after
2016. The interesting question is, will that be replaced by a growth
of revenue-cycle system implementations to support payment reform
commencing by the middle of this decade? As Confucius once said,
“may we live in interesting times.”
HIMSS Analytics Stage 7 Awards
HIMSS Analytics launched the EMRAM in 2005 to track adoption
of EMR applications within hospitals and health systems. The
EMRAM scores hospitals in the HIMSS Analytics® Database on
their progress in completing 8 Stages (0-7), with the goal of reaching
Stage 7, an environment where paper charts are no longer used to
document the delivery of patient care.
In 2009, HIMSS Analytics honored 38 Stage 7 hospitals, the first
hospitals to reach Stage 7. By 2011, the number of hospitals swelled
to 66, including two international Stage 7 hospitals.
Stage 7 hospitals are positioned to share clinical information
via standard electronic transactions with all entities within HIE
networks (i.e. other hospitals, ambulatory clinics, sub-acute
environments, employers, payers and patients). This stage allows the
healthcare organization to support the true sharing and use of health
and wellness information by consumers and providers alike. Also at
this stage, healthcare organizations use data warehousing and
mining techniques to capture and analyze care data for performance
improvement and advancing the use of clinical decision support
protocols. As such, it is these organizations that are best positioned
to reach Stage 1 Meaningful Use.
The following is a list of healthcare organizations that have
achieved Stage 7 of EMRAM (as of December 2012). These
hospitals exemplify organizations that are using IT as the
supporting infrastructure for their advances.
In 2012, a record number of 40 hospitals representing 10 different
North American IDNs, satisfied the criteria to be validated as an
EMRAM Stage 7 facility.
Name
Banner Baywood Medical Center
Banner Boswell Memorial Hospital
Banner Churchill Community Hospital
Banner Del E. Webb Memorial Hospital
Banner Desert Medical Center
Banner Estrella Medical Center
Banner Gateway Medical Center
Banner Good Samaritan Medical Center
Banner Heart Hospital
Banner Ironwood Medical Center
Banner Lassen Medical Center
Banner Thunderbird Medical Center
Community Hospital
East Morgan County Hospital
Ellis Fischel Cancer Center
Florida Hospital North Pinellas
Fort Memorial Hospital
Hennepin County Medical Center
McKee Medical Center
Missouri Orthopedic Institute
Missouri Psychiatric Center
North Colorado Medical Center
Ogallala Community Hospital
Page Hospital
Platte County Memorial Hospital
Sterling Regional MedCenter
Texas Health Harris Methodist Alliance
The Ohio State University Comprehensive Cancer Center –
Arthur G. James Cancer Hospital and Richard J. Solove
Research Institute
The Ohio State University Harding Hospital
The Ohio State University Hospital
The Ohio State University Hospital East
The Ohio State University Rehabilitation Services at Dodd Hall
The Ohio State University Richard M. Ross Heart Hospital
Truman Medical Center–Hospital Hill
Truman Medical Center–Lakewood
UC Davis Medical Center
University Hospital
University of Iowa Hospitals and Clinics
Washakie Medical Center
Women’s and Children’s Hospital
City
Mesa
Sun City
Fallon
Sun City West
Mesa
Phoenix
Gilbert
Phoenix
Mesa
San Tan Valley
Susanville
Glendale
Torrington
Brush
Columbia
Tarpon Springs
Fort Atkinson
Minneapolis
Loveland
Columbia
Columbia
Greeley
Ogallala
Page
Wheatland
Sterling
Fort Worth
State
AZ
AZ
NV
AZ
AZ
AZ
AZ
AZ
AZ
AZ
CA
AZ
WY
CO
MO
FL
WI
MN
CO
MO
MO
CO
NE
AZ
WY
CO
TX
Columbus
Columbus
Columbus
Columbus
Columbus
Columbus
Kansas City
Kansas City
Sacramento
Columbia
Iowa City
Worland
Columbia
OH
OH
OH
OH
OH
OH
MO
MO
CA
MO
IA
WY
MO
This is the eighth edition of the Annual Report of the U.S. Hospital
IT Market. It is our deepest desire that you find this report thoughprovoking, stimulating and informative.
The HIMSS Analytics Research Team
John Hoyt
Lorren Pettit
Jennifer Horowitz
Roger Park
Maggy Tieche
Hospitals validated as Stage 7 prior to 2012.
Name
Alfred I. DuPont Hospital for Children
American Family Children’s Hospital
Children’s Hospital Boston
Children’s Hospital of Pittsburgh
Children’s Medical Center at Legacy
Children’s Medical Center of Dallas
Citizens Memorial Healthcare
Deaconess Cross Point Center
Deaconess Gateway Hospital
Deaconess Hospital
Evanston Hospital
Florida Hospital–Flagler
Glenbrook Hospital
Highland Park Hospital
Kaiser Permanente–Anaheim Medical Center
Kaiser Permanente–Antioch Medical Center
Kaiser Permanente–Baldwin Park Medical Center
Kaiser Permanente–Bellflower Medical Center
Kaiser Permanente–Fontana Medical Center
Kaiser Permanente–Fremont Medical Center
Kaiser Permanente–Fresno Medical Center
Kaiser Permanente–Hayward Medical Center
Kaiser Permanente–Los Angeles Medical Center
Kaiser Permanente–Manteca Medical Center
Kaiser Permanente–Moanalua Medical Center
Kaiser Permanente–Modesto Medical Center
Kaiser Permanente–Moreno Valley Community Hospital
Kaiser Permanente–Oakland Medical Center
Kaiser Permanente–Orange County/Irvine Medical Center
Kaiser Permanente–Panorama City Medical Center
Kaiser Permanente–Redwood City Medical Center
Kaiser Permanente–Richmond Medical Center
Kaiser Permanente–Riverside Medical Center
Kaiser Permanente–Roseville Medical Center
Kaiser Permanente–Sacramento Medical Center
Kaiser Permanente–San Diego Medical Center
Kaiser Permanente–San Francisco Medical Center–Geary
Kaiser Permanente–San Jose Medical Center
Kaiser Permanente–San Rafael Medical Center
Kaiser Permanente–Santa Clara Homestead Medical Center
Kaiser Permanente–Santa Rosa Medical Center
Kaiser Permanente–South Bay Medical Center
Kaiser Permanente–South Sacramento Medical Center
Kaiser Permanente–South San Francisco Medical Center
Kaiser Permanente–Sunnyside Medical Center
Kaiser Permanente–Vacaville Medical Center
Kaiser Permanente–Walnut Creek Medical Center
Kaiser Permanente–West Los Angeles Medical Center
Kaiser Permanente–Woodland Hills Medical Center
Rochester Methodist Hospital
Sentara Bayside
Sentara CarePlex
Sentara Leigh Hospital
Sentara Norfolk General Hospital
Sentara Virginia Beach General Hospital
Sentara Williamsburg Regional Medical Center
Skokie Hospital
St. Mary’s Hospital of Rochester
Stanford Hospital and Clinics
The Heart Hospital
Tucson Medical Center
UC San Diego Medical Center–Hillcrest
UC San Diego Medical Center–Thornton Hospital
University of Wisconsin–Hospital and Clinics
Seoul National University Bundang Hospital
Universitätsklinikum Hamburg-Eppendorf
Hospital de Dénia Marina Salud S.A.
City
Wilmington
Madison
Boston
Pittsburgh
Plano
Dallas
Bolivar
Evansville
Newburgh
Evansville
Evanston
Winter Park
Glenview
Highland Park
Anaheim
Antioch
Baldwin Park
Bellflower
Fontana
Fremont
Fresno
Hayward
Los Angeles
Manteca
Honolulu
Modesto
Moreno Valley
Oakland
Irvine
Panorama City
Redwood City
Richmond
Riverside
Roseville
Sacramento
San Diego
San Francisco
San Jose
San Rafael
Santa Clara
Santa Rosa
Harbor City
Sacramento
San Francisco
Clackamas
Vacaville
Walnut Creek
Los Angeles
Woodland Hills
Rochester
Virginia Beach
Hampton
Norfolk
Norfolk
Virginia Beach
Williamsburg
Skokie
Rochester
Stanford
Newburgh
Tucson
San Diego
La Jolla
Madison
Seoul
Hamburg
Denia
State
DE
WI
MA
PA
TX
TX
MO
IN
IN
IN
IL
FL
IL
IL
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
HI
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
OR
CA
CA
CA
CA
MN
VA
VA
VA
VA
VA
VA
IL
MN
CA
IN
AZ
CA
CA
WI
KOR
GER
ESP
5
▶▶ 2012 Hospital IT Budget and Expenses
The 2012 Hospital IT budget and expenses report highlights
financial benchmarks that provide a glimpse into IT-related
spending as a percentage of organizations’ overall spending.
Analyses are presented from three different perspectives. First,
the average and median IT operating expenses (OPEX) are
shown as a percentage of total hospital operating expense. This
calculation excludes capital expenses from both the numerator and
the denominator. The second set of ratios shows the average and
median spending ratios for the total IT budget, including both
operating and capital expense (CAPEX) for this fiscal year, as a
percentage of the organizations’ overall operating and capital
expenses. The final set of ratios focuses on the IT department
capital expenses for this fiscal year, as a percentage of the hospital’s
total capital expense. Each set of ratios is examined by hospital
size, hospital type and U.S. census region.
The year 2012 represents an end to the downward trend in these
ratios that were first noticed in 2010. The results of this year suggest
a more positive outlook in the economy. In retrospect, the financial
recession began in September 2007, when unemployment rates
began to rise, lasting until the early months of 2009, when the
bottom of the stock market was reached in February. Since then,
the healthcare industry like other industries, has been wary of
making significant investments outside of the Meaningful Use
and ICD-10 directives. This period coincides with the crisis that
began to directly affect healthcare provider organizations (HCOs).
According to data from HIMSS Analytics, the percentage of
hospitals stating that their IT operating budgets were increasing
continued to fall each quarter in 2010, until the 4th quarter when
we saw a return to more normal spending.
According to an annual analysis by the CMS, national healthcare
spending rose at a rate of 3.9 percent in 2011, identical to what was
reported in 2010. The recession and its resulting decline in the
number of people covered by health insurance have been slowing
the rate of healthcare spending since 2007. In 2010, according to
CMS projections, healthcare spending will stay at 17.6 percent of
GDP, the same rate for two years. Healthcare spending slowed
across all sources, including the federal government, state
governments, private employers and individuals.
The impact on hospitals was largely attributable to two factors—
a drop in utilization—especially elective type procedures—which
are generally tracked to unemployment, and the 3.4 percent reduction
in Medicare’s private health plan payments. By early 2011, lingering
unemployment and the expiration of COBRA benefits continued to
slow elective admissions in many hospitals.1, 2, 3, 4
In November and December of 2011, we began to see some growth
in the national employment rate. The unemployment rate began to
tick down below the nine percent range where it had been stuck for
most of 2011 and ended at 7.7 percent in November of 2012. The
number of layoffs in U.S. hospitals in 2012 was on par with the
2011 number and below the levels in 2009 and 2010 respectively
according to the BLS. In 2012, there were an estimated 124 “mass
layoffs” at U.S. hospitals (affecting 50 or more employees at once, a
BLS definition) compared to 120 in 2011, 137 in 2010, and 152 in
2009. Even though the overall economy is improving and
employment is growing, including in the healthcare sector, the
number of “mass layoffs” is similar to 2011. The most common
reason cited is impending reductions in Medicare and Medicaid
payments. Other data from HIMSS Analytics indicates that hospital
consolidation continues to increase, though at a markedly slower
pace. In 2012, the number of hospitals per IDN was 7.0 compared to
6.9 in 2011, a positive increase of only 1.45 percent, and
considerably less than a growth of 4.55 percent in 2011 over 2010.
Some evidence exists to point to an increase in hospital capital
spending, possibly spurred on by the assumption of a decrease in
cash flow after 2014 when planned Medicare reductions take place
due to the ACA. Of course, increased admissions from expanded
coverage availability may offset that decrease from Medicare. That
remains to be seen. The notable slowdown in in the number of
hospitals per IDN show that very large capital spending may be
slowing until hospitals have a better feel for the economic
environment in 2014 and beyond.
The average and median ratio of IT department operating expense
to total hospital operating expense increased from 2011 to 2012
(see Table HB1).
When examining the ratio of the total IT budget (includes
operating and capital expenses for this year) to total hospital
operating expense, the average and median ratio decreased from
2011 to 2012; these ratios remain, however, above what was
reported in 2010 (see Table HB2).
Ratios related to the hospital’s capital expense to the hospital’s
overall capital expense increased from 2010 to 2011 and again from
2011 to 2012. Both the average and median ration increased during
this time (see Table HB3).
Ta ble hB1
% of Total IT Operating Expense/Total
Hospital Operating Expense-Overall
Avg
Median
N
2010
2.40%
1.93%
471
2011
2.39%
2.11%
475
2012
2.74%
2.27%
400
2010
2.77%
2.26%
469
2011
4.87%
3.92%
436
2012
3.21%
2.66%
479
2010
17.32%
10.27%
211
2011
17.89%
12.14%
300
2012
20.22%
14.10%
244
Ta ble hB2
% of Total IT Budget/Total Hospital
Expense–Overall
Avg
Median
N
Ta ble hB 3
% IS Capital Expense/Total Hospital
Capital Expense–Overall
Avg
Median
N
1 By 2018, national health spending is expected to reach $4.4 trillion and comprise just over one-fifth (20.3 percent) of Gross Domestic Product (GDP). http://www.cms.gov/Research-Statistics-
Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/proj2008.pdf
2 The actuaries estimate that health spending will account for 19.6 percent of the gross domestic product (GDP) in 2021, up from 17.9 percent in 2010. http://www.govhealthit.com/news/cms-
estimates-healthcare-will-soar-one-fifth-gdp
3 For 2011–13, U.S. health spending is projected to grow at 4.0 percent, on average—slightly above the historically low growth rate of 3.8 percent in 2009. (Published June 2012) http://content.
healthaffairs.org/content/early/2012/06/11/hlthaff.2012.0404
4 In 2014, health spending growth is expected to accelerate to 7.4 percent as the major coverage expansions from the Affordable Care Act begin. (Published June 2012) http://content.healthaffairs.
org/content/early/2012/06/11/hlthaff.2012.0404
▶▶ 2012 Hospital IT Budget and Expenses con tinue d
The general increase in the capital and operating expense ratios
appear to be modest. However, this may be viewed as an indicator
that the economy has recovered to a point where hospitals are
beginning to feel more at ease with spending and/or budgeting
increases in 2012.
IT OPEX as a Percentage of Hospital Total OPEX
IT OPEX as a percentage of the hospital total OPEX spending
generally increased from 2011 to 2012 (see Table HB4). Almost all
bed segments experienced a fairly strong increase. The 501–600 bed
Ta ble HB 4
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
2011
Avg % Total
Avg % Total
IT Operating
IT Operating
Expense/
Expense/
Total Hospital
Total Hospital
Operating
Operating
Expense
N
Expense
1.82% 183
1.97%
2.09% 77
2.17%
2.97% 78
2.52%
3.08% 55
2.81%
3.43%
41
3.35%
2.53% 13
3.16%
2.54% 24
2.73%
2.40% 471
2.39%
N
171
91
74
60
37
17
25
475
2012
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
N
2.39% 146
2.50%
74
3.02% 58
2.79%
47
3.47% 29
3.83%
21
2.96% 25
2.74% 400
N
37
438
321
154
84
391
66
409
187
288
2012
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
3.14%
2.70%
2.78%
2.66%
2.22%
2.86%
2.34%
2.82%
3.01%
2.57%
N
38
362
266
134
78
322
67
333
155
245
N
72
15
57
18
49
67
82
59
56
2012
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.98%
3.19%
2.52%
3.22%
2.30%
2.84%
2.53%
2.76%
2.50%
N
68
21
44
29
36
50
54
57
41
Ta ble HB5
Type
Academic
Non-Academic
General Med/Surg
Others
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
2010
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
3.20%
2.33%
2.45%
2.31%
1.76%
2.57%
1.69%
2.56%
2.55%
2.32%
N
39
432
304
167
102
369
88
383
160
311
2011
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.89%
2.35%
2.35%
2.48%
1.79%
2.52%
1.79%
2.49%
2.52%
2.31%
N
77
14
49
25
46
53
77
58
72
2011
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.34%
3.28%
2.44%
2.34%
2.43%
2.46%
2.36%
2.62%
1.86%
Ta ble HB6
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2010
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.60%
2.82%
2.35%
2.41%
3.20%
2.80%
2.26%
2.41%
1.46%
State Key for Regions:
New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA, ME, VT, RI, CT, NH
Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NY, NJ, PA
South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD, DE, DC, WV, VA, NC, SC, GA, FL
East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI
East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL
West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE
West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK
Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM
Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI
segment showed the largest increase at 0.67 percent followed by the
201–300 bed segment (0.50 percent increase) and 0–100 bed
segment (0.42 percent increase), while the 301–400 bed segment
witnessed a negligible decline (.02 points).
In our opinion, this correlates with the general patterns we have
seen with respect to the acquisition and implementation of
electronic medical records (EMRs)—where hospitals in the higher
bed ranges, particularly academic medical centers, implemented
EMRs in larger numbers earlier than those in the middle and lower
bed size categories. However, these earlier deployments in larger
institutions, notably academic medical centers, were often more
“best of breed-like” in their deployments and many now have aging
architectures. With the growth of the integrated clinical systems
offerings and the need for ARRA compliance and reporting, some
of these larger institutions have begun replacing legacy pieces that
may be driving this increase. As these larger institutions progress
further into the operational phase of their EMR deployments, the
increase in expenses typically associated with the implementation
phase declines as does the depreciation expense associated with
these capital intensive projects, which generally have front-loaded
depreciation schedules. During this same period, the most
significant increases in the sales of enterprise EMR systems were
among medium sized hospital, i.e., those in the 301–500 bed range.
Here, we found modest increases in the expense ratios.
An evaluation of the IT OPEX by hospital type showed that
every category demonstrated an increase in IT OPEX from 2011 to
2012 (see Table HB5). Rural hospitals reflected the largest growth
(0.55 percent) followed by multi-hospital systems (0.49 percent),
and critical access and general medical/surgical types (both at
0.43 percent growth).
On a U.S. regional level, the IT OPEX growth occurred for most
regions except for the East South Central and New England regions.
The Mountain region reported the highest year-over-year growth of
almost a full percent (0.88 percent) followed by East North Central
and West South Central regions, at 0.64 percent growth each (see
Table HB6).
The median IT OPEX ratios for hospital bed size segments shows
virtually all of the segments have increased from 2011 to 2012
except the 301–400 bed segment (see Table HB7). The largest
growth occurred among large hospitals. Growth in both the 401–500
and 501–600 bed segments is 0.33 percent.
Ta ble HB7
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
2011
2012
Median % Total
Median % Total
Median % Total
IT Operating
IT Operating
IT Operating
Expense/Total
Expense/Total
Expense/Total
Hospital
Hospital
Hospital
Operating
Operating
Operating
Expense
N
Expense
N
Expense
N
1.56% 183
1.70% 171
2.00% 146
1.73% 77
1.98% 91
2.05% 74
2.13% 78
2.20% 74
2.48% 58
2.74% 55
2.75% 60
2.54% 47
3.23% 41
3.13% 37
3.46% 29
2.43% 13
3.17% 17
3.50% 21
2.32% 24
2.53% 25
2.62% 25
1.93% 471
2.11% 475
2.27% 400
7
Upon evaluating the median operating expense ratio by hospital
type category, all categories indicated a growth in IT OPEX (see
Table HB8). The highest growth was among the rural hospital
segment (0.42 percent), critical access hospitals (0.38 percent) and
multi-hospital systems (0.38 percent).
From 2011 to 2012, most of the U.S. regions indicated IT OPEX
growth except Middle Atlantic (see Table HB9). The highest growth
occurred in the East South Central region at one percent followed
by Mountain region (0.77 percent).
IT Spending as a Percentage of Hospital Total Spending Including CAPEX
The average total IT budget as a percent of the total hospital
operating expense (the average budget ratio) across various hospital
segments is shown in Tables HB10–HB12. Overall, the IT budget
ratio increased from 2011 to 2012. Based on the 2012 data, it
appears as if the 2010 data was an anomaly and that the 2012 and
2011 data are more comparable than 2010 data.
An evaluation of the average IT budget ratio by bed segmentation
shows that the average ratio of four of the seven bed size segments
indicated an increase from 2011 to 2012 (0–100, 201–300, 501–600
beds and over 600 beds), ranging from 0.06 percent to 1.39 percent
(501–600 beds) (see table HB10). The remaining segments showed
a decrease from 2011, ranging from 0.18 percent to 0.32 percent,
with the largest decrease among hospitals with between 401 and
500 beds.
Ta ble HB8
2010
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Type
Expense
Academic
2.78%
Non-Academic
1.86%
General Med/Surg
2.00%
Others
1.86%
Critical Access
1.53%
Non-Critical Access
2.12%
Rural
1.34%
Urban
2.12%
1.92%
1.93%
N
39
432
304
167
102
369
88
383
160
311
2011
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Expense
2.80%
2.01%
2.13%
1.99%
1.52%
2.21%
1.53%
2.21%
2.16%
2.07%
N
77
14
49
25
46
53
77
58
72
2011
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Expense
2.14%
1.83%
2.29%
2.05%
2.38%
2.25%
1.89%
1.88%
1.25%
N
37
438
321
154
84
391
66
409
187
288
2012
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Expense
2.85%
2.18%
2.29%
2.23%
1.90%
2.36%
1.95%
2.38%
2.54%
2.15%
N
72
15
57
18
49
67
82
59
56
2012
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Expense
2.22%
2.83%
2.20%
2.82%
2.46%
2.76%
2.17%
1.96%
1.84%
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
The Pacific, East North Central and Mountain regions are the only
segments to indicate an increase in spending ratio from 2011 to
2012, ranging from 0.16 percent to 1.58 percent (see Table HB12).
All other regions indicated a decrease in the spending ratio with
the largest decrease occurring in the West South Central region at
0.80 percent.
Ta ble HB10
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
Avg of Total
IT Budget as
% of Total
Hospital
Expense
N
2.04% 179
2.39% 72
3.59% 79
3.22% 57
3.80%
41
3.20% 13
3.47% 28
2.77% 469
2011
Avg of Total
IT Budget as
% of Total
Hospital
Expense
N
4.44% 149
4.92% 78
4.85% 78
5.22% 52
6.00% 38
5.47% 16
4.52% 25
4.87% 436
2012
Avg of Total
IT Budget as
% of Total
Hospital
Expense
N
4.66% 140
4.73% 69
4.91% 67
5.04% 45
5.68%
31
6.86%
17
5.05% 26
4.96% 395
2010
Avg of Total
IT Budget as
% of Total
Hospital
Expense
N
3.34% 46
2.71% 423
2.84% 300
2.64% 169
3.06% 148
2.63% 321
2.16% 99
2.93% 370
2.02% 86
2.94% 383
2011
Avg of Total
IT Budget as
% of Total
Hospital
Expense
4.80%
4.88%
4.85%
4.92%
4.57%
4.94%
4.69%
4.91%
5.71%
4.44%
2012
Avg of Total
IT Budget as
% of Total
Hospital
Expense
N
5.06% 38
4.95% 357
5.12% 269
4.61% 126
4.13% 75
5.15% 320
4.63% 69
5.03% 326
6.04% 140
4.36% 255
2010
Avg of Total
IT Budget as
% of Total
Hospital
Expense
2.70%
3.02%
2.72%
2.76%
3.25%
3.22%
2.95%
2.71%
1.73%
2011
Avg of Total
IT Budget as
% of Total
Hospital
Expense
4.96%
4.28%
4.64%
7.66%
3.73%
4.92%
6.02%
4.94%
3.69%
Ta ble HB11
N
38
362
266
134
78
322
67
333
155
245
Ta ble HB9
2010
Median % Total
IT Operating
Expense/Total
Hospital
Operating
Expense
1.75%
2.28%
1.97%
1.93%
2.58%
2.24%
2.12%
2.04%
1.00%
Several of the hospital types have indicated an increase in total IT
spending to total hospital spending ratio (see Table HB11). These
hospital types include academic, non-academic, general medical/
surgical, non-critical access, urban and multi-hospital systems. The
increase in ratio ranged from 0.07 percent (non-academic facilities)
to 0.33 percent (multi-hospital segment). The hospital types that
demonstrated a decrease in ratio are “other” non-general medical/
surgical, critical access, rural and single hospital systems. The
decrease in ratio ranged from 0.06 percent to 0.44 percent. The
largest decrease was among critical access hospitals.
Type
Academic
Non-Academic
General Med/Surg
Others
Critical Access
Non-Critical Access
Rural
Urban
N
40
396
290
146
79
357
68
368
148
288
Ta ble HB12
N
68
21
44
29
36
50
54
57
41
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
N
87
20
60
21
50
43
77
63
48
N
75
19
59
20
53
39
63
62
46
2012
Avg of Total
IT Budget as
% of Total
Hospital
Expense
5.17%
4.18%
4.38%
7.82%
3.56%
6.50%
5.79%
4.14%
3.56%
N
70
21
47
33
44
31
55
58
36
Tables HB13–HB15 represent the median of total IT budget as a
percent of the total hospital operating expense (median budget ratio)
in the various hospital segments.
By bed segmentation, 0–100, 201–300, 301–400 and 501–600
bed segments indicated an increase in ratio from 2011 to 2012,
ranging from 0.13 percent to 1.41 percent (501–600 bed segment)
(see Table HB13).
The ratio across almost all of the hospital type market segments,
except “other” non-general medical/surgical hospitals and single
hospital systems, indicated an increase from 2011 to 2012,
ranging from 0.05 percent to 0.26 percent (multi-hospital system)
(see Table HB14).
As for the U.S. regions, almost all of them, excluding Middle
Atlantic and West North Central, indicated an increase in spending
ratio, with the Mountain region demonstrating the highest increase
at 1.79 percent (see Table HB15).
Ta ble HB13
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
2011
2012
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Expense
N
Expense
N
Expense
N
1.77% 179
3.30% 149
3.72% 140
2.15% 72
4.08% 78
3.65% 69
2.77% 79
3.98% 78
4.13% 67
2.98% 57
4.29% 52
4.32% 45
4.12%
41
5.11% 38
5.06%
31
3.41% 13
4.19% 16
5.60%
17
2.93% 28
4.14% 25
4.07% 26
2.26% 469
3.92% 436
4.05% 395
IT Capital Expenses as a Percentage of Hospital Total Capital Expenses
An evaluation of average total IT capital expenses (last fiscal year)
to total hospital capital expenses (capital ratios) is shown in tables
HB16–HB18. Overall, the general ratio increased across most of the
segments from 2011 to 2012 continuing an upward trend based on
the increase reported from 2010 to 2011. The economic recovery
may be the driving influence in capital spending.
By bed segments, only the 101–200 and over 600 bed segments
indicated a decrease in the average capital expense ratio (see Table
HB16). Each of these segments showed an approximate two percent
decline. The remaining bed segments demonstrated a growth in
capital spending ratio from 2011 to 2012, ranging from 2.01 percent
to 8.65 percent (501–600 bed segment). The increase is not
statistically significant due to the small population size in 2010,
2011 and 2012.
An evaluation by hospital types shows that only academic medical
centers indicated a decline from 2011 to 2012 in capital expenses
(0.88 percent) (see Table HB17). The remaining hospital types have
indicated growth in IT capital spending ranging from 0.26 percent
to 6.25 percent (multi-hospital system).
As for the U.S. region, the average IT capital expense spending
ratios are mixed. Five of the nine regions (East South Central,
Middle Atlantic, Mountain, South Atlantic and West North Central)
indicated an increase in spending, ranging from 1.37 percent to
11.07 percent (see Table HB18). The remaining regions demonstrated
a decrease in IT capital spending ratio, ranging from 0.84 percent to
3.51 percent.
Ta ble HB16
Ta ble HB14
2010
2011
2012
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Type
Expense
N
Expense
N
Expense
N
Academic
3.06% 46
4.09% 40
4.13% 38
Non-Academic
2.16% 423
3.90% 396
4.01% 357
General Med/Surg
2.28% 300
3.87% 290
4.13% 269
Others
2.26% 169
4.09% 146
3.92% 126
Critical Access
1.89% 99
3.64% 79
3.66% 75
Non-Critical Access
2.53% 370
3.96% 357
4.16% 320
Rural
1.71% 86
3.47% 68
3.65% 69
Urban
2.54% 383
4.03% 368
4.18% 326
2.52% 148
4.58% 148
4.63% 140
2.20% 321
3.74% 288
3.74% 255
Ta ble HB15
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2010
Median %
Total IT Budget
as % of Total
Hospital
Expense
2.23%
2.11%
2.61%
2.49%
2.73%
3.02%
2.32%
2.18%
1.19%
N
87
20
60
21
50
43
77
63
48
2011
Median %
Total IT Budget
as % of Total
Hospital
Expense
4.04%
3.03%
4.32%
4.72%
3.48%
4.24%
3.74%
4.25%
2.74%
N
75
19
59
20
53
39
63
62
46
2012
Median %
Total IT Budget
as % of Total
Hospital
Expense
4.13%
3.78%
3.77%
6.51%
3.58%
4.74%
4.37%
4.05%
2.86%
N
70
21
47
33
44
31
55
58
36
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
17.26%
18.78%
16.19%
15.85%
19.51%
25.26%
13.87%
17.32%
N
74
33
36
26
22
5
15
211
2011
2012
Avg % Total
Avg % Total
IT Capital
IT Capital
Expense Last
Expense Last
Year/Total
Year/Total
Hospital
Hospital
Capital Expense
N Capital Expense
N
17.77% 99
22.22% 75
18.01% 54
16.19% 45
16.50% 51
18.51% 39
17.52%
41
21.89% 34
24.73% 27
27.38% 19
13.16% 11
21.81%
14
15.40%
17
13.74% 18
17.89% 300
20.22% 244
Ta ble HB17
2010
2011
2012
Avg % Total
Avg % Total
Avg % Total
IT Capital
IT Capital
IT Capital
Expense Last
Expense Last
Expense Last
Year/Total
Year/Total
Year/Total
Hospital
Hospital
Hospital
Type
Capital Expense
N Capital Expense
N Capital Expense
N
Academic
16.27% 19
14.05% 28
13.17% 26
Non-Academic
17.43% 192
18.28% 272
21.06% 218
General Med/Surg
17.88% 141
18.28% 203
20.97% 170
Others
16.20% 70
17.07% 97
18.51%
74
Critical Access
15.74% 38
18.88% 46
22.62% 36
Non-Critical Access
17.67% 173
17.71% 254
19.81% 208
Rural
17.69% 35
17.60% 38
18.80% 33
Urban
17.25% 176
17.93% 262
20.44% 211
12.35% 79
16.05% 99
22.30% 88
20.30% 132
18.79% 201
19.05% 156
9
An evaluation of median total IT capital expenses to total hospital
capital expenses (capital ratios) is shown in tables HB19–HB21. As
with the average ratio, the median ratio also increased across most
of the segments in the past year.
Ta ble HB18
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2010
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
19.08%
8.72%
17.53%
22.12%
19.44%
19.75%
13.46%
18.68%
16.31%
N
28
7
23
10
15
15
29
37
47
2011
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
19.38%
25.67%
14.77%
20.97%
19.29%
16.33%
18.92%
17.21%
15.79%
N
52
10
41
10
38
22
41
43
43
2012
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
15.87%
42.74%
17.55%
32.10%
17.46%
15.24%
25.34%
18.58%
14.95%
N
40
12
34
18
27
18
31
34
30
Ta ble HB19
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
Over 600 beds
Total
2010
Median %
IT Capital
Expense/
Total Hospital
Capital Expense
10.13%
9.42%
9.16%
10.24%
10.32%
17.45%
12.92%
10.27%
N
74
33
36
26
22
5
15
211
2011
2012
Median %
Median %
IT Capital
IT Capital
Expense/
Expense/
Total Hospital
Total Hospital
Capital Expense
N Capital Expense
N
12.20% 99
16.05% 75
11.04% 54
10.69% 45
14.41% 51
13.50% 39
11.18%
41
11.88% 34
18.33% 27
29.33% 19
12.98% 11
17.71%
14
11.96%
17
11.28% 18
12.14% 300
14.10% 244
Ta ble HB20
2010
2011
2012
Median %
Median %
Median %
IT Capital
IT Capital
IT Capital
Expense/
Expense/
Expense/
Total Hospital
Total Hospital
Total Hospital
Type
Capital Expense
N Capital Expense
N Capital Expense
N
Academic
10.26% 19
12.39% 28
12.33% 26
Non-Academic
10.34% 192
12.14% 272
15.37% 218
General Med/Surg
11.34% 141
11.96% 203
15.91% 170
Others
9.97% 70
12.32% 97
13.68%
74
Critical Access
8.93% 38
11.43% 46
14.76% 36
Non-Critical Access
11.34% 173
12.21% 254
13.75% 208
Rural
11.10% 35
8.99% 38
14.12% 33
Urban
10.26% 176
12.50% 262
14.09% 211
7.13% 79
10.38% 99
11.96% 88
13.45% 132
12.96% 201
14.39% 156
Ta ble HB21
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2010
Median %
IT Capital
Expense/
Total Hospital
Capital Expense
14.30%
8.06%
13.24%
14.92%
8.75%
11.10%
9.13%
14.68%
6.64%
N
28
7
23
10
15
15
29
37
47
2011
Median %
IT Capital
Expense/
Total Hospital
Capital Expense
11.89%
19.92%
11.84%
18.76%
11.84%
12.56%
11.50%
14.18%
9.86%
N
52
10
41
10
38
22
41
43
43
2012
Median %
IT Capital
Expense/
Total Hospital
Capital Expense
12.40%
36.63%
16.98%
33.44%
13.48%
9.69%
18.80%
12.79%
7.00%
N
40
12
34
18
27
18
31
34
30
An analysis of hospital bed segments indicates that the majority
of the bed segments indicated an increase in median spending
ratio, ranging from 0.70 percent to 11 percent (see Table HB19).
The largest increase was among hospitals with 401–500 beds.
The bed segments that indicated a decrease in spending were
101–200, 201–300 and over 600 bed segments. All decreases were
less than one percent.
With the exception of academic medical centers, all of the hospital
types indicated an increase in IT capital spending from 2011 to
2012, ranging from 1.36 percent to 5.13 percent (rural hospitals)
(see Table HB20). The decrease among academic medical centers
was small at .06 percent.
The regional analysis indicated that almost all of the regions have
shown an increase in the ratio from 2011 to 2012 (see Table HB21).
The increase in ratio ranged from 0.50 percent to 16.71 percent.
The West North Central, West South Central and Pacific regions
showed a decrease in this metric.
Market Drivers/Future Outlook
Despite the declines we saw in recent years, we expect the general
trend in both average and median ratios to gradually increase as the
U.S. shows signs of an economic recovery, and as federal healthcare
policies and subsidies combine to drive IT spending higher. There is
evidence that patient volumes are rebounding too, attributable to an
aging population as well a growing workforce. Also, as cited above,
there is a sense that capital spending in general (for plant and
equipment) is increasing for the short-term in anticipation of tougher
cash flow times ahead. However, very large capital outlays, such as
for acquisition of other hospitals, may be under greater constraints.
Hospitals are facing a series of major IT initiatives with significant
budgetary and cash flow implications. At the top of this list is the
need to continue to acquire, install, expand and/or optimize EMR
applications to meet the Stage 1 and Stage 2 Meaningful Use
criteria. In 2013 and 2014, hospitals must also begin to ramp up for
the implementation of ICD-10 encoding upgrades in 2014—
upgrades that will impact a broad range of financial, health
information management and clinical systems. Also by 2014,
hospitals will need to have enhanced their EMRs to meet Stage 2
Meaningful Use criteria and, by 2015, Stage 3, or they will begin
to face financial penalties for non-compliance.
As IDNs ambulatory portfolio continues to grow, some consolidation
around a common AEMR and a practice management system will
continue to drive some replacement activity. This additional source of
patient care data will also drive some infrastructure upgrades in IDN
data centers, or see an increasing use of outsourced data centers.
For clinicians, the need for ubiquitous access to EMR data of
varying types from inpatient and ambulatory sources—including
digital images—will necessitate improved wired and wireless
network capacity; higher investments in mobile point-of-care
devices; improved security; and more robust remote web access.
These upgrades to hospital application portfolios will drive
spending on IT infrastructure higher as well. As more missioncritical, patient clinical data is transformed into digital form, system
performance and reliability will become even more important, and
costly, for those hospitals that host their own data centers.
This massive growth of clinical data is not going unnoticed by
hospital boards and leadership who are expecting the wealth of
information to turn into a competitive advantage. C&BI is a growth
area for hospitals and the early leaders appear to be the large IDNs
who are positioning themselves to be ACOs. Investments in mass
data storage, vendor neutral archives, and C&BI skills and tools are
driving some significant data center investments, and selective
outsourcing of data storage.
While virtualization of both servers and workstations will help to
mitigate some of the associated cost increases, most of these costs
will be inescapable. Even hospitals that remotely host their
applications will see corresponding cost increases as their service
partners will also be forced to provide the necessary additional
capacity and services. It is also likely that the virtualization
phenomenon that we are seeing with servers and workstations will
rapidly spread to storage, as well with vendor neutral archives being
a hosted service.
However, some of the costs associated with these trends may not
necessarily be fully reflected in our metrics. Based on our
experience with past initiatives, many of these anticipated expenses
will be in the form of increased consulting costs and additional
non-IT labor costs, including nursing and other clinical personnel,
as well as specialty personnel in billing, finance and health
information management. Although attributable to IT projects, these
costs are often not charged back to IT cost centers. Also, increased
mass storage costs directly attributable to medical and pathology
imaging may be charged to those departments. Our evidence shows
that this is more likely in the larger hospital market.
▶▶ Financial Management
HIMSS Analytics monitors four financial management (FM)
applications—accounts payable, enterprise resource planning
(ERP), general ledger and materials management. Of these
applications, three are highly saturated markets with installation
rates exceeding 97 percent (see Table FM1). Not too surprisingly,
each of these three applications indicated little or no growth from
2011 to 2012. The fourth application in this category, the ERP
application, has an installed base of only 27 percent. The year-overyear growth of ERP has held steady at approximately two percent
per year since 2010.
ERP applications typically replace legacy, stand-alone accounts
payable, general ledger and materials management, and possibly
human resource solutions. That the ERP market may not be as
saturated, as general ledger, materials management and accounts
payable may be attributed to the fact that these solutions are not sold
as an ERP suite, or hospitals may still be running on legacy systems.
We have said in past Annual Reports that we believed that ERP
implementations would increase as hospitals consolidate and try to
drive supply chain efficiencies. However, we are not seeing that at
this time. It is obvious that CIOs are consumed with implementing
clinical systems to meet Meaningful Use requirements that have a
Ta ble F M1 | Financial Management
N=4,217
2010
2011
Accounts Payable
99.79%
99.86%
Enterprise Resource Planning
22.69%
24.19%
General Ledger
99.79%
99.83%
Materials Management
96.92%
97.44%
Percentages include installed, contracted or installation in process
2012
99.86%
26.82%
99.83%
97.82%
cash incentive attached. It appears that major consolidations around
an ERP will have to wait until after 2015.
As expected, most of the planned purchases for applications in the
financial management suite are from replacement buyers. The
exception being ERP, where nearly two-thirds of planned purchases
are attributed to first-time purchasers (see Table FM2).
An examination of the financial management application market
segment by hospital type reveals the following highlights:
• Accounts payable: this market is almost 100 percent saturated
across all hospital types (see Table FM3). No growth activities
were reported across all segments.
• ERP: with a market penetration of 49 percent, academic medical
centers have the highest adoption rate among the various U.S.
hospitals segments considered in this report (see Table FM4).
Rural hospitals on the other hand, are the least penetrated
hospital segment (10.4 percent). Multi-hospital systems reported
the largest increase in installations from 2011 to 2012 at more
than three and half percent, followed closely by general medical/
surgical and non-critical access hospitals.
• General ledger: more than 99 percent of U.S. hospitals have
adopted general ledger technology (see Table FM5). The level of
adoption has not changed from 2011 to 2012 across the different
hospital segments.
• Materials management: this market has achieved almost complete
market saturation (see Table FM6). Most of the hospital segments
reflected a slight increase in the past year, with the critical access
(1.4 percent) and rural hospital (1.2 percent) segments reporting
the greatest increase.
Ta ble F M2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Accounts Payable
58
100.00%
3
37.50%
General Ledger
59
100.00%
45
88.24%
Replacing = Statuses of live and operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
0
5
0
6
% of Hospitals Planning
for the First Time
0.00%
62.50%
0.00%
11.76%
N = Total Number of
Hospitals Planning
58
8
59
51
11
▶▶ Financial Management con tinued
Ta ble F M3 | Accounts Payable
2010
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
4,030
2,449
1,759
1,145
3,063
974
3,234
2,585
1,623
4,208
Percent
100.00%
99.78%
99.88%
99.66%
99.74%
99.80%
99.80%
99.78%
99.69%
99.94%
99.79%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
4,034
2,452
1,759
1,146
3,065
976
3,235
2,588
1,623
4,211
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
83
937
661
359
121
899
78
942
844
176
1,020
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
4,033
2,452
1,758
1,145
3,065
975
3,235
2,588
1,622
4,210
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,931
2,437
1,672
1,064
3,045
904
3,205
2,564
1,545
4,109
Percent
99.44%
99.88%
100.00%
99.66%
99.83%
99.87%
100.00%
99.81%
99.81%
99.94%
99.86%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
4,034
2,452
1,759
1,146
3,065
976
3,235
2,588
1,623
4,211
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
87
1,044
746
385
137
994
101
1,030
940
191
1,131
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
4,033
2,452
1,758
1,145
3,065
975
3,235
2,588
1,622
4,210
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,947
2,437
1,688
1,080
3,045
916
3,209
2,567
1,558
4,125
Percent
99.44%
99.88%
100.00%
99.66%
99.83%
99.87%
100.00%
99.81%
99.81%
99.94%
99.86%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F M4 | Enterprise Resource Planning
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
78
879
622
335
114
843
76
881
794
163
957
Percent
43.82%
21.76%
25.37%
18.98%
9.93%
27.47%
7.79%
27.18%
30.62%
10.04%
22.69%
2011
Percent
46.63%
23.20%
26.96%
20.34%
10.54%
29.29%
7.99%
29.07%
32.55%
10.84%
24.19%
2012
Percent
48.88%
25.85%
30.42%
21.81%
11.93%
32.39%
10.35%
31.78%
36.25%
11.76%
26.82%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F M5 | General Ledger
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
4,030
2,450
1,758
1,144
3,064
974
3,234
2,586
1,622
4,208
Percent
100.00%
99.78%
99.92%
99.60%
99.65%
99.84%
99.80%
99.78%
99.73%
99.88%
99.79%
2011
Percent
99.44%
99.85%
100.00%
99.60%
99.74%
99.87%
99.90%
99.81%
99.81%
99.88%
99.83%
2012
Percent
99.44%
99.85%
100.00%
99.60%
99.74%
99.87%
99.90%
99.81%
99.81%
99.88%
99.83%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F M6 | Materials Management
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
3,909
2,428
1,659
1,052
3,035
887
3,200
2,556
1,531
4,087
Percent
100.00%
96.78%
99.02%
93.99%
91.64%
98.89%
90.88%
98.73%
98.57%
94.27%
96.92%
2011
Percent
100.00%
97.33%
99.39%
94.73%
92.68%
99.22%
92.62%
98.89%
98.88%
95.14%
97.44%
2012
Percent
100.00%
97.72%
99.39%
95.64%
94.08%
99.22%
93.85%
99.01%
99.00%
95.94%
97.82%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
When evaluating the market by bed size segments, the following
are notable changes from 2011 to 2012:
• 0–100 beds: ERP and materials management are the only
financial management applications to grow during this period
(see Table FM7).
• 101–200 beds: ERP demonstrated growth of just over three
percent, while the other financial management applications
demonstrated no change (see Table FM8).
• 201–300 beds: ERP is the only application that demonstrated
growth from 2011 to 2012 at more than three and a half percent.
The install base of materials management applications decreased
slightly (see Table FM9).
Ta ble F M7
0–100 Beds
Accounts Payable
General Ledger
2010
2,156
308
2,156
2,042
99.58%
14.23%
99.58%
94.32%
2011
2012
% of 2,165 Hospitals
2,160 99.77% 2,160 99.77%
335 15.47%
376 17.37%
2,159 99.72% 2,159 99.72%
2,060 95.15% 2,077 95.94%
Ta ble F M8
101–200 Beds
Accounts Payable
General Ledger
2010
802 100.00%
192 23.94%
802 100.00%
797 99.38%
2011
% of 802 Hospitals
802 100.00%
204 25.44%
802 100.00%
799 99.63%
2012
802 100.00%
229 28.55%
802 100.00%
799 99.63%
Ta ble F M9
201–300 Beds
Accounts Payable
General Ledger
2010
483 100.00%
145 30.02%
483 100.00%
483 100.00%
2011
% of 483 Hospitals
483 100.00%
152 31.47%
483 100.00%
483 100.00%
2012
483 100.00%
169 34.99%
483 100.00%
482 99.79%
Ta ble F M10
301–400 Beds
Accounts Payable
General Ledger
2010
312 100.00%
111 35.58%
312 100.00%
311 99.68%
2011
% of 312 Hospitals
312 100.00%
120 38.46%
312 100.00%
312 100.00%
2012
312 100.00%
132 42.31%
312 100.00%
312 100.00%
Ta ble F M11
401–500 Beds
Accounts Payable
General Ledger
2010
188 100.00%
77 40.96%
188 100.00%
187 99.47%
2011
% of 188 Hospitals
188 100.00%
78 41.49%
188 100.00%
188 100.00%
2012
188 100.00%
84 44.68%
188 100.00%
188 100.00%
Ta ble F M12
501–600 Beds
Accounts Payable
General Ledger
2010
116 100.00%
54 46.55%
116 100.00%
116 100.00%
2011
% of 116 Hospitals
115 99.14%
55 47.41%
115 99.14%
116 100.00%
2012
115 99.14%
58 50.00%
115 99.14%
116 100.00%
Ta ble F M13
Over 600 beds
Accounts Payable
General Ledger
2010
151 100.00%
70 46.36%
151 100.00%
151 100.00%
2011
% of 151 Hospitals
151 100.00%
76 50.33%
151 100.00%
151 100.00%
2012
151 100.00%
83 54.97%
151 100.00%
151 100.00%
• 301–400 beds: At close to four percent, ERP had the highest growth
in this segment when compared to the other bed size groupings. The
remaining three applications, which have already achieved full market
saturation, reported no growth from 2011 to 2012 (see Table FM10)
• 401–500 beds: General ledger, materials management and
accounts payable reached full market maturation in 2010 and
have maintained complete saturation in 2012 (see Table FM11).
Use of ERP solutions grew at slightly more than three percent.
• 501–600 beds: ERP is the only financial management application
that demonstrated growth at more than two percent from 2011 to
2012. Materials management reached full market saturation in
2010 and continues to be saturated at this time (see Table FM12).
• Over 600 beds: Close to five percent of growth was reported for
ERP in this segment while all other financial management
applications maintained market saturation (see Table FM13).
A historical review of financial management application contracts
reveals that approximately ten percent of all contracts were signed
between 2010 and 2012. Approximately half of all financial
management application contracts were signed between 2000 and
2009 (see Tables FM14–FM15).
Purchase activities in this area are being subordinated to
Meaningful Use deployments even though some financial
management applications are near the end of their useful lives. Some
replacement activity was driven by the ICD-10 conversion, but we
expect most of that to have been accomplished by this time since
the original ICD-10 conversion was set for October 2013.
Ta ble F M14
Accounts Payable
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
120
224
919
827
556
341
2,987
2,987
2,987
2,987
2,987
2,987
2,987
2,987
4.02%
7.50%
30.77%
27.69%
18.61%
11.42%
100.00%
0
19
206
203
87
71
586
586
586
586
586
586
586
586
0.00%
3.24%
35.15%
34.64%
14.85%
12.12%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
91
220
916
881
539
337
2,984
2,984
2,984
2,984
2,984
2,984
2,984
2,984
3.05%
7.37%
30.70%
29.52%
18.06%
11.29%
100.00%
70
178
662
876
576
314
2,676
2,676
2,676
2,676
2,676
2,676
2,676
2,676
2.62%
6.65%
24.74%
32.74%
21.52%
11.73%
100.00%
Ta ble F M15
General Ledger
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
13
The financial management IT application market has been and
will continue to be impacted through 2013 by:
• Competing IT initiatives (e.g. EHRs, and ICD-10 coding
conversion projects) leaving relatively little capital funding or
resources available for the upgrade or replacement of financial
management applications.
• Access to capital for replacing older legacy applications and
budget battles that assign financial management system
replacements a lower priority than high profile, governmentmandated clinical systems with incentive dollars to be earned.
• Replacement of legacy general ledger, accounts payable, and
materials management application systems by ERP systems,
particularly in hospitals with more than 400 beds.
• Some revenue cycle system replacements for those IDNs that
qualify as ACOs.
Beyond 2013, we see potential resurgence in purchasing activity
in this area, driven by:
• The need to improve supply chain management processes and
lower supply costs.
• The need to incorporate newer, more automated supply chain
workflows.
• The need for more accurate and flexible accounting, resulting
from mergers, acquisitions and divestitures among hospital
systems.
• Improved integration with financial decision support and
business analytics software.
• Satisfying the accounting and financial analysis and reporting
requirements associated with ACOs, patient-centered medical
home, and other bundled payment programs related to
healthcare reform.
▶▶ Financial Decision Support Environment
The financial decision support market monitored by HIMSS Analytics
consists of the following seven applications: budgeting, business
intelligence-financial, cost accounting, data warehousing/mining–
financial, executive information systems, financial modeling and
medical necessity checking content. With the increased interest in
C&BI in hospitals, HIMSS Analytics will begin reporting business
intelligence applications separately for financial and clinical functions.
The business intelligence–financial is covered in this chapter for
2012, while the business intelligence–clinical will be reported in the
electronic medical records section in future Annual Reports.
The financial decision support market presents as a maturing market.
Among the seven software solutions tracked in this market, only two
applications had a market penetration of less than 50 percent (business
intelligence-financial and financial modeling). The most commonly
installed application was a budgeting solution (84 percent) (see Table
FDS1). The adoption of financial decision support IT applications
has increased since 2010 and is expected to continue growing
gradually with the exception of the intelligence and warehousing
tools that shows above average activity for this segment.
Ta ble F DS1 | Financial Decision Support
N=4,217
2010
2011
Budgeting
81.86%
82.69%
Business Intelligence–Financial
39.03%
43.18%
Cost Accounting
69.10%
69.81%
Data Warehousing/Mining–Financial
43.13%
46.91%
Executive Information Systems
62.20%
64.33%
Financial Modeling
34.34%
36.42%
Medical Necessity Checking Content
53.50%
58.43%
2012
83.87%
47.55%
70.90%
51.03%
66.21%
39.27%
62.08%
The financial decision support market reflects a mix of hospitals
planning to purchase a solution for the first time, as well as those
intending to replace existing solutions. The majority of purchases
for budgeting, cost accounting, executive information systems and
medical necessity content checking will be replacement purchases,
while more than half of the planned purchases for business
intelligence-financial, data warehousing/mining-financial and
financial modeling will be among hospitals procuring these
solutions for the first time (see Table FDS2).
The evaluation of the financial decision support market by the
various hospital segments yields the following insights:
• Budgeting: critical access, rural and non-general medical/surgical
hospitals indicated a growth of more than two percentage points
from 2011 to 2012 (see Table FDS3). The academic medical
center segment is approaching market saturation and did not
demonstrate any growth in the past year.
• Business intelligence-financial: more than five percentage point
growth was reported for the rural and critical access segments
from 2011 to 2012 (see Table FDS4). All other hospital segments
reported a growth of approximately four percentage points, with
the exception of the academic medical center segment, which
grew by slightly less than three percentage points.
• Cost accounting: both the rural and critical access segments
indicated a growth of approximately two percentage points (see
Table FDS5). Growth in the other segments was limited and there
was no change in adoption among academic medical centers.
Ta ble F DS 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Budgeting
36
94.74%
8
44.44%
Cost Accounting
35
81.40%
7
35.00%
29
80.56%
Financial Modeling
6
46.15%
9
60.00%
for the First Time
2
10
8
13
7
7
6
for the First Time
5.26%
55.56%
18.60%
65.00%
19.44%
53.85%
40.00%
N = Total Number of
Hospitals Planning
38
18
43
20
36
13
15
▶▶ Financial Decision Support Environment con tinue d
• Data warehousing/mining-financial: growth was greatest in the
rural hospital and critical access hospital segments, at slightly
more than five percentage points. Growth in all other segments
was between three to four percentage points (see Table FDS6).
• Executive information systems: critical access hospitals and rural hospitals demonstrated the highest growth from 2011 to 2012 at approximately three percentage points, while the remaining other segments
indicated a growth of one to two percentage points (see Table FDS7).
• Financial modeling: the academic medical center segment
reported the largest increase from 2011 to 2012, at more than
five percentage points (see Table FDS8). The other segments
demonstrated a growth of one to four percentage points.
• Medical necessity checking content: the single hospital segment
demonstrated the largest growth from 2011 to 2012 (more than five
percentage points). All other segments reported growth ranging
from three to slightly under five percentage points (see Table FDS9).
Ta ble F DS 3 | Budgeting
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
169
3,283
2,198
1,254
797
2,655
691
2,761
2,250
1,202
3,452
Percent
94.94%
81.28%
89.64%
71.05%
69.43%
86.51%
70.80%
85.19%
86.77%
74.01%
81.86%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
167
3,320
2,206
1,281
813
2,674
707
2,780
2,259
1,228
3,487
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
118
1,703
1,185
636
245
1,576
191
1,630
1,398
423
1,821
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
165
2,779
1,955
989
618
2,326
525
2,419
1,952
992
2,944
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
116
1,862
1,306
672
280
1,698
221
1,757
1,490
488
1,978
Percent
93.82%
82.20%
89.97%
72.58%
70.82%
87.13%
72.44%
85.78%
87.12%
75.62%
82.69%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
167
3,370
2,215
1,322
843
2,694
730
2,807
2,287
1,250
3,537
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
123
1,882
1,296
709
304
1,701
242
1,763
1,519
486
2,005
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
165
2,825
1,976
1,014
641
2,349
546
2,444
1,978
1,012
2,990
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
124
2,028
1,400
752
341
1,811
274
1,878
1,604
548
2,152
Percent
93.82%
83.44%
90.33%
74.90%
73.43%
87.78%
74.80%
86.61%
88.20%
76.97%
83.87%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F DS 4 | Business Intelligence
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
106
1,540
1,066
580
215
1,431
162
1,484
1,276
370
1,646
Percent
59.55%
38.13%
43.47%
32.86%
18.73%
46.63%
16.60%
45.79%
49.21%
22.78%
39.03%
2011
Percent
66.29%
42.16%
48.33%
36.03%
21.34%
51.35%
19.57%
50.29%
53.91%
26.05%
43.18%
2012
Percent
69.10%
46.60%
52.85%
40.17%
26.48%
55.43%
24.80%
54.40%
58.58%
29.93%
47.55%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F DS5 | Cost Accounting
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
164
2,750
1,944
970
604
2,310
510
2,404
1,934
980
2,914
Percent
92.13%
68.09%
79.28%
54.96%
52.61%
75.27%
52.25%
74.17%
74.59%
60.34%
69.10%
2011
Percent
92.70%
68.80%
79.73%
56.03%
53.83%
75.79%
53.79%
74.64%
75.28%
61.08%
69.81%
2012
Percent
92.70%
69.94%
80.59%
57.45%
55.84%
76.54%
55.94%
75.41%
76.28%
62.32%
70.90%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F DS6 | Data Warehousing/Mining–Financial
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
107
1,712
1,176
643
272
1,547
203
1,616
1,384
435
1,819
Percent
60.11%
42.39%
47.96%
36.43%
23.69%
50.41%
20.80%
49.86%
53.37%
26.79%
43.13%
2011
Percent
65.17%
46.10%
53.26%
38.07%
24.39%
55.33%
22.64%
54.21%
57.46%
30.05%
46.91%
2012
Percent
69.66%
50.21%
57.10%
42.61%
29.70%
59.01%
28.07%
57.95%
61.86%
33.74%
51.03%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
15
Ta ble F DS7 | Executive Information Systems
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
134
2,489
1,653
970
513
2,110
429
2,194
1,760
863
2,623
Percent
75.28%
61.62%
67.41%
54.96%
44.69%
68.75%
43.95%
67.70%
67.88%
53.14%
62.20%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
135
2,578
1,713
1,000
535
2,178
451
2,262
1,813
900
2,713
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
101
1,435
989
547
254
1,282
209
1,327
1,107
429
1,536
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
115
2,349
1,627
837
521
1,943
420
2,044
1,669
795
2,464
Percent
75.84%
63.83%
69.86%
56.66%
46.60%
70.97%
46.21%
69.79%
69.92%
55.42%
64.33%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
138
2,654
1,750
1,042
570
2,222
481
2,311
1,854
938
2,792
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
111
1,545
1,049
607
298
1,358
235
1,421
1,202
454
1,656
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
121
2,497
1,727
891
566
2,052
467
2,151
1,738
880
2,618
Percent
77.53%
65.71%
71.37%
59.04%
49.65%
72.40%
49.28%
71.31%
71.50%
57.76%
66.21%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F DS 8 | Financial Modeling
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
96
1,352
942
506
236
1,212
188
1,260
1,053
395
1,448
Percent
53.93%
33.47%
38.42%
28.67%
20.56%
39.49%
19.26%
38.88%
40.61%
24.32%
34.34%
2011
Percent
56.74%
35.53%
40.33%
30.99%
22.13%
41.77%
21.41%
40.94%
42.69%
26.42%
36.42%
2012
Percent
62.36%
38.25%
42.78%
34.39%
25.96%
44.25%
24.08%
43.84%
46.36%
27.96%
39.27%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble F DS9 | Medical Necessity Checking Content
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
95
2,161
1,496
760
465
1,791
374
1,882
1,549
707
2,256
Percent
53.37%
53.50%
61.01%
43.06%
40.51%
58.36%
38.32%
58.07%
59.74%
43.53%
53.50%
2011
The following reflects the highlights of the financial decision
support market by bed-size segment:
• 0–100 beds: data warehousing/mining-financial and business
intelligence-financial demonstrated the greatest increase, at more
than four percentage points each (see Table FDS10). All other
financial decision support applications indicated growth ranging
from approximately two to three percentage points.
• 101–200 beds: medical necessity checking content and business
intelligence-financial indicated growth of more than four
percentage points each. Data warehousing/mining-financial
also showed growth of nearly four percentage points. Growth
for budgeting systems was negligible during this past year
(see Table FDS11).
• 201–300 beds: business intelligence-financial and financial
modeling indicated the largest growth (at more than four
percentage points). Use of cost accounting solutions decreased
slightly (see Table FDS12).
• 301–400 beds: medical necessity checking content had the
highest growth for this segment at more than four percentage
Percent
64.61%
58.16%
66.35%
47.42%
45.38%
63.31%
43.03%
63.07%
64.37%
48.95%
58.43%
2012
Percent
67.98%
61.82%
70.43%
50.48%
49.30%
66.86%
47.85%
66.37%
67.03%
54.19%
62.08%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
points, followed by business intelligence-financial at just less
than four percent. Budgeting and cost accounting each indicated
a slight decrease from 2011 to 2012 (see Table FDS13).
• 401–500 beds: business intelligence-financial had the highest
growth for this segment, at more than five percent and data
warehousing/mining-financial showed growth of nearly five
percentage points. Cost accounting and budgeting reported no
growth from 2011 to 2012 (see Table FDS14).
• 501–600 beds: the adoption of medical necessity checking
content increased by more than seven percentage points in this
bed segment. Almost all of the other financial decision support
applications demonstrated slight growth in this bed segment,
except budgeting and cost accounting, which are approaching
market saturation (see Table FDS15).
• Over 600 beds: with more than a five percentage point increase
from 2011 to 2012, financial modeling demonstrated the largest
increase within this bed segment. Business intelligence-financial,
data warehousing/mining-financial and medical necessity
checking content also experienced an increase (see Table FDS16).
Ta ble F DS10
Ta ble F DS15
0–100 Beds
2010
Budgeting
1,563
622
Cost Accounting
1,198
Data Warehousing/Mining–
Financial
700
Executive Information Systems 1,183
Financial Modeling
532
Medical Necessity Checking
Content
983
2011
2012
72.19% 1,597 73.76% 1,647 76.07%
28.73%
694 32.06%
789 36.44%
55.33% 1,228 56.72% 1,265 58.43%
32.33%
54.64%
24.57%
755
1,228
577
34.87%
56.72%
26.65%
859
1,280
639
39.68%
59.12%
29.52%
45.40%
1,072
49.52%
1,143
52.79%
Ta ble F DS11
2010
723
371
615
2011
% of 802 Hospitals
90.15%
724 90.27%
46.26%
408 50.87%
76.68%
615 76.68%
2012
725
443
627
90.40%
55.24%
78.18%
397
543
306
49.50%
67.71%
38.15%
437
567
323
54.49%
70.70%
40.27%
467
577
342
58.23%
71.95%
42.64%
505
62.97%
540
67.33%
576
71.82%
Ta ble F DS12
201–300 Beds
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
2010
439
234
409
2011
% of 483 Hospitals
90.89%
441 91.30%
48.45%
255 52.80%
84.68%
408 84.47%
2012
441
278
407
91.30%
57.56%
84.27%
245
338
210
50.72%
69.98%
43.48%
280
344
217
57.97%
71.22%
44.93%
297
353
237
61.49%
73.08%
49.07%
287
59.42%
328
67.91%
342
70.81%
Ta ble F DS13
301–400 Beds
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
2010
292
164
273
2011
% of 312 Hospitals
93.59%
292 93.59%
52.56%
183 58.65%
87.50%
273 87.50%
2012
291
195
272
93.27%
62.50%
87.18%
186
221
153
59.62%
70.83%
49.04%
201
230
160
64.42%
73.72%
51.28%
210
235
166
67.31%
75.32%
53.21%
196
62.82%
211
67.63%
224
71.79%
Ta ble F DS14
401–500 Beds
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
2010
112
70
109
2011
% of 116 Hospitals
96.55%
111 95.69%
60.34%
75 64.66%
93.97%
109 93.97%
2012
111
77
109
95.69%
66.38%
93.97%
63
83
66
54.31%
71.55%
56.90%
67
86
71
57.76%
74.14%
61.21%
69
87
75
59.48%
75.00%
64.66%
72
62.07%
75
64.66%
84
72.41%
Ta ble F DS16
101–200 Beds
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
501–600 Beds
2010
181
99
168
2011
% of 188 Hospitals
96.28%
180 95.74%
52.66%
110 58.51%
89.36%
170 90.43%
2012
180
120
170
95.74%
63.83%
90.43%
121
135
101
64.36%
71.81%
53.72%
124
139
107
65.96%
73.94%
56.91%
133
141
108
70.74%
75.00%
57.45%
122
64.89%
134
71.28%
138
73.40%
Over 600 beds
Budgeting
Cost Accounting
Financial
Financial Modeling
Content
2010
142
86
142
2011
% of 151 Hospitals
94.04%
142 94.04%
56.95%
96 63.58%
94.04%
141 93.38%
2012
142
103
140
94.04%
68.21%
68.87%
107
120
80
70.86%
79.47%
52.98%
114
119
81
75.50%
78.81%
53.64%
117
119
89
77.48%
78.81%
58.94%
91
60.26%
104
68.87%
111
73.51%
At least three-quarters of the contracts signed for all of the
applications in the financial decision support application suite were
signed in 2000 or later. The most current contract market surrounds
medical necessity checking content where more than one-third of
all the contracts were signed between 2010 and 2012 (see Tables
FDS17–FDS19).
Ta ble F DS17
Budgeting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Cost Accounting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
60
179
393
757
512
289
2,190
2,190
2,190
2,190
2,190
2,190
2,190
2,190
2.74%
8.18%
17.96%
34.60%
23.40%
13.21%
100.00%
4
28
164
238
245
147
826
826
826
826
826
826
826
826
0.49%
3.46%
20.27%
29.42%
30.28%
18.17%
100.00%
75
200
399
487
416
226
1,803
1,803
1,803
1,803
1,803
1,803
1,803
1,803
4.16%
11.10%
22.14%
27.03%
23.09%
12.54%
100.00%
17
Ta ble F DS18
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Financial Modeling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
6
49
109
284
274
175
897
897
897
897
897
897
897
897
0.68%
5.57%
12.40%
32.31%
31.17%
19.91%
100.00%
42
128
413
394
381
237
1,595
1,595
1,595
1,595
1,595
1,595
1,595
1,595
2.64%
8.04%
25.94%
24.75%
23.93%
14.89%
100.00%
6
102
103
250
137
105
703
703
703
703
703
703
703
703
0.85%
14.53%
14.67%
35.61%
19.52%
14.96%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
3
10
123
75
230
232
673
673
673
673
673
673
673
673
0.45%
1.49%
18.36%
11.19%
34.33%
34.63%
100.00%
Ta ble F DS19
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
The financial decision support IT application market has both
growth areas and sluggish areas. This market has (and will continue
to have) a mixed future driven through 2015 by the following forces:
• The drive to provide excellent efficiency analytics counteracts
with declining Medicare and Medicaid reimbursement.
• Adoption of ICD-10 coding, and the upgrades of all applications
impacted by this coding will facilitate significantly enhanced
cost and quality analyses, though most of this may have been
accomplished by year end 2012.
• Continued focus on quality outcomes measures as driven
both by the ARRA regulations and the general trend towards
transparency and availability of quality and performance metrics
to the public at large.
• Higher rates of adoption of EHR applications that provide a rich
source of line item consumption data for efficiency analytics.
• Increasing pay for performance reimbursement models from
private insurers and the government.
• Continued movement of patient treatment services from the acute
care environment to ambulatory settings.
• Increased market competition in large metropolitan areas.
• Hospital acquisition/divestiture and merger activities.
• The need to carefully evaluate new or enhanced hospital services
to ensure viability, and profitability, or to determine closure or
divestiture strategies.
• Increased awareness of, and movement towards, new models of
service delivery, such as patient-centered medical homes and
ACOs, or other models that may require increased assumption
of risk.
• More mature users of performance management and decision
support tools replacing their earliest efforts—principally data
marts—with more integrated, more functional, enterprise-wide
data warehouses.
▶▶ Human Resource Environment
Human Resources (HR) IT applications support key staff
management operations and are therefore critical to a healthcare
provider’s success. The value of these applications have elevated
over the years as healthcare organizations have relied on these
systems to effectively manage staffing shortages and recruitment
processes. Hospitals, for example, can alleviate some staff shortages
by using these systems to connect to Web sources of resumes and
screen the resumes for key words to find candidates.
Ta ble HR1 | Human Resources
N=4,217
2010
2011
Benefits Administration
88.64%
89.59%
Payroll
98.72%
98.98%
Personnel Management
88.66%
89.90%
Time and Attendance
92.93%
94.07%
2012
90.51%
99.19%
90.70%
94.85%
All of the HR IT applications tracked by HIMSS Analytics grew
(albeit ever so slightly) between 2010 and 2012. This growth occurred
despite the fact that all these applications are at very high levels of
market penetration (see Table HR1). The greatest increase in HR IT
application adoption between 2011 and 2012 involved the benefits
administration system (.92 percentage point increase), whereas the
lowest adoption rate involved the payroll solution (.21 percentage
point increase).
The HR IT buyer market is largely composed of replacement
purchasers. The exception being time and attendance applications,
for which two-thirds of the planned purchases are from hospitals
making a purchase for the first time (see Table HR2). The high level
of replacement purchases is not unexpected given the high market
penetration of these applications.
Ta ble HR 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
21
91.30%
Payroll
29
96.67%
25
86.21%
Time and Attendance
4
33.33%
for the First Time
2
1
4
8
for the First Time
8.70%
3.33%
13.79%
66.67%
N = Total Number of
Hospitals Planning
23
30
29
12
▶▶ Human Resource Environment con tinue d
The following reflects some key highlights when comparing the
2012 HR IT market profile to the 2011 market profile by various
hospital segments:
• Benefits administration: critical access hospitals demonstrated the
highest level of first-time buyer adoption (two percentage point
increase), followed by rural and non-general medical/surgical
hospitals. By organizational size, single hospitals reflected a
greater first-time buyer adoption rate (just over one percentage
point increase) than hospitals belonging to multi-hospital systems
(see Table HR3).
• Payroll: the growth for most hospital types was less than one
percentage point. The academic medical center segment is the
only segment to have achieved 100 percent market penetration.
The academic medical segment along with general medical/
surgical facilities are the only two segments to reflect no
measurable growth in the past year (see Table HR4).
• Personnel management: critical access hospitals demonstrated
the largest growth, registering an increase greater than two
percentage points. The rural hospital and non-medical surgical
hospital segments also grew, although their growth was slightly
less than the critical access hospital market. Other hospital
segments indicated a year-over-year growth of less than one
percent, with the exception of the academic medical center which
has 100 percent market penetration and remained unchanged
(see Table HR5).
• Time and attendance: rural hospitals and critical access hospitals
had the largest growth (approximately two percentage points)
between 2011 and 2012. Growth in the single hospital and nonmedical surgical segments exceeded one percent, while most of
the other segments grew at less than one percent. The academic
medical center segment is the only segment to remain unchanged
from last year (see Table HR6).
Ta ble HR3 | Benefits Administration
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non Critical Access
Rural
Urban
All
Segment
Count
176
3,562
2,326
1,412
825
2,913
700
3,038
2,480
1,258
3,738
Percent
98.88%
88.19%
94.86%
80.00%
71.86%
94.92%
71.72%
93.74%
95.64%
77.46%
88.64%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,603
2,343
1,435
846
2,932
727
3,051
2,489
1,289
3,778
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,996
2,444
1,730
1,124
3,050
957
3,217
2,574
1,600
4,174
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,613
2,367
1,424
831
2,960
719
3,072
2,497
1,294
3,791
Percent
98.31%
89.21%
95.55%
81.30%
73.69%
95.54%
74.49%
94.14%
95.99%
79.37%
89.59%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,641
2,354
1,463
869
2,948
745
3,072
2,509
1,308
3,817
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
4,005
2,444
1,739
1,132
3,051
961
3,222
2,580
1,603
4,183
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,647
2,374
1,451
856
2,969
736
3,089
2,517
1,308
3,825
Percent
98.88%
90.15%
96.00%
82.89%
75.70%
96.06%
76.33%
94.79%
96.76%
80.54%
90.51%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HR4 | Payroll
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
3,985
2,438
1,725
1,123
3,040
954
3,209
2,567
1,596
4,163
Percent
100.00%
98.66%
99.43%
97.73%
97.82%
99.06%
97.75%
99.01%
99.00%
98.28%
98.72%
2011
Percent
100.00%
98.94%
99.67%
98.02%
97.91%
99.38%
98.05%
99.26%
99.27%
98.52%
98.98%
2012
Percent
100.00%
99.16%
99.67%
98.53%
98.61%
99.41%
98.46%
99.41%
99.50%
98.71%
99.19%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HR5 | Personnel Management
2010
Type
Academic/Teaching
Non Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
3,561
2,343
1,396
804
2,935
686
3,053
2,488
1,251
3,739
Percent
100.00%
88.17%
95.55%
79.09%
70.03%
95.63%
70.29%
94.20%
95.95%
77.03%
88.66%
2011
Percent
100.00%
89.45%
96.53%
80.68%
72.39%
96.45%
73.67%
94.79%
96.30%
79.68%
89.90%
2012
Percent
100.00%
90.29%
96.82%
82.21%
74.56%
96.74%
75.41%
95.31%
97.07%
80.54%
90.70%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
19
Ta ble HR6 | Time and Attendance
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
175
3,744
2,379
1,540
947
2,972
813
3,106
2,513
1,406
3,919
Percent
98.31%
92.70%
97.02%
87.25%
82.49%
96.84%
83.30%
95.83%
96.91%
86.58%
92.93%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
When examining the HR IT market by bed size segments, the
following observations are notable changes from 2011 to 2012:
• 0–100 beds: benefits administration, personnel management and
time and attendance applications increased by one and a half
percentage points, while use of payroll systems increased by
less than half a percent (see Table HR7).
• 101–200 beds: benefits administration indicated the largest
growth in this segment (0.38 percentage points) while the other
HR applications remained unchanged (see Table HR8).
• 201–300 beds: personnel management is the only HR application
that indicated growth in this segment (.20 percentage points), while
the other HR applications remained unchanged (see Table HR9).
• 301–400 beds: payroll and personnel management reached
100 percent market saturation in 2011 and remained unchanged
in 2012. Benefits administration demonstrated a slight increase;
while time and attendance remained unchanged from 2011 levels
(see Table HR10).
• 401–500 beds: payroll and personnel management reached
100 percent market saturation in 2011 and remained unchanged
in 2012. Time and attendance experienced a decrease from last
year of 0.54 percentage points (see Table HR11).
• 501–600 beds: time and attendance indicated a growth of almost
two percent. Payroll and personnel management reached market
saturation in 2010 and market penetration remains unchanged.
There was also no market growth in the use of benefits
administration solutions (see Table HR12).
• Over 600 beds: benefits administration demonstrated an increase
of almost one percent while the other applications remained
unchanged. Use of payroll and personnel management systems
reached market saturation in 2010 (see Table HR13).
Approximately ten percent of contracts for benefits administration,
payroll and personnel management were signed within the last two
years (between 2010 and 2012). The activity in these areas is not
too surprising, since these are often older, legacy solutions that
healthcare organizations are replacing (Table HR14 and HR15).
This trend can be expected to continue, as at least 40 percent of
contracts for all applications in this suite were signed prior to 2000.
That said, there is a good possibility that future purchases of HR
IT applications may be deferred for many hospitals because of
various federal IT related initiatives, such as ICD-10, and Medicare
and Medicaid-funded EHR implementations. Hospitals leaders may
elect to allocate their resources in satisfying federal initiatives
instead of replacing older HR applications, unless their HR IT
applications do not meet minimal requirements or been sunsetted
by the vendor.
Segment
Count
175
3,792
2,400
1,567
971
2,996
833
3,134
2,526
1,441
3,967
Percent
98.31%
93.88%
97.88%
88.78%
84.58%
97.62%
85.35%
96.70%
97.42%
88.73%
94.07%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,825
2,407
1,593
996
3,004
851
3,149
2,539
1,461
4,000
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
98.31%
94.70%
98.16%
90.25%
86.76%
97.88%
87.19%
97.16%
97.92%
89.96%
94.85%
Ta ble HR7
0–100 Beds
Payroll
Time and Attendance
2010
1,738
2,117
1,717
1,916
80.28%
97.78%
79.31%
88.50%
2011
2012
1,769 81.71% 1,803 83.28%
2,125 98.15% 2,134 98.57%
1,762 81.39% 1,795 82.91%
1,953 90.21% 1,985 91.69%
Ta ble HR8
101–200 Beds
Payroll
Time and Attendance
2010
775
779
782
779
96.63%
97.13%
97.51%
97.13%
2011
% of 802 Hospitals
779 97.13%
800 99.75%
785 97.88%
785 97.88%
2012
782
800
785
785
97.51%
99.75%
97.88%
97.88%
Ta ble HR9
201–300 Beds
Payroll
Time and Attendance
2010
472
482
476
472
97.72%
99.79%
98.55%
97.72%
2011
% of 483 Hospitals
475 98.34%
482 99.79%
477 98.76%
474 98.14%
2012
475
482
478
474
98.34%
99.79%
98.96%
98.14%
Ta ble HR10
301–400 Beds
Payroll
Time and Attendance
2010
307
311
310
303
98.40%
99.68%
99.36%
97.12%
2011
% of 312 Hospitals
308 98.72%
312 100.00%
312 100.00%
306 98.08%
2012
309 99.04%
312 100.00%
312 100.00%
306 98.08%
Ta ble HR11
401–500 Beds
Payroll
Time and Attendance
2010
185
187
187
186
98.40%
99.47%
99.47%
98.94%
2011
% of 188 Hospitals
186 98.94%
188 100.00%
188 100.00%
186 98.94%
2012
186 98.94%
188 100.00%
188 100.00%
185 98.40%
Ta ble HR12
501–600 Beds
Payroll
Time and Attendance
2010
114 98.28%
116 100.00%
116 100.00%
114 98.28%
2011
% of 116 Hospitals
114 98.28%
116 100.00%
116 100.00%
113 97.41%
2012
114 98.28%
116 100.00%
116 100.00%
115 99.14%
Ta ble HR13
Over 600 beds
Payroll
Time and Attendance
2010
147 97.35%
151 100.00%
151 100.00%
149 98.68%
2011
% of 151 Hospitals
147 97.35%
151 100.00%
151 100.00%
150 99.34%
2012
148 98.01%
151 100.00%
151 100.00%
150 99.34%
Ta ble HR14
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Payroll
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
100
197
747
725
476
277
2,522
2,522
2,522
2,522
2,522
2,522
2,522
2,522
3.97%
7.81%
29.62%
28.75%
18.87%
10.98%
100.00%
98
207
851
779
529
315
2,779
2,779
2,779
2,779
2,779
2,779
2,779
2,779
3.53%
7.45%
30.62%
28.03%
19.04%
11.34%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
106
197
776
727
469
270
2,545
2,545
2,545
2,545
2,545
2,545
2,545
2,545
4.17%
7.74%
30.49%
28.57%
18.43%
10.61%
100.00%
39
152
776
749
434
169
2,319
2,319
2,319
2,319
2,319
2,319
2,319
2,319
1.68%
6.55%
33.46%
32.30%
18.71%
7.29%
100.00%
Ta ble HR15
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Time and Attendance
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
It is our opinion that the HR IT application market has been and
will continue to be impacted through 2015 by the following forces:
• A concern over future reimbursement levels and higher IT
application priorities, such as EMR and revenue cycle management
(RCM) applications, should drive most hospitals to extend the
useful life of these applications for as long as possible.
• Continued shortages of clinicians, especially pharmacists, nurses
and IT staff are driving an increased interest in manpower
planning, skills training and enhanced recruiting tools.
• The need to track security training and policies for all hospital
employees.
• Outsourcing services for the HR application suite in order to
reduce capital requirements.
• The increased centralization of HR operations in IDNs where
employees are internally mobile and where internal consolidation
is occurring when acquired hospitals has disparate HR systems.
• Acquisitions and mergers of healthcare IT vendors.
• Service as a Software (SaaS)/Application solutions provider
(ASP) products that will appeal to smaller hospitals don’t have
the breadth and depth of IT staff to support a large portfolio of
IT applications.
• Potential government regulations (e.g., nurse staffing ratios,
healthcare savings accounts, public insurance options).
• Innovative benefits packages crafted to attract and retain
skilled clinicians.
• The necessity to track clinician credentials and continuing
education for all hospital employees.
• The need to drive efficiencies in HR departments through
the expanded use of e-HR functions such as e-recruiting,
HR portals, etc.
▶▶ Revenue Cycle Management Environment
The business processes supported by the applications in the
Revenue Cycle Management (RCM) category are critical to a
hospital’s viability. There are eight different applications tracked
by HIMSS Analytics in this report: ADT/registration, bed
management, contract management, credit/collections, electronic
data interchange (EDI), enterprise master person index (EMPI),
patient billing and patient scheduling.
Of the applications monitored, four applications have reached or
are approaching market saturation. These applications are ADT/
registration, patient billing, patient scheduling, and credit/collections
(see Table RCM1). Bed management indicated the largest year-overyear growth from 2011 to 2012, registering an increase of approximately
four percentage points. Growth for the remaining applications was
three percentage points or less. ADT/registration is the only
application to remain unchanged from last year.
The majority of purchasing plans for all of the RCM applications in
2012 were replacement purchases (see Table RCM2). This was not
just the case for applications that have achieved market saturation,
but for all applications. Due to impending federal regulation
implementation dates that will require significant changes for the
RCM environment with the ICD-10 coding adoption in 2014, the
impact of healthcare reform legislative provisions for bundled
payments and ACOs, it is expected that replacement purchasing will
continue to grow significantly for RCM applications through 2015.
Ta ble RCM1 | Revenue Cycle Management
N=4,217
2010
2011
ADT/Registration
99.55%
99.67%
Bed Management
33.96%
38.42%
Contract Management
66.11%
67.56%
Credit/Collections
90.89%
91.68%
Electronic Data Interchange (EDI)–
Clearing House Vendor
80.39%
84.82%
Enterprise Master Patient Index (EMPI)
48.66%
52.10%
Patient Billing
99.29%
99.81%
Patient Scheduling
95.94%
96.82%
2012
99.67%
42.47%
70.05%
93.03%
87.55%
54.97%
99.86%
97.49%
21
▶▶ Revenue Cycle Management Environment con tinue d
Ta ble RCM2 | 2012
# of Hospitals
with Installed
63
34
30
44
% of Hospitals
with Installed
100.00%
91.89%
83.33%
100.00%
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Electronic Data Interchange (EDI)–
Clearing House Vendor
15
93.75%
33
82.50%
Patient Billing
66
100.00%
Patient Scheduling
64
95.52%
An evaluation of the RCM application market by hospital market
segment indicates the following highlights:
• ADT/Registration: virtually all hospitals types have reached market
saturation with adoption rates exceeding 99 percent (see Table RCM3).
• Bed management: the academic medical center segment reported
the highest penetration rate at more than 78 percent in 2012.
Adoption in this market grew slightly less than three percentage
points in the past year. In general, there is a consistent level of
adoption growth of approximately four percentage points across
all other market segments (see Table RCM4).
• Contract management: the rural hospital, critical access hospital
and multi-hospital segments reported a year-over-year growth that
exceeded three percentage points (see Table RCM5).
• Credit/Collections: the critical access hospital, rural hospital and
other non-general medical/surgical hospital segments reported the
highest growth (approximately two and one half percentage
points). The academic medical center segment is approaching
market saturation and demonstrated no growth in the past year.
Growth in all other segments was less than two percentage points
(see Table RCM6).
for the First Time
0 3
6
for the First Time
0.00%
8.11%
16.67%
0.00%
N = Total Number of
Hospitals Planning
63
37
36
44
1
7
0
3
6.25%
17.50%
0.00%
4.48%
16
40
66
67
• EDI: all of the segments indicated growth from 2011 to 2012
ranging from two to three percent, with rural hospitals indicating
the largest growth (see Table RCM7).
• EMPI: the rural hospital and general medical/surgical hospital
segments demonstrated the highest growth from 2011 to 2012 at
more than three percentage points. The other segments indicated
smaller growth rates, with the academic medical center segment
indicating the smallest growth at less than one percentage point
(see Table RCM8).
• Patient billing: with 99 percent of U.S. hospitals indicating they
have patient billing, there is little to no growth in this market
segment. Those segments that did indicate some growth had
grown one-tenth of one percentage point or less (see Table RCM9).
• Patient scheduling: this is a highly saturated market. The rural
hospital, critical access hospital, single hospital and other nongeneral medical/surgical hospital segments reported growth
exceeding one percentage point from 2011 to 2012. The remaining
segments reported growth at less than one percentage point. The
academic medical center segment, which is fully saturated, is the
only segment to report no growth from last year (see Table RCM10).
Ta ble RCM3 | ADT/Registration
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
4,020
2,447
1,751
1,138
3,060
968
3,230
2,583
1,615
4,198
Percent
100.00%
99.53%
99.80%
99.21%
99.13%
99.71%
99.18%
99.66%
99.61%
99.45%
99.55%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
4,025
2,449
1,754
1,140
3,063
971
3,232
2,585
1,618
4,203
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
135
1,485
1,146
474
229
1,391
169
1,451
1,115
505
1,620
Percent
100.00%
99.65%
99.88%
99.38%
99.30%
99.80%
99.49%
99.72%
99.69%
99.63%
99.67%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
4,025
2,449
1,754
1,140
3,063
971
3,232
2,585
1,618
4,203
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
140
1,651
1,255
536
277
1,514
207
1,584
1,225
566
1,791
Percent
100.00%
99.65%
99.88%
99.38%
99.30%
99.80%
99.49%
99.72%
99.69%
99.63%
99.67%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RCM4 | Bed Management
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
120
1,312
1,044
388
181
1,251
132
1,300
985
447
1,432
Percent
67.42%
32.48%
42.58%
21.98%
15.77%
40.76%
13.52%
40.11%
37.99%
27.52%
33.96%
2011
Percent
75.84%
36.77%
46.74%
26.86%
19.95%
45.32%
17.32%
44.77%
43.00%
31.10%
38.42%
2012
Percent
78.65%
40.88%
51.18%
30.37%
24.13%
49.33%
21.21%
48.87%
47.24%
34.85%
42.47%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RCM5 | Contract Management
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
147
2,641
1,825
963
478
2,310
410
2,378
1,967
821
2,788
Percent
82.58%
65.39%
74.43%
54.56%
41.64%
75.27%
42.01%
73.37%
75.86%
50.55%
66.11%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
148
2,701
1,863
986
489
2,360
423
2,426
2,008
841
2,849
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,694
2,350
1,516
959
2,907
822
3,044
2,453
1,413
3,866
Percent
83.15%
66.87%
75.98%
55.86%
42.60%
76.90%
43.34%
74.85%
77.44%
51.79%
67.56%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
150
2,804
1,919
1,035
528
2,426
458
2,496
2,086
868
2,954
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,751
2,362
1,561
988
2,935
846
3,077
2,485
1,438
3,923
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
166
3,526
2,176
1,516
949
2,743
804
2,888
2,300
1,392
3,692
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
134
2,184
1,517
801
518
1,800
419
1,899
1,556
762
2,318
Percent
84.27%
69.42%
78.26%
58.64%
45.99%
79.05%
46.93%
77.01%
80.45%
53.45%
70.05%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RCM6 | Credit/Collections
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
171
3,662
2,332
1,501
939
2,894
806
3,027
2,435
1,398
3,833
Percent
96.07%
90.67%
95.11%
85.04%
81.79%
94.30%
82.58%
93.40%
93.91%
86.08%
90.89%
2011
Percent
96.63%
91.46%
95.84%
85.89%
83.54%
94.72%
84.22%
93.92%
94.60%
87.01%
91.68%
2012
Percent
96.63%
92.87%
96.33%
88.44%
86.06%
95.63%
86.68%
94.94%
95.83%
88.55%
93.03%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RCM7 | Electronic Data Interchange (EDI)–Clearing House Vendor
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
155
3,235
2,010
1,380
864
2,526
733
2,657
2,100
1,290
3,390
Percent
87.08%
80.09%
81.97%
78.19%
75.26%
82.31%
75.10%
81.98%
80.99%
79.43%
80.39%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
161
3,416
2,119
1,458
912
2,665
771
2,806
2,228
1,349
3,577
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
133
2,064
1,436
761
486
1,711
384
1,813
1,483
714
2,197
Percent
90.45%
84.58%
86.42%
82.61%
79.44%
86.84%
79.00%
86.58%
85.92%
83.07%
84.82%
2012
Percent
93.26%
87.30%
88.74%
85.89%
82.67%
89.38%
82.38%
89.11%
88.70%
85.71%
87.55%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RCM8 | Enterprise Master Person Index (EMPI)
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
125
1,927
1,341
711
448
1,604
352
1,700
1,387
665
2,052
Percent
70.22%
47.71%
54.69%
40.28%
39.02%
52.26%
36.07%
52.45%
53.49%
40.95%
48.66%
2011
Percent
74.72%
51.10%
58.56%
43.12%
42.33%
55.75%
39.34%
55.94%
57.19%
43.97%
52.10%
2012
Percent
75.28%
54.07%
61.87%
45.38%
45.12%
58.65%
42.93%
58.59%
60.01%
46.92%
54.97%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
23
Ta ble RCM9 | Patient Billing
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
4,009
2,450
1,737
1,144
3,043
974
3,213
2,566
1,621
4,187
Percent
100.00%
99.26%
99.92%
98.41%
99.65%
99.15%
99.80%
99.14%
98.96%
99.82%
99.29%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
4,031
2,451
1,758
1,144
3,065
975
3,234
2,586
1,623
4,209
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,905
2,431
1,652
1,044
3,039
893
3,190
2,551
1,532
4,083
Percent
100.00%
99.80%
99.96%
99.60%
99.65%
99.87%
99.90%
99.78%
99.73%
99.94%
99.81%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
4,033
2,452
1,759
1,145
3,066
976
3,235
2,587
1,624
4,211
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,933
2,439
1,672
1,062
3,049
912
3,199
2,555
1,556
4,111
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
100.00%
99.85%
100.00%
99.66%
99.74%
99.90%
100.00%
99.81%
99.77%
100.00%
99.86%
Ta ble RCM10 | Patient Scheduling
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
178
3,868
2,418
1,628
1,021
3,025
868
3,178
2,533
1,513
4,046
Percent
100.00%
95.77%
98.61%
92.24%
88.94%
98.57%
88.93%
98.06%
97.69%
93.17%
95.94%
2011
The evaluation by bed size reported that ADT/registration, patient
billing, and patient scheduling are at, or near, saturation across all
bed segments (see Tables RCM11–RCM17). ADT/registration
indicated no growth across all bed segments. Some other key
findings within each bed segment are as follows:
• 0–100 beds: bed management, contract management and EDI
indicated the largest growth, surpassing three percentage points
from 2011 to 2012 (see Table RCM11).
• 101–200 beds: bed management reported the largest increase over
the past year at slightly less than six percentage points. Contract
management, EDI and EMPI showed growth of between two and
four percentage points, while the remaining solutions showed
growth of less than one percentage point (see Table RCM12).
• 201–300 beds: the adoption of bed management grew by more
than four percentage points in this segment. Growth of the other
applications ranged from less than one percentage point for credit/
collections and patient scheduling to nearly three percentage
points for EMPI. ADT/registration has reached market saturation
and did not see any additional growth (see Table RCM13).
• 301–400 beds: bed management reported a growth of more than
three percentage points, while contract management and EMPI
grew at approximately two percentage points. ADT/registration,
patient billing and patient scheduling, which are all at or near
market saturation did not grow in the past year (see Table RCM14).
• 401–500 beds: EMPI reported the highest increase at more than
three percentage points, while bed management and EDI grew
approximately two percentage points. Contract management and
credit/collections are the only applications which decreased
slightly in penetration from 2011 to 2012 (see Table RCM15).
• 501–600 beds: bed management demonstrated the largest increase
over the past year at more than six percentage points, followed by
contract management at four percentage points. Applications at or
Percent
100.00%
96.68%
99.14%
93.60%
90.94%
99.02%
91.50%
98.43%
98.38%
94.33%
96.82%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
100.00%
97.38%
99.47%
94.73%
92.51%
99.35%
93.44%
98.70%
98.53%
95.81%
97.49%
near market saturation such as ADT/registration, credit/
collections, patient billing and patient scheduling demonstrated
no growth (see Table RCM16).
• Over 600 beds: bed management and EDI are the only RCM
applications to report a growth exceeding three percentage points
from 2011 to 2012. ADT/registration, patient billing and patient
scheduling, which have all reached market saturation, reported no
growth. The remaining applications demonstrated growth of less
than three percentage points (see Table RCM17).
Ta ble rcm11
0–100 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Electronic Data Interchange
(EDI)–Clearing House Vendor
Enterprise Master Patient
Index (EMPI)
Patient Billing
Patient Scheduling
2010
2011
2012
2,152 99.40% 2,152 99.40%
510 23.56%
586 27.07%
1,193 55.10% 1,258 58.11%
1,889 87.25% 1,937 89.47%
2,147
418
1,152
1,865
99.17%
19.31%
53.21%
86.14%
1,681
77.64%
1,770
81.76%
1,842
85.08%
830
2,136
2,008
38.34%
98.66%
92.75%
900
2,158
2,043
41.57%
99.68%
94.36%
956
2,159
2,066
44.16%
99.72%
95.43%
Ta ble rcm12
101–200 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
2010
2011
% of 802 Hospitals
801 99.88%
323 40.27%
622 77.56%
776 96.76%
801
294
615
775
99.88%
36.66%
76.68%
96.63%
663
82.67%
699
442
801
793
55.11%
99.88%
98.88%
482 60.10%
802 100.00%
794 99.00%
87.16%
2012
801
368
638
780
99.88%
45.89%
79.55%
97.26%
717
89.40%
514 64.09%
802 100.00%
797 99.38%
Ta ble rcm13
201–300 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
2010
483 100.00%
241 49.90%
383 79.30%
463 95.86%
393
2011
% of 483 Hospitals
483 100.00%
263 54.45%
390 80.75%
465 96.27%
2012
483 100.00%
285 59.01%
397 82.19%
469 97.10%
81.37%
422
87.37%
432
89.44%
281 58.18%
483 100.00%
480 99.38%
297
482
480
61.49%
99.79%
99.38%
311 64.39%
483 100.00%
482 99.79%
Ta ble rcm14
301–400 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
2010
312 100.00%
176 56.41%
254 81.41%
293 93.91%
263
84.29%
2011
% of 312 Hospitals
312 100.00%
196 62.82%
255 81.73%
296 94.87%
281
90.06%
2012
312 100.00%
207 66.35%
264 84.62%
297 95.19%
285
91.35%
193 61.86%
312 100.00%
311 99.68%
202 64.74%
312 100.00%
311 99.68%
209 66.99%
312 100.00%
311 99.68%
2010
2011
% of 188 Hospitals
188 100.00%
125 66.49%
164 87.23%
183 97.34%
2012
Ta ble rcm15
401–500 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
188 100.00%
118 62.77%
157 83.51%
181 96.28%
157
83.51%
162
86.17%
188 100.00%
129 68.62%
163 86.70%
182 96.81%
166
88.30%
119 63.30%
188 100.00%
188 100.00%
121 64.36%
188 100.00%
188 100.00%
127 67.55%
188 100.00%
188 100.00%
2010
2011
% of 116 Hospitals
116 100.00%
77 66.38%
95 81.90%
111 95.69%
2012
Ta ble rcm16
501–600 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
116 100.00%
71 61.21%
100 86.21%
111 95.69%
100
86.21%
69 59.48%
116 100.00%
115 99.14%
104
89.66%
74 63.79%
116 100.00%
116 100.00%
116 100.00%
84 72.41%
100 86.21%
111 95.69%
106
91.38%
77 66.38%
116 100.00%
116 100.00%
Ta ble rcm17
Over 600 beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
Index (EMPI)
Patient Billing
Patient Scheduling
2010
151 100.00%
114 75.50%
126 83.44%
145 96.03%
133
88.08%
118 78.15%
151 100.00%
151 100.00%
2011
% of 151 Hospitals
151 100.00%
126 83.44%
130 86.09%
146 96.69%
139
92.05%
121 80.13%
151 100.00%
151 100.00%
2012
151 100.00%
132 87.42%
134 88.74%
147 97.35%
144
95.36%
124 82.12%
151 100.00%
151 100.00%
In evaluating the RCM contract signed dates, 10 to 20 percent of
the contracts signed were done so between 2010 and 2012. The
exceptions are bed management and credit/collections. More than
30 percent of the contracts for bed management were signed between
2010 and 2012, while only four percent of the total credit/collections
contracts were signed during this time. The majority of credit/
collections contracts were signed from 1990 to 2004.
Activities between 2010 and 2012, particularly for market saturated
applications such as ADT/registration, patient billing and patient
scheduling, are good indications that replacement purchases are
being made. It is likely that these applications will continue to be
replaced over the next three to five years.
Ta ble RCM18
ADT/Registration
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Bed Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Contract Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
120
320
749
774
658
467
3,088
3,088
3,088
3,088
3,088
3,088
3,088
3,088
3.89%
10.38%
24.29%
25.10%
21.34%
15.14%
100.00%
9
16
40
147
253
199
664
664
664
664
664
664
664
664
1.36%
2.41%
6.03%
22.17%
38.16%
30.02%
100.00%
54
101
406
521
416
229
1,727
1,727
1,727
1,727
1,727
1,727
1,727
1,727
3.15%
5.88%
23.65%
30.34%
24.23%
13.34%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
2,781
2,781
2,781
2,781
2,781
2,781
2,781
11.88%
25.78%
23.62%
20.45%
14.40%
4.00%
100.00%
1,316
1,316
1,316
1,316
1,316
1,316
1,316
1.15%
5.44%
20.14%
25.88%
30.47%
17.69%
100.00%
1,338
1,338
1,338
1,338
1,338
1,338
1,338
0.97%
6.35%
12.18%
33.63%
26.91%
19.96%
100.00%
Ta ble RCM19
Credit/Collections
Prior to 1990
330
1990 to 1994
716
1995 to 1999
656
2000 to 2004
568
2005 to 2009
400
2010 to 2012
111
Total
2,781
Electronic Data Interchange (EDI)–Clearing House Vendor
Prior to 1990
15
1990 to 1994
71
1995 to 1999
263
2000 to 2004
338
2005 to 2009
398
2010 to 2012
231
Total
1,316
Prior to 1990
13
1990 to 1994
85
1995 to 1999
163
2000 to 2004
450
2005 to 2009
360
2010 to 2012
267
Total
1,338
25
Ta ble RCM20
Patient Billing
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Patient Scheduling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
147
309
772
749
619
452
3,048
3,048
3,048
3,048
3,048
3,048
3,048
3,048
4.83%
10.15%
25.37%
24.61%
20.34%
14.85%
100.00%
44
205
532
784
651
461
2,677
2,677
2,677
2,677
2,677
2,677
2,677
2,677
1.65%
7.69%
19.96%
29.42%
24.43%
17.30%
100.00%
The RCM IT application market has been and will continue to be
impacted through 2015 by:
• The conversion to ICD-10 coding currently scheduled for
October 1, 2014.
• The need of many organizations to update or replace their legacy
RCM environments to effectively meet ICD-10 upgrade and
conversion requirements.
• The emergence of outcomes-based reimbursement models, some
of which will be driven by ARRA Meaningful Use requirements,
while others will be in response to pay for performance initiatives
from private insurers.
• Hospitals electing to compete as an ACO in consort with other
entities.
• Hospitals focusing on bundled payments as a measure to integrate
the medical and surgical staff with Medicare and possible private
insurance contracts.
• The focus on consumer/patient satisfaction and patient
engagement (e.g., pricing transparency, consumer-friendly billing
formats, online bill paying, self-scheduling, pre-registration and
other web-based, self-service applications).
• The need to more effectively integrate financial and clinical data
for business analysis and government reporting.
• The need to more effectively integrate financial decision support
into the RCM environment.
▶▶ Next Generation Revenue Cycle Management
Next generation revenue cycle management (next generation RCM)
IT solutions refer to applications designed to improve collection
rates, business office workflows, productivity, patient satisfaction
and patient convenience. The solutions contribute to the overall
efficiency of the RCM process by complementing and enhancing
core legacy RCM applications.
HIMSS Analytics monitors the solutions available in the following
five next generation RCM categories:
1.Consumer focus: provides the ability to extend B2C (Business to
Consumer) web services to patients; and facilitates online preregistration,self-scheduling, and bill payment to enhance patient
service efficiency and convenience.
2.Eligibility verification: supports real-time insurance eligibility
verification transactions to ensure that patients’ insurance covers
services and procedures.
3.Rules capability for billing and payment processing: provides
rules engines that facilitate medical necessity checking during
patient scheduling and registration functions prior to care
delivery; determine self-pay patient liability prior to or at the
point of registration; and compare submitted, allowed and paid
claims against contractual terms to identify and facilitate claims
resubmissions. They also allow business office personnel to edit
bills online prior to submission, if needed, to improve billing
accuracy and compliance with contractual terms and to provide
the necessary updates to all billing and accounts receivable files
related to those edits. next generation RCM tools can also
accommodate the auto-encoding of clinical information from the
EHR system, determine claims attachment requirements, and
automatically create required attachments (when such supporting
data exists in digital form, such as in the EHR) prior to claim
submission to avoid denied or pended claims and improve the
efficiency and accuracy of the billing process.
4.Claims processing: provides the ability to submit claims directly
to payers, eliminating the need to use a third-party clearinghouse
intermediary; accepts direct electronic claims remittance transactions
from payers; and directly posts third-party payments against patientspecific receivables from bundled remittance transactions.
5.Treasury functions: provides electronic funds transfers (EFT)
from third-party payers directly to the provider organization’s
bank accounts to improve cash flow and facilitate financial
reconciliation processes for the organization.
The adoption of next generation RCM solutions continued to
increase this past year with the exception of EMR documentation
for claims, which showed a minor decrease (less than one percent).
Web self-pay demonstrated the highest growth rate among next
Ta ble NGRCM1 | Next Generation Revenue Cycle Management
N=4,217
2010
2011
Biller’s Dash Board
22.69%
25.85%
Claims Attachment Rules
26.01%
28.72%
Claims Remittance Updates AR
15.27%
16.79%
Denial Rules
26.68%
30.31%
Direct Payer Claims
12.14%
12.90%
EFT Transaction
24.24%
26.08%
Eligibility Transaction with Payer
15.51%
16.93%
EMR Documentation for Claims
3.84%
2.96%
Necessity Alert @ Registration
36.25%
38.65%
Necessity Alert @ Scheduling
21.48%
23.14%
Web PreRegister
16.81%
19.26%
Web Schedule
6.76%
6.92%
Web Self-Pay
26.89%
32.51%
2012
28.57%
32.23%
17.95%
34.01%
13.59%
28.05%
17.83%
2.82%
40.03%
24.99%
20.49%
9.13%
38.04%
▶▶ Next Generation Revenue Cycle Management con tinue d
generation RCM applications (more than five percentage points),
followed by denial rules (approximately four percentage points), and
claims attachment rules (3.5 percentage points). The remaining next
generation RCM applications increased between approximately one
and three percentage points (see Table NGRCM1).
The next generation RCM index is developed by HIMSS Analytics
designed to allow hospitals to compare their use of next generation
RCM capabilities against other hospitals in the market. A hospital’s
next generation RCM adoption is influenced by several factors that
include business needs, strategies and competitive environment.
Hospitals must be cognizant of the impact that ICD-10 coding upgrades
and Meaningful Use objectives will have on many of these applications,
and are highly encouraged to be preparing their upgrade strategies now.
An evaluation of this market in 2012 by hospital type shows the
following trends:
Consumer Focus:
• Web pre-registration: the rural hospital segment’s adoption rate
showed the highest increase at more than two percentage points,
followed closely by the critical access segment at just under two
percentage points (see Table NGRCM2).
• Web scheduling: all segments indicated an increase of between
one and a half and four percentage points from 2011 to 2012,
with academic medical centers showing the greatest increase
(see Table NGRCM3). (Note: we are not making a distinction
between whether the consumer can actually write an appointment
to the schedule or simply request a schedule slot which is later
confirmed by the provider).
• Web self-pay: all segments increased adoption of this technology.
The academic medical center, medical/surgical, non-critical
access hospital and multi-hospital system segments had an
increase of more than six percentage points from 2011 to 2012
(see Table NGRCM4).
Eligibility Verification
• Medical necessity alerts at the point of scheduling: growth was
consistent at one to two percentage points across all hospital
segments (see Table NGRCM5).
• Medical necessity alerts at point of registration: the highest
growth in adoption occurred in the single hospital system
segment at approximately three percentage points. All other
segments except multi-hospital system showed growth at more
than one percentage point (see Table NGRCM6).
Rules and Billing Capabilities:
• Claims attachment rules: at approximately six percentage points,
the academic medical center hospital segment had the highest
growth in 2012. Adoption in the remaining hospital segments
increased between three and four percentage points (see Table
NGRCM7).
• Denials rules: the highest growth rate was evidenced in academic
medical centers at approximately six percentage points. From
2011 to 2012, all other hospital segments increased between three
and four percentage points (see Table NGRCM8).
• Biller’s dashboard (a graphical user interface of key performance
indicators for billing processes that also allows for the editing of
claims data): the academic medical center hospital segment had
the highest growth rate at approximately four percentage points,
followed closely by the single hospital system segment at more
than three percentage points. The remaining segments all
increased over two percentage points (see Table NGRCM9).
• EMR documentation for claims: the academic medical center
hospital segment grew by one percentage point, while the
remaining segments either grew by less than one percentage
point or experienced a slight decrease (see Table NGRCM10).
Claims Processing:
• Direct payer claims (no clearinghouse): between 2011 and 2012,
the medical/surgical and non-critical access hospital segments
experienced the highest growth rates of approximately one
percentage point. Academic medical centers had no change in
adoption rates, while critical access hospitals experienced a slight
decrease (see Table NGRCM11).
• Claims remittance with automatic accounts receivable update:
most hospital segments grew by one percentage point while the
rural hospital segment increased by roughly two percentage
points (see Table NGRCM12).
• Eligibility transaction with payer (no clearinghouse): the highest
growth is witnessed in the academic medical center segment at
approximately two percentage points. The remaining segments grew
by approximately one percentage point (see Table NGRCM13).
Treasury Funds
• EFT transactions (direct to organization’s bank): the academic
medical center hospital segment grew approximately three
percentage points between 2011 and 2012. The general medical/
surgical, non-critical access, multi-hospital and urban hospital
segments experienced the next highest increases (see Table
NGRCM14).
Ta ble NGRCM2 | Web Pre-Register
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
31
678
548
161
99
610
79
630
606
103
709
Percent
17.42%
16.79%
22.35%
9.12%
8.62%
19.88%
8.09%
19.44%
23.37%
6.34%
16.81%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
29
783
645
167
104
708
101
711
697
115
812
Percent
16.29%
19.39%
26.31%
9.46%
9.06%
23.07%
10.35%
21.94%
26.88%
7.08%
19.26%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
30
834
671
193
126
738
123
741
721
143
864
Percent
16.85%
20.65%
27.37%
10.93%
10.98%
24.05%
12.60%
22.86%
27.81%
8.81%
20.49%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
27
Ta ble NGRCM3 | Web Schedule
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
35
250
207
78
28
257
20
265
248
37
285
Percent
19.66%
6.19%
8.44%
4.42%
2.44%
8.37%
2.05%
8.18%
9.56%
2.28%
6.76%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
29
263
217
75
30
262
25
267
260
32
292
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
60
1,311
992
379
270
1,101
229
1,142
1,033
338
1,371
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
40
936
712
264
183
793
142
834
654
322
976
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
71
1,559
1,066
564
325
1,305
280
1,350
1,132
498
1,630
Percent
16.29%
6.51%
8.85%
4.25%
2.61%
8.54%
2.56%
8.24%
10.03%
1.97%
6.92%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
36
349
279
106
50
335
41
344
332
53
385
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
73
1,531
1,152
452
315
1,289
273
1,331
1,189
415
1,604
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
42
1,012
765
289
202
852
162
892
698
356
1,054
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
73
1,615
1,103
585
344
1,344
297
1,391
1,142
546
1,688
Percent
20.22%
8.64%
11.38%
6.01%
4.36%
10.92%
4.20%
10.61%
12.80%
3.26%
9.13%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM4 | Web Self-Pay
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
63
1,071
828
306
197
937
169
965
885
249
1,134
Percent
35.39%
26.52%
33.77%
17.34%
17.16%
30.53%
17.32%
29.77%
34.13%
15.33%
26.89%
2011
Percent
33.71%
32.46%
40.46%
21.47%
23.52%
35.87%
23.46%
35.24%
39.84%
20.81%
32.51%
2012
Percent
41.01%
37.91%
46.98%
25.61%
27.44%
42.00%
27.97%
41.07%
45.85%
25.55%
38.04%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM5 | Necessity Alert @ Scheduling
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
34
872
658
248
177
729
135
771
626
280
906
Percent
19.10%
21.59%
26.84%
14.05%
15.42%
23.75%
13.83%
23.79%
24.14%
17.24%
21.48%
2011
Percent
22.47%
23.17%
29.04%
14.96%
15.94%
25.84%
14.55%
25.73%
25.22%
19.83%
23.14%
2012
Percent
23.60%
25.06%
31.20%
16.37%
17.60%
27.76%
16.60%
27.52%
26.92%
21.92%
24.99%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM6 | Necessity Alert @ Registration
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
59
1,470
997
532
310
1,219
264
1,265
1,076
452
1,529
Percent
33.15%
36.40%
40.66%
30.14%
27.00%
39.72%
27.05%
39.03%
41.50%
27.83%
36.25%
2011
Percent
39.89%
38.60%
43.47%
31.95%
28.31%
42.52%
28.69%
41.65%
43.66%
30.67%
38.65%
2012
Percent
41.01%
39.99%
44.98%
33.14%
29.97%
43.79%
30.43%
42.92%
44.04%
33.62%
40.03%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM7 | Claims Attachment Rules
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
52
1,045
702
395
201
896
172
925
677
420
1,097
Percent
29.21%
25.87%
28.63%
22.38%
17.51%
29.20%
17.62%
28.54%
26.11%
25.86%
26.01%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
61
1,150
766
445
235
976
190
1,021
731
480
1,211
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
71
1,207
794
484
252
1,026
209
1,069
736
542
1,278
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
57
1,033
642
448
241
849
214
876
629
461
1,090
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
10
115
85
40
21
104
18
107
70
55
125
Percent
34.27%
28.47%
31.24%
25.21%
20.47%
31.80%
19.47%
31.50%
28.19%
29.56%
28.72%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
71
1,288
860
499
271
1,088
227
1,132
814
545
1,359
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
81
1,353
893
541
290
1,144
249
1,185
827
607
1,434
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
64
1,141
716
489
269
936
243
962
687
518
1,205
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
12
107
80
39
19
100
20
99
68
51
119
Percent
39.89%
31.89%
35.07%
28.27%
23.61%
35.45%
23.26%
34.93%
31.39%
33.56%
32.23%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM8 | Denial Rules
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
60
1,065
707
418
210
915
181
944
674
451
1,125
Percent
33.71%
26.37%
28.83%
23.68%
18.29%
29.81%
18.55%
29.13%
25.99%
27.77%
26.68%
2011
Percent
39.89%
29.88%
32.38%
27.42%
21.95%
33.43%
21.41%
32.98%
28.38%
33.37%
30.31%
2012
Percent
45.51%
33.50%
36.42%
30.65%
25.26%
37.28%
25.51%
36.56%
31.89%
37.38%
34.01%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM9 | Biller’s Dashboard
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
49
908
561
396
208
749
188
769
570
387
957
Percent
27.53%
22.48%
22.88%
22.44%
18.12%
24.41%
19.26%
23.73%
21.98%
23.83%
22.69%
2011
Percent
32.02%
25.58%
26.18%
25.38%
20.99%
27.66%
21.93%
27.03%
24.26%
28.39%
25.85%
2012
Percent
35.96%
28.25%
29.20%
27.71%
23.43%
30.50%
24.90%
29.68%
26.49%
31.90%
28.57%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM10 | EMR Documentation for Claims
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
14
148
116
46
27
135
27
135
77
85
162
Percent
7.87%
3.66%
4.73%
2.61%
2.35%
4.40%
2.77%
4.17%
2.97%
5.23%
3.84%
2011
Percent
5.62%
2.85%
3.47%
2.27%
1.83%
3.39%
1.84%
3.30%
2.70%
3.39%
2.96%
2012
Percent
6.74%
2.65%
3.26%
2.21%
1.66%
3.26%
2.05%
3.05%
2.62%
3.14%
2.82%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
29
Ta ble NGRCM11 | Direct Payer Claims
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
31
481
326
186
129
383
105
407
278
234
512
Percent
17.42%
11.91%
13.30%
10.54%
11.24%
12.48%
10.76%
12.56%
10.72%
14.41%
12.14%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
37
507
337
207
132
412
107
437
289
255
544
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
47
661
406
302
127
581
102
606
417
291
708
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
36
678
392
322
156
558
120
594
415
299
714
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
63
1,037
640
460
253
847
210
890
634
466
1,100
Percent
20.79%
12.55%
13.74%
11.73%
11.50%
13.42%
10.96%
13.48%
11.15%
15.70%
12.90%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
37
536
365
208
130
443
108
465
309
264
573
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
48
709
441
316
137
620
119
638
442
315
757
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
40
712
416
336
164
588
127
625
439
313
752
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
69
1,114
706
477
260
923
219
964
693
490
1,183
Percent
20.79%
13.27%
14.89%
11.78%
11.32%
14.43%
11.07%
14.35%
11.92%
16.26%
13.59%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM12 | Claims Remittance Updates AR
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
37
607
361
283
124
520
101
543
380
264
644
Percent
20.79%
15.03%
14.72%
16.03%
10.80%
16.94%
10.35%
16.75%
14.65%
16.26%
15.27%
2011
Percent
26.40%
16.37%
16.56%
17.11%
11.06%
18.93%
10.45%
18.70%
16.08%
17.92%
16.79%
2012
Percent
26.97%
17.55%
17.99%
17.90%
11.93%
20.20%
12.19%
19.69%
17.05%
19.40%
17.95%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM13 | Eligibility Transaction with Payer
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
31
623
363
291
141
513
108
546
392
262
654
Percent
17.42%
15.42%
14.80%
16.49%
12.28%
16.72%
11.07%
16.85%
15.12%
16.13%
15.51%
2011
Percent
20.22%
16.79%
15.99%
18.24%
13.59%
18.18%
12.30%
18.33%
16.00%
18.41%
16.93%
2012
Percent
22.47%
17.63%
16.97%
19.04%
14.29%
19.16%
13.01%
19.28%
16.93%
19.27%
17.83%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble NGRCM14 | EFT Transaction
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
53
969
609
413
228
794
195
827
607
415
1,022
Percent
29.78%
23.99%
24.84%
23.40%
19.86%
25.87%
19.98%
25.52%
23.41%
25.55%
24.24%
2011
Percent
35.39%
25.67%
26.10%
26.06%
22.04%
27.60%
21.52%
27.46%
24.45%
28.69%
26.08%
2012
Percent
38.76%
27.58%
28.79%
27.03%
22.65%
30.07%
22.44%
29.74%
26.73%
30.17%
28.05%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
An evaluation of next generation RCM adoption by hospital bed-size
reveals the following insights (see Tables NGRCM15–NGRCM21):
• 0–100 beds: web self-pay demonstrated the largest increase at
more than four percentage points. Claims attachment rules and
denial rules each increased in adoption by three percentage
points. EMR documentation for claims showed a slight decrease
in adoption.
• 101–200 beds: web self-pay and denial rules increased in adoption
by approximately four percentage points. All other next generation
RCM applications, except EMR documentation for claims,
increased between one and three percentage points.
• 201–300 beds: the highest increase in adoption is evidenced in the
web self-pay application with an approximate growth of eight
percentage points. Denial rules adoption increased by
approximately five percentage points while claims attachment
rules increased by slightly more than four percentage points.
• 301–400 beds: the adoption of web self-pay had the highest
increase at six percentage points, followed by biller’s dashboard
at more than four percentage points. Besides EMR documentation
for claims and web preregister, all other next generation RCM
applications increased between one and four percentage points.
• 401–500 beds: web self-pay and biller’s dashboard demonstrated
the largest increases in application adoption at more than four
percentage points. Necessity alert at registration decreased by
more than two percentage points, while EMR documentation for
claims decreased by one percentage point. Web preregister, web
schedule, claims attachment rules and denial rules each increased
by three percentage points from 2011 to 2012.
• 501–600 beds: the highest growth in adoption for this bed segment
was for web self-pay at 11 percentage points. Web schedule had
the second largest growth at approximately eight percentage
points. Direct payer claims and claims remittance accounts
receivable updates did not change while all other next generation
RCM applications grew between one and six percentage points.
• Over 600 beds: web self-pay had the largest increase in adoption
at more than 11 percentage points, followed by web schedule at
six percentage points. The remaining next generation RCM
applications increased approximately one to five percentage points.
Ta ble NGRCM15
0–100 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Biller’s Dashboard
Direct Payer Claims
EFT Transaction
2010
232
63
426
334
690
494
514
475
53
230
318
336
503
10.72%
2.91%
19.68%
15.43%
31.87%
22.82%
23.74%
21.94%
2.45%
10.62%
14.69%
15.52%
23.23%
2011
271 12.52%
68
3.14%
542 25.03%
350 16.17%
730 33.72%
538 24.85%
581 26.84%
535 24.71%
42
1.94%
247 11.41%
329 15.20%
366 16.91%
542 25.03%
2012
294
108
641
378
748
606
650
583
39
252
349
379
565
13.58%
4.99%
29.61%
17.46%
34.55%
27.99%
30.02%
26.93%
1.80%
11.64%
16.12%
17.51%
26.10%
Ta ble NGRCM16
101–200 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
172
70
280
218
323
213
219
157
34
85
103
111
180
21.45%
8.73%
34.91%
27.18%
40.27%
26.56%
27.31%
19.58%
4.24%
10.60%
12.84%
13.84%
22.44%
2011
% of 802 Hospitals
212 26.43%
70
8.73%
338 42.14%
244 30.42%
346 43.14%
239 29.80%
256 31.92%
188 23.44%
24
2.99%
90 11.22%
122 15.21%
122 15.21%
198 24.69%
2012
217
83
373
273
365
268
288
206
21
100
132
130
221
27.06%
10.35%
46.51%
34.04%
45.51%
33.42%
35.91%
25.69%
2.62%
12.47%
16.46%
16.21%
27.56%
Ta ble NGRCM17
201–300 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
105
57
153
136
192
137
137
116
24
57
79
73
122
21.74%
11.80%
31.68%
28.16%
39.75%
28.36%
28.36%
24.02%
4.97%
11.80%
16.36%
15.11%
25.26%
2011
% of 483 Hospitals
130 26.92%
60 12.42%
182 37.68%
145 30.02%
208 43.06%
164 33.95%
160 33.13%
135 27.95%
18
3.73%
67 13.87%
89 18.43%
82 16.98%
130 26.92%
2012
142
70
223
150
215
185
183
153
19
71
95
87
145
29.40%
14.49%
46.17%
31.06%
44.51%
38.30%
37.89%
31.68%
3.93%
14.70%
19.67%
18.01%
30.02%
Ta ble NGRCM18
301–400 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
83
37
113
91
141
95
92
78
16
49
50
46
81
26.60%
11.86%
36.22%
29.17%
45.19%
30.45%
29.49%
25.00%
5.13%
15.71%
16.03%
14.74%
25.96%
2011
% of 312 Hospitals
81 25.96%
44 14.10%
124 39.74%
95 30.45%
144 46.15%
100 32.05%
101 32.37%
85 27.24%
16
5.13%
52 16.67%
58 18.59%
46 14.74%
86 27.56%
2012
83
50
143
103
153
111
114
99
14
57
67
52
97
26.60%
16.03%
45.83%
33.01%
49.04%
35.58%
36.54%
31.73%
4.49%
18.27%
21.47%
16.67%
31.09%
Ta ble NGRCM19
401–500 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
47
17
61
58
87
71
72
61
13
43
44
42
65
25.00%
9.04%
32.45%
30.85%
46.28%
37.77%
38.30%
32.45%
6.91%
22.87%
23.40%
22.34%
34.57%
2011
% of 188 Hospitals
45 23.94%
16
8.51%
77 40.96%
64 34.04%
93 49.47%
73 38.83%
75 39.89%
66 35.11%
9
4.79%
38 20.21%
48 25.53%
43 22.87%
66 35.11%
2012
51
22
86
65
88
79
81
74
7
38
49
44
69
27.13%
11.70%
45.74%
34.57%
46.81%
42.02%
43.09%
39.36%
3.72%
20.21%
26.06%
23.40%
36.70%
31
Ta ble NGRCM20
501–600 Beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
35
14
47
29
44
36
36
30
7
20
19
20
25
30.17%
12.07%
40.52%
25.00%
37.93%
31.03%
31.03%
25.86%
6.03%
17.24%
16.38%
17.24%
21.55%
2011
% of 116 Hospitals
34 29.31%
12 10.34%
53 45.69%
30 25.86%
46 39.66%
42 36.21%
42 36.21%
35 30.17%
5
4.31%
21 18.10%
25 21.55%
24 20.69%
28 24.14%
2012
36
21
66
34
52
48
49
41
7
21
25
25
30
31.03%
18.10%
56.90%
29.31%
44.83%
41.38%
42.24%
35.34%
6.03%
18.10%
21.55%
21.55%
25.86%
Ta ble NGRCM21
Over 600 beds
Web PreRegister
Web Schedule
Web Self-Pay
Denial Rules
Direct Payer Claims
EFT Transaction
2010
35
27
54
40
52
51
55
40
15
28
31
26
46
23.18%
17.88%
35.76%
26.49%
34.44%
33.77%
36.42%
26.49%
9.93%
18.54%
20.53%
17.22%
30.46%
2011
% of 151 Hospitals
39 25.83%
22 14.57%
55 36.42%
48 31.79%
63 41.72%
55 36.42%
63 41.72%
46 30.46%
11
7.28%
29 19.21%
37 24.50%
31 20.53%
50 33.11%
2012
41
31
72
51
67
62
69
49
12
34
40
35
56
27.15%
20.53%
47.68%
33.77%
44.37%
41.06%
45.70%
32.45%
7.95%
22.52%
26.49%
23.18%
37.09%
The next generation RCM market is still in its infancy, but these
applications are expected to become critical solutions for all
hospitals within the next few years (see Table NGRCM1). This
market will continue to be impacted through 2015 by:
• Capital constraints and the intense competition of IT capital
funds, which will drive many hospitals to acquire bolt-on next
generation RCM applications to enhance their existing, legacy
RCM environments, extending their useful life.
• Possible major upgrades or outright replacements of RCM
solutions due to the ICD-10 mandate.
• Shifting profile of the vendors offering next generation RCM
solutions. Many next generation RCM applications in each of the
product categories are currently delivered by relatively small,
specialty vendors. Over time, we expect:
–– Larger RCM vendors to introduce similar capabilities as an
integral component of new versions. Hospitals upgrading to
these new versions will displace these niche products.
–– In the near term, many of the specialty vendors offering these
applications will be acquired by larger RCM vendors.
• As more small- to mid-sized hospitals contract for EMRs, many
of these hospitals will acquire complete application suites,
including replacement of legacy RCM applications with versions
that incorporate these features.
• Stage 2 Meaningful Use has a strong intent to increase “patient
engagement” as a way to begin tackling the chronic disease
issues in the country. We see this as another Meaningful Use
driver for web capabilities adoption.
▶▶ Health Information Management
The health information management (HIM) IT environment focuses
on solutions designed to assist with the maintenance and care of
paper as well as EHRs. Eleven different HIM applications are
tracked by HIMSS Analytics in this report; abstracting, case mix
management, chart deficiency, chart tracking/locator, computerassisted coding, data warehousing/mining-clinical, dictation,
dictation with speech recognition, encoder, outcomes and quality
management and in-house transcription.
The HIM environment generally presents as a well-penetrated
marketplace. Five of the 11 HIM applications tracked had
penetration levels of 90 percent or greater (abstracting and encoder,
chart deficiency, chart tracking/locator and dictation), while eight
applications exceeded 70 percent (see Table HIM1). That said,
three applications in this environment have exceedingly lower
penetration levels when compared to the other applications in this
suite: dictation with speech recognition (45.3 percent), data
warehousing/mining–clinical (43.0 percent), and computer assisted
coding (12.8 percent).
Overall, the HIM environment is a growing market as nine of the
eleven applications tracked in this report increased penetration
levels of one to five percentage points in 2012. The two applications
with lower penetration levels in 2012 were in-house transcription
(decreased by approximately one percentage point) and computer
assisted coding (decreased by more than four percentage points).
While the decline of the in-house transcription market penetration
may be reflective of a service increasingly outsourced, the notable
decline in the computer assisted coding is due in large part to a
change in HIMSS Analytics’ definition of computer assisted coding.
In 2012, the definition of computer assisted coding was changed to
read “software solutions that utilize natural language processing
(NLP) and exclusive patented algorithmic software to electronically
analyze entire medical charts to pre-code with both CPT procedure
and ICD diagnostic nomenclatures.” Due to the change in the
definitions, it is likely that computer assisted coding data from 2010
and 2011 were over-reported.
Ta ble HIM1 | Health Information Management
N=4,217
2010
2011
Abstracting
95.61%
96.66%
Case Mix Management
78.68%
79.87%
Chart Deficiency
90.70%
92.39%
Chart Tracking/Locator
89.49%
91.13%
Computer Assisted Coding
14.63%
17.17%
Data Warehousing/Mining–Clinical
33.32%
38.42%
Dictation
88.10%
90.75%
Dictation with Speech Recognition
33.67%
40.67%
Encoder
95.94%
96.59%
Outcomes and Quality Management
68.65%
70.31%
In-House Transcription
77.73%
76.76%
2012
97.34%
81.20%
93.72%
91.89%
12.78%
42.97%
92.13%
45.27%
97.15%
73.18%
75.39%
▶▶ Health Information Management con tinue d
Ta ble hiM2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Abstracting
50
90.91%
Case Mix Management
37
97.37%
Chart Deficiency
45
88.24%
43
91.49%
2
2.99%
7
50.00%
Dictation
6
54.55%
16
48.48%
Encoder
9
52.94%
12
63.16%
5
83.33%
The best growth potential for the HIM market is expected in
two applications—dictation with speech recognition and data
warehousing/mining-clinical. However, with respect to the latter, the
increasing trend towards more highly integrated, enterprise-wide
architectures to support business and clinical intelligence, outcomes
and quality reporting, can lead to a corresponding de-emphasis of, and
decline in, specialized, department-specific data marts. We believe
that a significant portion of the growth reported in the adoption of the
data warehousing/mining – clinical and the outcomes and quality
management applications go hand-in-hand with the growth
highlighted in the Financial Decision Support section of this report.
The market penetration of computer assisted coding is highest among
academic medical centers at close to 25 percent in 2012. The next
highest is general medical surgical hospitals and multi-hospital systems
at slightly under 15 percent. As usual, academic medical centers are
often closely associated as early adopters to new technology.
Encoding upgrades (due to ICD-10 upgrade requirements) and
outcomes and quality management (due to ARRA Meaningful Use
reporting) are expected to be growth drivers in the HIM market.
Standardization of the templates for transcribed documents will
improve the ability of hospitals to share standard patient information
with one another using the CDA construct (see www.HealthStory.com).
The HIM market generally reflects a replacement buyer market
partially driven by continued movement away form “best of breed”
solutions. This is especially true for abstracting, case mix
management, chart deficiency, chart tracking/locator and in-house
transcription. That said, the majority of purchases for computer
assisted coding will be first time purchases (see Table HIM2).
Through 2015, two government mandates are expected to
significantly impact the HIM market. The first is the requirement to
upgrade encoding systems to use ICD-10 codes by October 1, 2014
(which was delayed in August 2012 from the original date of
October 1, 2013). The other mandate is the requirement to report
on clinical outcomes as part of the ARRA Meaningful Use
requirements. Health reform, and changes in reimbursement
methods demanded by both public and private insurers, will
increase the need for hospitals to report process and outcomes
measures in order to justify reimbursement or qualify for pay for
performance bonus payments. These mandates will drive increased
HIM application upgrades, if not outright system replacements.
Highlights of the past year by hospital segments reveal the following:
• Abstracting: the rural hospital and critical access hospital
segments have the largest year-over-year growth at approximately
two percentage points. Most of the other segments reported a
•
•
•
•
•
•
•
•
•
•
for the First Time
5
1
6
4
65
7
5
17
8
7
1
for the First Time
9.09%
2.63%
11.76%
8.51%
97.01%
50.00%
45.45%
51.52%
47.06%
36.84%
16.67%
N = Total Number of
Hospitals Planning
55
38
51
47
67
14
11
33
17
19
6
growth of one percentage point or less. Having already reached
market saturation, there was no reported growth among academic
medical centers (see Table HIM3).
Case mix management: rural hospitals had the highest year-overyear growth at more than three percentage points. The critical
access hospital segment also saw growth of more than two
percentage points (see Table HIM4).
Chart deficiency: both the critical access hospital and the rural
hospital segments saw growth of more than three percentage
points (see Table HIM5). All other segments registered growth
of less than three percentage points.
Chart tracking/locator: the critical access and rural hospital
segments both reported growth of more than three percentage
points. A number of segments reported a slight decline in use
of chart tracking/locator solutions (see Table HIM6).
Computer assisted coding: in 2012, about one-quarter of the
academic medical centers reported adopting computer assisted
coding solutions. Due to a change in definition of computer
assisted coding, comparison to previous years’ data is not
meaningful (see Table HIM7).
Data warehousing/mining–clinical: all of the hospital segments
indicated a growth ranging from three to six percentage points,
with the highest growth demonstrated by academic medical
centers and the multi-hospital system segments (see Table HIM8).
Dictation: except for the academic medical center segment, all
segments grew three percentage points or less (see Table HIM9).
Growth was greatest in the critical access hospital and rural
hospital segments.
Dictation with speech recognition: the growth for all hospital
segments was consistent ranging between three and five
percentage points (see Table HIM10). The greatest growth
was in the general medical/surgical hospital and multi-hospital
system segments.
Encoder: because this solution is on the verge of complete market
saturation across all market segments, there was little increase in
adoption over the past year. No segment reported growth of more
than two percentage points (see Table HIM11).
Outcomes and quality management: both the rural hospital and
critical access hospital segments reported growth more than four
percentage points from 2011 to 2012. The other hospital segments
indicated growth ranging from two to four percentage points (see
Table HIM12).
In-house transcription: all hospital segments demonstrated a
decrease in the penetration of this application. The academic
medical center segment indicated the sharpest decrease in
adoption at more than two percentage points (see Table HIM13).
33
Ta ble HIM3 | Abstracting
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Non- Critical Access
Rural
Urban
All
Segment
Count
176
3,856
2,425
1,607
1,011
3,021
860
3,172
2,531
1,501
4,032
Percent
98.88%
95.47%
98.90%
91.05%
88.07%
98.44%
88.11%
97.87%
97.61%
92.43%
95.61%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,899
2,432
1,644
1,041
3,035
883
3,193
2,547
1,529
4,076
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
167
3,201
2,162
1,206
675
2,693
587
2,781
2,241
1,127
3,368
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,719
2,405
1,491
889
3,007
758
3,138
2,500
1,396
3,896
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,667
2,377
1,466
869
2,974
744
3,099
2,480
1,363
3,843
Percent
99.44%
96.53%
99.18%
93.14%
90.68%
98.89%
90.47%
98.52%
98.23%
94.15%
96.66%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,928
2,434
1,671
1,066
3,039
905
3,200
2,556
1,549
4,105
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
170
3,254
2,183
1,241
707
2,717
619
2,805
2,273
1,151
3,424
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,774
2,413
1,539
933
3,019
792
3,160
2,512
1,440
3,952
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,700
2,375
1,500
912
2,963
780
3,095
2,475
1,400
3,875
Percent
99.44%
97.25%
99.27%
94.67%
92.86%
99.02%
92.73%
98.73%
98.57%
95.38%
97.34%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM4 | Case Mix Management
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
166
3,152
2,133
1,185
668
2,650
578
2,740
2,205
1,113
3,318
Percent
93.26%
78.04%
86.99%
67.14%
58.19%
86.35%
59.22%
84.54%
85.04%
68.53%
78.68%
2011
Percent
93.82%
79.25%
88.17%
68.33%
58.80%
87.75%
60.14%
85.81%
86.42%
69.40%
79.87%
2012
Percent
95.51%
80.56%
89.03%
70.31%
61.59%
88.53%
63.42%
86.55%
87.66%
70.87%
81.20%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM5 | Chart Deficiency
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
177
3,648
2,388
1,437
845
2,980
723
3,102
2,469
1,356
3,825
Percent
99.44%
90.32%
97.39%
81.42%
73.61%
97.10%
74.08%
95.71%
95.22%
83.50%
90.70%
2011
Percent
99.44%
92.08%
98.08%
84.48%
77.44%
97.98%
77.66%
96.82%
96.41%
85.96%
92.39%
2012
Percent
100.00%
93.44%
98.41%
87.20%
81.27%
98.37%
81.15%
97.50%
96.88%
88.67%
93.72%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM6 | Chart Tracking/Locator
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
177
3,597
2,365
1,409
827
2,947
709
3,065
2,451
1,323
3,774
Percent
99.44%
89.06%
96.45%
79.83%
72.04%
96.02%
72.64%
94.57%
94.52%
81.47%
89.49%
2011
Percent
98.88%
90.79%
96.94%
83.06%
75.70%
96.90%
76.23%
95.62%
95.64%
83.93%
91.13%
2012
Percent
98.31%
91.61%
96.86%
84.99%
79.44%
96.55%
79.92%
95.50%
95.45%
86.21%
91.89%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM7 | Computer Assisted Coding
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
39
578
420
197
122
495
96
521
391
226
617
Percent
21.91%
14.31%
17.13%
11.16%
10.63%
16.13%
9.84%
16.08%
15.08%
13.92%
14.63%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
46
678
479
245
148
576
110
614
467
257
724
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
108
1,512
1,088
532
229
1,391
196
1,424
1,188
432
1,620
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,655
2,365
1,462
965
2,862
828
2,999
2,397
1,430
3,827
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
126
1,589
1,225
490
269
1,446
194
1,521
1,219
496
1,715
Percent
25.84%
16.79%
19.54%
13.88%
12.89%
18.77%
11.27%
18.94%
18.01%
15.83%
17.17%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
43
496
365
174
97
442
76
463
387
152
539
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
118
1,694
1,205
607
290
1,522
248
1,564
1,332
480
1,812
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,713
2,386
1,499
998
2,887
855
3,030
2,419
1,466
3,885
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
134
1,775
1,348
561
326
1,583
241
1,668
1,357
552
1,909
Percent
24.16%
12.28%
14.89%
9.86%
8.45%
14.40%
7.79%
14.29%
14.92%
9.36%
12.78%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM8 | Data Warehousing/Mining–Clinical
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
95
1,310
930
475
208
1,197
173
1,232
1,026
379
1,405
Percent
53.37%
32.43%
37.93%
26.91%
18.12%
39.00%
17.73%
38.01%
39.57%
23.34%
33.32%
2011
Percent
60.67%
37.44%
44.37%
30.14%
19.95%
45.32%
20.08%
43.94%
45.82%
26.60%
38.42%
2012
Percent
66.29%
41.94%
49.14%
34.39%
25.26%
49.59%
25.41%
48.26%
51.37%
29.56%
42.97%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM9 | Dictation
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
168
3,547
2,316
1,399
921
2,794
788
2,927
2,330
1,385
3,715
Percent
94.38%
87.82%
94.45%
79.26%
80.23%
91.04%
80.74%
90.31%
89.86%
85.28%
88.10%
2011
Percent
96.63%
90.49%
96.45%
82.83%
84.06%
93.26%
84.84%
92.53%
92.44%
88.05%
90.75%
2012
Percent
96.63%
91.93%
97.31%
84.93%
86.93%
94.07%
87.60%
93.49%
93.29%
90.27%
92.13%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM10 | Dictation with Speech Recognition
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
111
1,309
1,017
403
192
1,228
141
1,279
1,031
389
1,420
Percent
62.36%
32.41%
41.48%
22.83%
16.72%
40.01%
14.45%
39.46%
39.76%
23.95%
33.67%
2011
Percent
70.79%
39.34%
49.96%
27.76%
23.43%
47.12%
19.88%
46.93%
47.01%
30.54%
40.67%
2012
Percent
75.28%
43.95%
54.98%
31.78%
28.40%
51.58%
24.69%
51.47%
52.33%
33.99%
45.27%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
35
Ta ble HIM11 | Encoder
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
178
3,868
2,441
1,605
1,007
3,039
857
3,189
2,553
1,493
4,046
Percent
100.00%
95.77%
99.55%
90.93%
87.72%
99.02%
87.81%
98.40%
98.46%
91.93%
95.94%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,895
2,443
1,630
1,025
3,048
875
3,198
2,560
1,513
4,073
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
153
2,812
1,944
1,021
494
2,471
441
2,524
2,110
855
2,965
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
127
3,110
1,928
1,309
899
2,338
775
2,462
1,978
1,259
3,237
Percent
100.00%
96.43%
99.63%
92.35%
89.29%
99.32%
89.65%
98.67%
98.73%
93.17%
96.59%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,919
2,445
1,652
1,045
3,052
892
3,205
2,565
1,532
4,097
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
160
2,926
2,005
1,081
544
2,542
487
2,599
2,172
914
3,086
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
123
3,056
1,882
1,297
894
2,285
769
2,410
1,941
1,238
3,179
Percent
100.00%
97.03%
99.71%
93.60%
91.03%
99.45%
91.39%
98.89%
98.92%
94.33%
97.15%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM12 | Outcomes and Quality Management
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
151
2,744
1,909
986
466
2,429
418
2,477
2,066
829
2,895
Percent
84.83%
67.94%
77.85%
55.86%
40.59%
79.15%
42.83%
76.43%
79.68%
51.05%
68.65%
2011
Percent
85.96%
69.62%
79.28%
57.85%
43.03%
80.51%
45.18%
77.88%
81.37%
52.65%
70.31%
2012
Percent
89.89%
72.44%
81.77%
61.25%
47.39%
82.83%
49.90%
80.19%
83.76%
56.28%
73.18%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble HIM13 | In-House Transcription
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
137
3,141
1,971
1,307
897
2,381
777
2,501
1,991
1,287
3,278
Percent
76.97%
77.77%
80.38%
74.05%
78.14%
77.58%
79.61%
77.17%
76.78%
79.25%
77.73%
2011
The highlights by bed size segments yielded the following
(see Tables HIM14–HIM20):
• 0–100 beds: data warehousing-clinical indicated the largest
increase in growth from 2011 to 2012 at nearly five percentage
points, followed by dictation with speech recognition at more
than four percentage points (see Table HIM14). In-house
transcription and computer assisted coding (redefined for 2012)
both showed decreases in market penetration.
• 101–200 beds: eight of the 11 applications indicated an increase
in market penetration; the largest growth was among dictation
with speech recognition solutions. Decreases in market
penetration were seen for chart tracking/locator, computer
assisted coding and in-house transcription (see Table HIM15).
• 201–300 beds: dictation with speech recognition showed the
highest growth at more than five percentage points. Growth
was also strong for data warehousing/mining-clinical solutions.
Decreased market penetration was seen for chart tracking/
locator, computer assisted coding and in-house transcription
(see Table HIM16).
Percent
71.35%
77.00%
78.63%
74.16%
78.31%
76.18%
79.41%
75.96%
76.28%
77.52%
76.76%
2012
Percent
69.10%
75.66%
76.75%
73.48%
77.87%
74.45%
78.79%
74.36%
74.86%
76.23%
75.39%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
• 301–400 beds: the application with the greatest growth in this
segment was dictation with speech recognition, at nearly four
percentage points. Decreased market penetration was noted for
chart tracking/locator, computer assisted coding and in-house
transcription (see Table HIM17).
• 401–500 beds: at more than six percentage points, data warehousing/
mining-clinical demonstrated the largest growth from 2011 to 2012.
This was followed by dictation with speech recognition at more
than four percentage points (see Table HIM18). Adoption of both
computer assisted coding and in-house transcription declined. There
are also many saturated markets with no growth potential.
• 501–600 beds: both the dictation with speech recognition and data
warehousing/mining-clinical indicated a growth of more than six
percentage points from 2011 to 2012 (see Table HIM19). Declines in
market penetration were noted in abstracting, chart deficiency,
chart tracking/locator, encoder and in-house transcription.
• Over 600 beds: dictation with speech recognition and data
warehousing/mining-clinical are the only two applications to
indicate a growth from 2011 to 2012. All other segments reported
a decline or no change (see Table HIM20).
Ta ble HIM14
Ta ble HIM19
0–100 Beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
2010
1,992
1,470
1,790
1,757
246
506
1,756
427
1,998
1,202
1,653
2011
2012
92.01% 2,031 93.81% 2,057 95.01%
67.90% 1,500 69.28% 1,547 71.45%
82.68% 1,857 85.77% 1,908 88.13%
81.15% 1,824 84.25% 1,864 86.10%
11.36% 293 13.53% 199
9.19%
23.37% 581 26.84% 682 31.50%
81.11% 1,832 84.62% 1,880 86.84%
19.72% 544 25.13% 640 29.56%
92.29% 2,026 93.58% 2,048 94.60%
55.52% 1,247 57.60% 1,330 61.43%
76.35% 1,663 76.81% 1,636 75.57%
Ta ble HIM15
2010
795
720
787
784
126
304
762
320
800
653
619
99.13%
89.78%
98.13%
97.76%
15.71%
37.91%
95.01%
39.90%
99.75%
81.42%
77.18%
2011
% of 802 Hospitals
798 99.50%
727 90.65%
791 98.63%
789 98.38%
140 17.46%
363 45.26%
779 97.13%
382 47.63%
799 99.63%
660 82.29%
600 74.81%
2012
801
731
796
787
99
399
784
419
801
677
592
99.88%
91.15%
99.25%
98.13%
12.34%
49.75%
97.76%
52.24%
99.88%
84.41%
73.82%
Ta ble HIM16
201–300 Beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
2010
483 100.00%
438 90.68%
481 99.59%
477 98.76%
90 18.63%
209 43.27%
461 95.45%
241 49.90%
483 100.00%
402 83.23%
391 80.95%
2011
% of 483 Hospitals
483 100.00%
441 91.30%
481 99.59%
476 98.55%
109 22.57%
249 51.55%
471 97.52%
285 59.01%
483 100.00%
407 84.27%
381 78.88%
2012
483 100.00%
443 91.72%
482 99.79%
474 98.14%
85 17.60%
271 56.11%
474 98.14%
310 64.18%
483 100.00%
417 86.34%
372 77.02%
Ta ble HIM17
301–400 Beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
2010
308 98.72%
272 87.18%
312 100.00%
310 99.36%
58 18.59%
148 47.44%
301 96.47%
165 52.88%
310 99.36%
253 81.09%
243 77.88%
2011
% of 312 Hospitals
309 99.04%
280 89.74%
312 100.00%
309 99.04%
67 21.47%
170 54.49%
306 98.08%
196 62.82%
310 99.36%
259 83.01%
235 75.32%
2012
310 99.36%
280 89.74%
312 100.00%
308 98.72%
52 16.67%
179 57.37%
309 99.04%
208 66.67%
311 99.68%
264 84.62%
233 74.68%
Ta ble HIM18
401–500 Beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
2010
115 99.14%
102 87.93%
116 100.00%
115 99.14%
23 19.83%
53 45.69%
113 97.41%
69 59.48%
116 100.00%
96 82.76%
98 84.48%
2011
% of 116 Hospitals
116 100.00%
101 87.07%
116 100.00%
115 99.14%
25 21.55%
58 50.00%
113 97.41%
78 67.24%
116 100.00%
95 81.90%
95 81.90%
2012
115
104
115
113
26
65
113
86
115
98
92
99.14%
89.66%
99.14%
97.41%
22.41%
56.03%
97.41%
74.14%
99.14%
84.48%
79.31%
Ta ble HIM20
101–200 Beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
501–600 Beds
2010
188 100.00%
172 91.49%
188 100.00%
183 97.34%
42 22.34%
91 48.40%
180 95.74%
99 52.66%
188 100.00%
153 81.38%
149 79.26%
2011
% of 188 Hospitals
188 100.00%
174 92.55%
188 100.00%
183 97.34%
47 25.00%
99 52.66%
181 96.28%
118 62.77%
188 100.00%
160 85.11%
141 75.00%
2012
188 100.00%
174 92.55%
188 100.00%
182 96.81%
36 19.15%
111 59.04%
183 97.34%
126 67.02%
188 100.00%
163 86.70%
137 72.87%
Over 600 beds
Abstracting
Case Mix Management
Chart Deficiency
Dictation
Encoder
2010
151 100.00%
144 95.36%
151 100.00%
148 98.01%
32 21.19%
94 62.25%
142 94.04%
99 65.56%
151 100.00%
136 90.07%
125 82.78%
2011
% of 151 Hospitals
151 100.00%
145 96.03%
151 100.00%
147 97.35%
43 28.48%
100 66.23%
145 96.03%
112 74.17%
151 100.00%
137 90.73%
122 80.79%
2012
151 100.00%
145 96.03%
151 100.00%
147 97.35%
42 27.81%
105 69.54%
145 96.03%
120 79.47%
151 100.00%
137 90.73%
117 77.48%
When analyzing the HIM contract information in the HIMSS
Analytics database, contracts for most of the applications tracked
were signed between 1995 and 2004. The notable exception
surrounds computer assisted coding contracts for which
approximately three-quarters of these contracts were signed
between 2010 and 2012 (see Tables HIM20–HIM23).
Ta ble HIM21
Abstracting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Case Mix Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Chart Deficiency
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
119
213
694
736
634
430
2,826
2,826
2,826
2,826
2,826
2,826
2,826
2,826
4.21%
7.54%
24.56%
26.04%
22.43%
15.22%
100.00%
114
233
552
722
430
304
2,355
2,355
2,355
2,355
2,355
2,355
2,355
2,355
4.85%
9.91%
23.48%
30.71%
18.29%
12.93%
100.00%
63
171
567
838
647
410
2,696
2,696
2,696
2,696
2,696
2,696
2,696
2,696
2.34%
6.35%
21.05%
31.11%
24.02%
15.22%
100.00%
37
Ta ble HIM22
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Ta ble HIM24
# for Contract
Range
Total
Responding
% of Total
Responding
68
181
564
808
593
393
2,607
2,607
2,607
2,607
2,607
2,607
2,607
2,607
2.61%
6.95%
21.64%
31.01%
22.76%
15.08%
100.00%
0
0
5
5
11
74
95
95
95
95
95
95
95
95
0.00%
0.00%
5.26%
5.26%
11.58%
77.89%
100.00%
5
139
70
262
295
203
974
974
974
974
974
974
974
974
0.52%
14.36%
7.23%
27.07%
30.48%
20.97%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
31
76
263
605
435
171
1,581
1,581
1,581
1,581
1,581
1,581
1,581
1,581
1.96%
4.81%
16.64%
38.27%
27.51%
10.82%
100.00%
0
6
7
112
322
143
590
590
590
590
590
590
590
590
0.00%
1.05%
1.23%
19.61%
56.39%
25.04%
100.00%
222
280
681
556
294
153
2,186
2,181
2,181
2,181
2,181
2,181
2,181
2,181
10.18%
12.84%
31.22%
25.49%
13.48%
7.02%
100.23%
Ta ble HIM23
Dictation
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Encoder
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
37
132
440
620
344
268
1,841
1,841
1,841
1,841
1,841
1,841
1,841
1,841
2.02%
7.21%
24.03%
33.86%
18.79%
14.64%
100.00%
35
141
318
477
398
197
1,566
1,566
1,566
1,566
1,566
1,566
1,566
1,566
2.25%
9.07%
20.45%
30.68%
25.59%
12.67%
100.00%
Chart deficiency and chart tracking/locator applications are
approaching this threshold (90 percent to 95 percent). Ultimately, we
believe that chart deficiency and chart tracking/locator applications
will become obsolete as the adoption of EHR applications become
more prevalent. However, until dependence on paper documentation is
completely eliminated, these applications will maintain a healthy
market presence.
The HIM IT applications market will be significantly impacted
through 2015 by several factors:
• Preparations for conversation to ICD-10. This includes mapping
several applications that rely on encoded data to the new
ICD-10 formats (also significantly affecting interfaces) by
October 1, 2014.
• Negotiating the contractual commitments between hospitals and
vendors for federal, state and other regulatory upgrades relative to
ICD-10 encoding upgrades.
• Increased demands from the government (ARRA) and payers
for reporting quality and outcomes data.
• Increased conversion of the medical record from paper to a
digital format; the mixed format providing some special
challenges for security and operational management, as well as
patient care challenges.
• Acquisitions of ambulatory practices which have completely
paper based records by IDNs.
• Increase focus on quality outcomes for participating in outcomes
based reimbursement models (e.g. pay for performance, ACOs).
• Increased adoption of nomenclature coding standards such as
SNOMED and LOINC and RxNorm.
▶▶ Document Management/Electronic Forms
Healthcare IT document management and electronic form
applications are important components of the EHR environment
for scanning paper forms that still may be in use as hospitals move
to a paperless environment. It has been HIMSS Analytics’
expectation that the market increasingly adopted these applications
to prevent having the medical staff and clinical employees look
both online and into a paper chart for clinical documentation, an
expectation which appears to be validated.
Document management allowing hospitals to track and store
electronic documents and/or images of paper documents yielding
greater efficiencies in the ability to reuse information and to control
the flow of the documents, from creation to archiving. Document
management is often used to store documents related to registration,
personnel management, and medical records. These systems
commonly provide storage, versioning, metadata, security, as well as
indexing and retrieval capabilities. Electronic forms automatically
generates forms and can be populated with patient data by importing
data from another system and/or can export data that has been
entered into another system. The electronic forms typically print
identifying bar codes to facilitate immediate scanning and indexing
to the right location in the right patient electronic record.
During the past three years, the document management and
electronic forms application market has demonstrated a very positive
growth trajectory (see Table DMEF1). Electronic forms management
grew by slightly more than seven percentage points from 2011 to
2012, while the implementation of document management solutions
increased by approximately 3.5 percentage points.
Three-quarters of planned purchases for electronic forms
management applications are expected to be among hospitals
making a purchase for the first time. In comparison, just more than
half of purchases for document management solutions will be for
the first time (see Table DMEF2).
Ta ble DME F1 | Document Management/Electronic Forms
N=4,217
2010
2011
Document Management
67.54%
71.59%
Electronic Forms Management
51.22%
56.01%
2012
75.12%
63.36%
An evaluation of the 2012 hospital market segments reveals
the following highlights:
• Document management: the critical access hospital segment
indicated the highest increase in adoption, at nearly seven
percentage points (see Table DMEF3), followed closely by the
rural hospital and single hospital.
• Electronic forms management: all hospital segments—except
academic hospitals—grew at least five percentage points. The
other non-general medical/surgical hospital segment even grew
more than 10 percentage points this past year (see Table DMEF4).
Review of the document management and electronic forms
management market in 2012 by bed size segments provides
additional insight into this application environment (see Tables
DMEF5–DMEF11). In our opinion, the adoption of these
technologies, particularly electronic forms management, has been
heavily influenced by the increases in EMR adoption seen across all
bed size ranges by the desire to have all documentation and orders
available on the network, even if it was originated on paper.
Document management adoption rates exceed 80 percent in all
bed size ranges over 100 beds. Conversely, electronic forms
management has lower adoption rates and demonstrated larger
growth increases.
• 0–100 beds: this segment has the lowest adoption rates of both
the document management and electronic forms management
applications (see Table DMEF5). Electronic forms management
adoption increased by more than 10 percentage points while
document management adoption increased by just more than four
percentage points.
• 101–200 beds: from 2011 to 2012, electronic forms management
grew nearly six percentage points, while document management
adoption grew by nearly four percentage points (see Table DMEF6).
• 201–300 beds: both the document management and electronic
forms management applications increased by two percentage
points (see Table DMEF7).
• 301–400 beds: electronic forms management increased by nearly
four percentage points from 2011 to 2012, while document
management’s growth was just more than one percentage point
(see Table DMEF8).
Ta ble DME F 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Document Management
34
57.63%
6
24.00%
for the First Time
25
19
for the First Time
42.37%
76.00%
N = Total Number of
Hospitals Planning
59
25
Ta ble DME F 3 | Document Management
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
151
2,697
1,806
1,042
540
2,308
459
2,389
1,918
930
2,848
Percent
84.83%
66.77%
73.65%
59.04%
47.04%
75.20%
47.03%
73.71%
73.97%
57.27%
67.54%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
158
2,861
1,902
1,117
598
2,421
508
2,511
2,021
998
3,019
Percent
88.76%
70.83%
77.57%
63.29%
52.09%
78.89%
52.05%
77.48%
77.94%
61.45%
71.59%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
160
3,008
1,980
1,187
678
2,490
568
2,600
2,078
1,090
3,168
Percent
89.89%
74.47%
80.75%
67.25%
59.06%
81.13%
58.20%
80.22%
80.14%
67.12%
75.12%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
39
▶▶ Document Management/Electronic Forms con tinue d
Ta ble DME F4 | Electronic Forms Management
2010
Segment
Count
118
2,042
1,383
777
443
1,717
357
1,803
1,422
738
2,160
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Percent
66.29%
50.56%
56.40%
44.02%
38.59%
55.95%
36.58%
55.63%
54.84%
45.44%
51.22%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
• 401–500 beds: document management adoption neared 90 percent
in 2012 as the market penetration grew by less than one percentage
point in the past year (see Table DMEF9). Electronic forms
management demonstrated an increase of two percentage points.
• 501–600 beds: both applications increased in adoption from 2011 to
2012. Electronic forms management adoption increased by slightly
more than four percentage points while document management
adoption grew by five percentage points (see Table DMEF10).
• Over 600 beds: document management adoption reached more
than 90 percent market penetration in 2011 and grew by
approximately one percentage point in 2012. Electronic forms
management’s adoption grew by three percentage points from
2011 to 2012 (see Table DMEF11).
Ta ble DME F5
0–100 Beds
Document Management
2010
1,242
913
2011
2012
57.37% 1,335 61.66% 1,429 66.00%
42.17% 1,031 47.62% 1,259 58.15%
Ta ble DME F6
101–200 Beds
Document Management
2010
581
457
2011
2012
% of 802 Hospitals
72.44% 614 76.56% 646 80.55%
56.98% 485 60.47% 531 66.21%
Ta ble DME F 7
201–300 Beds
Document Management
2010
380
290
2011
2012
% of 483 Hospitals
78.67% 403 83.44% 413 85.51%
60.04% 315 65.22% 325 67.29%
Ta ble DME F 8
301–400 Beds
Document Management
2010
255
200
2011
2012
% of 312 Hospitals
81.73% 263 84.29% 267 85.58%
64.10% 212 67.95% 224 71.79%
Ta ble DME F 9
401–500 Beds
Document Management
2010
125
125
2011
2012
% of 188 Hospitals
66.49% 168 89.36% 169 89.89%
66.49% 134 71.28% 138 73.40%
Ta ble DME F10
501–600 Beds
Document Management
2010
94
78
2011
2012
% of 116 Hospitals
81.03%
97 83.62% 103 88.79%
67.24%
80 68.97%
85 73.28%
Ta ble DME F11
Over 600 beds
Document Management
2010
132
97
2011
2012
% of 151 Hospitals
87.42% 139 92.05% 141 93.38%
64.24% 105 69.54% 110 72.85%
Segment
Count
128
2,234
1,484
878
517
1,845
412
1,950
1,536
826
2,362
Percent
71.91%
55.31%
60.52%
49.75%
45.03%
60.12%
42.21%
60.17%
59.24%
50.86%
56.01%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
126
2,546
1,608
1,064
609
2,063
489
2,183
1,741
931
2,672
Percent
70.79%
63.04%
65.58%
60.28%
53.05%
67.22%
50.10%
67.36%
67.14%
57.33%
63.36%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Almost two-thirds of document management contracts were signed
after 2005. One in five contracts (or 20 percent of the contracts)
were signed between 2010 and 2012 (see Table DMEF12). More
than 90 percent of the contracts for electronic forms have been
signed since 2000.
Ta ble DME F12
Document Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
2
42
66
313
576
278
1,277
1,277
1,277
1,277
1,277
1,277
1,277
1,277
0.16%
3.32%
5.22%
24.74%
45.53%
21.98%
100.00%
1
34
39
264
350
219
907
907
907
907
907
907
907
907
0.11%
3.75%
4.30%
29.14%
38.63%
24.17%
100.00%
The document management IT application market has been and
will most likely continue to be impacted by the following forces:
• The need to remove paper from the care delivery and operations
processes to improve hospital efficiency.
• The need to eliminate or significantly reduce paper document
storage and filing processes.
• The need to improve access to information that is still captured
on paper documents and prevent errors that can occur from
having critical documentation stored in two distinct locations.
• The need to make medical record information more secure.
• Compliance with ARRA Meaningful Use criteria, which is
expected to drive more rapid adoption of both document
management and electronic forms management to reduce
dependency on paper and enhance the ability to capture more
discrete data.
▶▶ Nursing Department Environment
HIMSS Analytics monitors seven IT applications in the nursing
department environment used to support the care nurses deliver to
patients. These nursing applications include; electronic medication
administration record (eMAR), infection surveillance system,
medication reconciliation, nurse call system, nurse staffing/
scheduling, nursing documentation and patient acuity.
Of the IT applications tracked in the nursing department, two
applications (nursing documentation and eMAR) present as fairly
universal tools. Three of the applications in this environment (nurse
staffing/scheduling; medication reconciliation; nurse call system)
present as a maturing product market, while infection surveillance
systems and patient acuity reflect a relatively young product market.
From 2011 to 2012, medication reconciliation demonstrated the
highest growth of the various nursing applications (approximately
13 percent), a trajectory consistent with the applications growth
between 2010 and 2011. Infection surveillance systems and nurse
call systems also experienced strong growth trajectories this past
year, each increasing by seven percentage points. All nursing
applications, except nurse staffing/scheduling, reflected an increased
market penetration this past year (see Table NA1).
The purchasers of applications in the nursing IT environment are
most likely to reflect replacement buyers, although this first-time/
replacement buyer mix varies by the application considered (see
Table NA2). For example, at least three-quarters of patient acuity
and nurse call systems purchases are expected to replace existing
systems, whereas slightly more than half of eMAR purchases are
projected to be a replacement purchase.
Ta ble N A1 | Nursing Department Applications
N=4,217
2010
2011
Electronic Medication Administration
Record (eMAR)
72.33%
79.08%
Infection Surveillance Systems
23.22%
29.52%
Medication Reconciliation
36.80%
50.06%
Nurse Call Systems
36.87%
46.72%
Nurse Staffing/Scheduling
64.76%
64.76%
Nursing Documentation
77.64%
82.50%
Patient Acuity
29.07%
30.71%
2012
85.32%
36.92%
62.94%
53.95%
64.06%
87.81%
33.03%
An evaluation of these seven applications by various hospital type
market segments shows the following trends:
• eMAR: the rural hospital segment demonstrated the largest
growth at more than 13 percentage points, followed by growth in
the critical access hospital and single hospital system segments
(see Table NA3). Other hospital segments indicated an increase in
adoption ranging from two to nine percent.
• Infection surveillance systems: for the second year in a row,
academic medical centers showed the highest increase in the use
of infection surveillance systems, at more than 11 percent. The
other segments demonstrated growth of approximately six to
eight percent (see Table NA4).
• Medication reconciliation: the other non-general medical/surgical
hospital segment reflected the highest year-over-year growth at
more than 17 percentage points. The critical access hospital and
rural hospital segments also saw a growth increase registering just
under 17 percentage points. The lowest market penetration growth,
seven percentage points, was among the market segment with the
highest adoption rate, academic medical centers (see Table NA5).
• Nurse call system: three segments (critical access, multi-hospital
system and other non-general medical/surgical hospitals) all
experienced market penetration increases of approximately eight
percentage points. Growth in all other segments ranged between
five and eight percent (see Table NA6).
• Nurse staffing/scheduling: this is the only nursing IT application
to indicate a decrease compared to 2011. Despite the overall
decline, there are areas of growth, including the rural hospital
and critical access hospital segments, each reporting a growth of
more than four percentage points (see Table NA7).
• Nursing documentation: rural hospitals indicated the largest
year-over-year increase of close to 12 percentage points. Growth
among critical access hospitals was nearly 10 percentage points.
All of the other segments reported an increase ranging from two
to nine percentage points (see Table NA6).
• Patient acuity: growth in the critical access hospital and rural
hospital segments was greatest, at approximately five percentage
points. Growth in the other segments ranged from one to four
percentage points (see Table NA7).
Ta ble N A 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Electronic Medication Administration Record (eMAR)
58
51.79%
36
57.14%
48
57.83%
Nurse Call Systems
7
77.78%
13
61.90%
63
63.00%
Patient Acuity
43
84.31%
Replacing = Statuses of Live and Operational, Contracted/Not Yet Installed and Installation In Process
First time = Status of Not Automated
for the First Time
54
27
35
2
8
37
8
for the First Time
48.21%
42.86%
42.17%
22.22%
38.10%
37.00%
15.69%
N = Total Number of
Hospitals Planning
112
63
83
9
21
100
51
Ta ble N A 3 | Electronic Medication Administration Record (eMAR)
2010
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
All
Segment
Count
164
2,886
1,914
1,136
617
2,433
514
2,536
2,035
1,015
3,050
Percent
92.13%
71.45%
78.06%
64.36%
53.75%
79.28%
52.66%
78.25%
78.48%
62.50%
72.33%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
167
3,168
2,061
1,274
756
2,579
634
2,701
2,141
1,194
3,335
Percent
93.82%
78.44%
84.05%
72.18%
65.85%
84.03%
64.96%
83.34%
82.57%
73.52%
79.08%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,426
2,171
1,427
886
2,712
763
2,835
2,230
1,368
3,598
Percent
96.63%
84.82%
88.54%
80.85%
77.18%
88.37%
78.18%
87.47%
86.00%
84.24%
85.32%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
41
▶▶ Nursing Department Environment con tinue d
Ta ble N A 4 | Infection Surveillance System
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
67
912
698
281
139
840
114
865
722
257
979
Percent
37.64%
22.58%
28.47%
15.92%
12.11%
27.37%
11.68%
26.69%
27.84%
15.83%
23.22%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
90
1,155
869
376
192
1,053
153
1,092
884
361
1,245
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
127
1,984
1,366
745
475
1,636
387
1,724
1,289
822
2,111
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
112
1,858
1,295
675
408
1,562
335
1,635
1,277
693
1,970
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
167
2,564
1,888
843
414
2,317
340
2,391
1,888
843
2,731
Percent
50.56%
28.60%
35.44%
21.30%
16.72%
34.31%
15.68%
33.69%
34.09%
22.23%
29.52%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
110
1,447
1,064
493
277
1,280
215
1,342
1,073
484
1,557
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
140
2,514
1,598
1,056
667
1,987
551
2,103
1,596
1,058
2,654
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
126
2,149
1,452
823
464
1,811
387
1,888
1,503
772
2,275
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
168
2,539
1,905
802
462
2,245
388
2,319
1,803
877
2,702
Percent
61.80%
35.83%
43.39%
27.93%
24.13%
41.71%
22.03%
41.41%
41.38%
29.80%
36.92%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble N A5 | Medication Reconciliation
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
101
1,451
1,049
503
311
1,241
254
1,298
1,020
532
1,552
Percent
56.74%
35.92%
42.78%
28.50%
27.09%
40.44%
26.02%
40.05%
39.34%
32.76%
36.80%
2011
Percent
71.35%
49.12%
55.71%
42.21%
41.38%
53.31%
39.65%
53.19%
49.71%
50.62%
50.06%
2012
Percent
78.65%
62.24%
65.17%
59.83%
58.10%
64.74%
56.45%
64.89%
61.55%
65.15%
62.94%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble N A6 | Nurse Call System
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
99
1,456
1,025
530
318
1,237
262
1,293
1,003
552
1,555
Percent
55.62%
36.05%
41.80%
30.03%
27.70%
40.31%
26.84%
39.90%
38.68%
33.99%
36.87%
2011
Percent
62.92%
46.00%
52.81%
38.24%
35.54%
50.90%
34.32%
50.45%
49.25%
42.67%
46.72%
2012
Percent
70.79%
53.21%
59.22%
46.63%
40.42%
59.01%
39.65%
58.25%
57.96%
47.54%
53.95%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble N A7 | Nurse Staffing/Scheduling
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
166
2,565
1,892
839
416
2,315
340
2,391
1,915
816
2,731
Percent
93.26%
63.51%
77.16%
47.54%
36.24%
75.43%
34.84%
73.77%
73.85%
50.25%
64.76%
2011
Percent
93.82%
63.48%
77.00%
47.76%
36.06%
75.50%
34.84%
73.77%
72.81%
51.91%
64.76%
2012
Percent
94.38%
62.86%
77.69%
45.44%
40.24%
73.15%
39.75%
71.55%
69.53%
54.00%
64.06%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble N A 8 | Nursing Documentation
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
170
3,104
2,042
1,232
704
2,570
582
2,692
2,143
1,131
3,274
Percent
95.51%
76.85%
83.28%
69.80%
61.32%
83.74%
59.63%
83.06%
82.65%
69.64%
77.64%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
171
3,308
2,132
1,347
804
2,675
662
2,817
2,229
1,250
3,479
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
87
1,208
852
443
191
1,104
153
1,142
887
408
1,295
Percent
96.07%
81.90%
86.95%
76.32%
70.03%
87.16%
67.83%
86.92%
85.96%
76.97%
82.50%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,528
2,225
1,478
917
2,786
776
2,927
2,315
1,388
3,703
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
92
1,301
881
512
250
1,143
197
1,196
951
442
1,393
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
98.31%
87.35%
90.74%
83.74%
79.88%
90.78%
79.51%
90.31%
89.28%
85.47%
87.81%
Ta ble N A9 | Patient Acuity
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
84
1,142
819
407
161
1,065
134
1,092
854
372
1,226
Percent
47.19%
28.27%
33.40%
23.06%
14.02%
34.70%
13.73%
33.69%
32.93%
22.91%
29.07%
2011
The profile the of nursing IT environment by bed segment from 2011
to 2012 yields the following highlights (see Tables NA10–NA16):
• 0–100 beds: with more than a 17 percentage point difference
between 2012 and 2011, medication reconciliation had the highest
year-over-year growth in this segment. Nurse staffing/scheduling
is the only application to indicate a decrease in this segment, at
approximately one percentage point (see Table NA10).
• 101–200 beds: medication reconciliation had the highest growth
from 2011 to 2012, at close to 12 percentage points, followed by
infection surveillance systems at eight percentage points (see
Table NA11).
• 201–300 beds: infection surveillance systems reported the largest
growth from 2011 to 2012 at more than eight percentage points,
while eMAR indicated a decrease in adoption (see Table NA12).
• 301–400 beds: infection surveillance systems, medication
reconciliation and nurse call systems had the three highest yearover-year growth rates ranging from nearly seven percentage
points to nine percentage points. Growth among the other
applications was approximately one to two percentage points,
with the exception of nurse staffing/scheduling, which showed
no growth (see Table NA13).
• 401–500 beds: at more than 97 percent, eMAR is on the verge
of reaching full market saturation. Medication reconciliation and
infection surveillance systems reported the largest growth at
approximately six percentage points. Nurse staffing/scheduling is
the only application to demonstrate a decrease in adoption at little
more than one percentage point (see Table NA14).
• 501–600: infection surveillance systems is the only nursing IT
application within this segment to indicate a double digit increase
in adoption from 2011 to 2012. Both medication reconciliation
and nurse call systems grew by more than nine percentage points.
The adoption of eMAR remained unchanged from last year (see
Table NA15).
Percent
48.88%
29.91%
34.75%
25.10%
16.64%
35.97%
15.68%
35.24%
34.21%
25.12%
30.71%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
51.69%
32.21%
35.93%
29.01%
21.78%
37.24%
20.18%
36.90%
36.68%
27.22%
33.03%
• Over 600 beds: infection surveillance systems had the largest
growth in this bed segment at close to 11 percentage points. This
is followed by medication reconciliation at more than nine
percentage points. All the other nursing IT applications market
penetrations also grew this year (see Table NA16).
Ta ble N A10
0–100 Beds
Electronic Medication
Administration Record (eMAR)
Nurse Call Systems
Patient Acuity
2010
1,338
336
620
634
982
1,473
424
2011
61.80%
15.52%
28.64%
29.28%
45.36%
68.04%
19.58%
1,544
432
910
826
993
1,622
474
71.32%
19.95%
42.03%
38.15%
45.87%
74.92%
21.89%
2012
1,730
571
1,281
999
970
1,792
548
79.91%
26.37%
59.17%
46.14%
44.80%
82.77%
25.31%
Ta ble N A11
101–200 Beds
Nurse Call Systems
Patient Acuity
2010
624
204
316
345
613
667
279
2011
% of 802 Hospitals
77.81%
25.44%
39.40%
43.02%
76.43%
83.17%
34.79%
651
252
402
426
614
695
286
81.17%
31.42%
50.12%
53.12%
76.56%
86.66%
35.66%
2012
700
317
497
478
615
726
290
87.28%
39.53%
61.97%
59.60%
76.68%
90.52%
36.16%
Ta ble N A12
201–300 Beds
Nurse Call Systems
Patient Acuity
2010
407
150
223
230
425
429
193
2011
% of 483 Hospitals
84.27%
31.06%
46.17%
47.62%
87.99%
88.82%
39.96%
428
200
294
285
417
441
196
88.61%
41.41%
60.87%
59.01%
86.34%
91.30%
40.58%
2012
443
241
317
310
414
452
203
91.72%
49.90%
65.63%
64.18%
85.71%
93.58%
42.03%
43
Ta ble N A13
Ta ble N A17
301–400 Beds
Nurse Call Systems
Patient Acuity
2010
259
105
140
130
288
280
118
83.01%
33.65%
44.87%
41.67%
92.31%
89.74%
37.82%
2011
% of 312 Hospitals
280
128
186
168
288
287
124
89.74%
41.03%
59.62%
53.85%
92.31%
91.99%
39.74%
2012
286
156
208
189
288
291
130
91.67%
50.00%
66.67%
60.58%
92.31%
93.27%
41.67%
Ta ble N A14
401–500 Beds
Nurse Call Systems
Patient Acuity
2010
177
76
108
84
173
171
92
94.15%
40.43%
57.45%
44.68%
92.02%
90.96%
48.94%
2011
% of 188 Hospitals
181
91
135
105
169
177
91
96.28%
48.40%
71.81%
55.85%
89.89%
94.15%
48.40%
2012
183
102
142
116
166
180
92
97.34%
54.26%
75.53%
61.70%
88.30%
95.74%
48.94%
Ta ble N A15
501–600 Beds
Nurse Call Systems
Patient Acuity
2010
109
46
66
57
108
112
49
93.97%
39.66%
56.90%
49.14%
93.10%
96.55%
42.24%
2011
% of 116 Hospitals
111
53
77
66
108
112
51
95.69%
45.69%
66.38%
56.90%
93.10%
96.55%
43.97%
2012
111
65
88
77
110
113
53
95.69%
56.03%
75.86%
66.38%
94.83%
97.41%
45.69%
Ta ble N A16
Over 600 beds
Nurse Call Systems
Patient Acuity
2010
136
62
79
75
142
142
71
90.07%
41.06%
52.32%
49.67%
94.04%
94.04%
47.02%
2011
% of 151 Hospitals
140
89
107
94
142
145
73
92.72%
58.94%
70.86%
62.25%
94.04%
96.03%
48.34%
2012
145
105
121
106
144
149
77
96.03%
69.54%
80.13%
70.20%
95.36%
98.68%
50.99%
An evaluation of the contract purchasing time frames for these
nursing applications reveals that approximately half of infection
surveillance systems, medication reconciliation systems and nurse
call systems were signed between 2010 and 2012. Approximately
one-quarter of the contracts for eMAR and nursing documentation
were signed also within this time frame (see Tables NA17–NA19).
# for Contract
Range
Prior to 1990
3
1990 to 1994
99
1995 to 1999
80
2000 to 2004
568
2005 to 2009
840
2010 to 2012
568
Total
2,158
Infection Surveillance System
Prior to 1990
0
1990 to 1994
4
1995 to 1999
10
2000 to 2004
58
2005 to 2009
160
2010 to 2012
206
Total
438
Prior to 1990
4
1990 to 1994
8
1995 to 1999
39
2000 to 2004
121
2005 to 2009
339
2010 to 2012
522
Total
1,033
Total
Responding
% of Total
Responding
2,158
2,158
2,158
2,158
2,158
2,158
2,158
0.14%
4.59%
3.71%
26.32%
38.92%
26.32%
100.00%
438
438
438
438
438
438
438
0.00%
0.91%
2.28%
13.24%
36.53%
47.03%
100.00%
1,033
1,033
1,033
1,033
1,033
1,033
1,033
0.39%
0.77%
3.78%
11.71%
32.82%
50.53%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
2
2
13
24
94
113
248
248
248
248
248
248
248
248
0.81%
0.81%
5.24%
9.68%
37.90%
45.56%
100.00%
89
87
196
348
496
230
1,446
1,446
1,446
1,446
1,446
1,446
1,446
1,446
6.15%
6.02%
13.55%
24.07%
34.30%
15.91%
100.00%
8
119
149
694
765
538
2,273
2,273
2,273
2,273
2,273
2,273
2,273
2,273
0.35%
5.24%
6.56%
30.53%
33.66%
23.67%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
5
21
41
286
259
145
757
757
757
757
757
757
757
757
0.66%
2.77%
5.42%
37.78%
34.21%
19.15%
100.00%
Ta ble N A18
Nurse Call System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Ta ble N A19
2012
Patient Acuity
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
The nursing application IT application market has been and will
continue to be impacted by:
• Quality outcomes and performance improvement initiatives.
• Pressures to improve patient safety and eliminate medical errors.
• Intense competition for limited capital for purchasing nursing
IT solutions.
• In this competition, nursing documentation purchases should fare
better than most other applications, since they include functions
deemed essential for hospitals to meet the ARRA Meaningful
Use criteria, measurements and reporting requirements.
• These systems, especially nursing documentation and eMAR, have
proven to be nurse satisfiers, thus aid in recruiting and retention.
• The need to create an effective support foundation for
computerized practitioner order entry (CPOE) as most hospitals
implement nursing documentation before CPOE.
• The need to effectively and efficiently determine nurse staffing
levels and assignments to meet minimum staffing requirements
and help reduce the impact of the nursing shortage.
• The need to couple eMAR applications with pharmacy
management and dispensing solutions to facilitate the closed-loop
medication administration process for improving patient
safety—a requirement that will support the medication safety
requirements of Stage 2 Meaningful Use.
▶▶ Ancillary Department Environment
The applications in the ancillary department support key clinical
departments and services in hospitals. HIMSS Analytics monitors
the following eight applications in this environment: cardiology
information system, emergency department systems (ED), intensive
care (ICU), laboratory information system, obstetrical system (OB),
pharmacy management system, radiology information system and
respiratory care information system.
The majority of the planned purchasing for this market in this next
year will be replacements purchases (see Table AD2). ED is the only
ancillary application to indicate that fewer than 80 percent of
planned purchase will be replacements. As in previous years, the
requirement for a tight data coupling with pharmacy systems and
CPOE systems is driving the replacement of legacy pharmacy
systems with the organization’s EMR vendor’s pharmacy system.
The market penetration of the applications in the ancillary department
varies. Laboratory, pharmacy, and radiology for example, have almost
reached complete saturation, while cardiology reflected the lowest
level of adoption at 47 percent (not too surprising as not all hospitals
have cardiology specific or heart centers). Respiratory had the highest
year-over-year level of adoption from 2011 to 2012, with more than a
six percentage point increase. At nearly five percentage points, there
was also a substantial growth in the ED area. All other ancillary
applications have reported an increase from the previous year (see
Table AD1).
Integration requirements between R-PACS and radiology systems is
driving replacement purchases for radiology information systems,
while replacement purchases for laboratory systems is being driven
by the need for laboratories to function as both hospital laboratories
and as reference laboratories for their local and/or regional markets.
In addition, as Meaningful Use requirements evolve, hospital
laboratories will be required to integrate laboratory results
associated with their own external reference labs into the EMRs of
their hospital patients and those of providers for whom they act as a
reference laboratory. High volumes of molecular biologic testing
(e.g., genetic and proteomic testing) may also induce laboratories to
evaluate replacing their current systems if current vendors do not
support these testing environments. Some laboratory replacements
are beginning to occur where niche laboratory vendors are being
replaced by an enterprise wide clinical vendor.
Ta ble A D1 | Ancillary Departments
N=4,217
2010
2011
Cardiology Information Systems
43.04%
45.34%
Emergency Department Systems
72.66%
77.21%
Intensive Care
50.46%
53.09%
Laboratory Information Systems
97.51%
98.32%
Obstetrical Systems (Labor and Delivery)
48.26%
50.58%
Pharmacy Management Systems
94.66%
95.97%
Radiology Information Systems
93.98%
94.88%
Respiratory Care Information Systems
43.49%
49.77%
2012
46.72%
81.91%
56.56%
98.86%
52.79%
97.11%
96.47%
55.96%
An evaluation of hospital type market segments for each ancillary
department system from 2011 to 2012 shows the following:
• Cardiology information systems: most of the segments reported
growth of two percentage points or less. The exception being
the academic medical center segment which reported no growth
from 2011 to 2012 (see Table AD3).
Ta ble A D2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
41
82.00%
57
66.28%
Intensive Care
32
84.21%
94
92.16%
13
86.67%
71
89.87%
83
88.30%
Respiratory Care Information Systems
41
80.39%
for the First Time
9
29
6
8
2
8
11
10
for the First Time
18.00%
33.72%
15.79%
7.84%
13.33%
10.13%
11.70%
19.61%
N = Total Number of
Hospitals Planning
50
86
38
102
15
79
94
51
45
▶▶ Ancillary Department Environment con tinue d
• Emergency department information systems: the rural and critical
access hospital segments demonstrated growth of more than
10 percentage points, while academic medical centers reported
a decline of less than one percentage point (see Table AD4).
• Intensive care systems: from 2011 to 2012, the general medical/
surgical, rural and single hospital segments all reported growth
of more than four percentage points. All other segments reported
growth of two to four percentage points (see Table AD5).
• Laboratory information systems: since this application is near
market saturation across all market segments, there was little
growth. The critical access hospital segment had the largest
growth at less than two percentage points. The academic medical
center segment has reached full market segmentation and there
was no growth from 2011 to 2012 (see Table AD6).
• Obstetrical systems: market penetration in 2012 is 60 percent or
more for the academic medical center, general medical/surgical,
non-critical access hospital and urban hospitals. All segments
reported growth from 2011 to 2012 ranging from one to nearly
four percentage points (see Table AD7).
• Pharmacy management systems: the academic medical center
segment, which is fully saturated, demonstrated no growth in the
past year. Growth in all other hospital segments ranged from less
than one percentage point to more than four percentage points.
Rural hospitals demonstrated the largest year-over-year growth
(see Table AD8).
• Radiology information systems: the critical access hospital and
rural hospital segments reported more than four percentage point
growth from 2011 to 2012 (see Table AD9).
• Respiratory care information systems: growth of five to eight
percentage points was reported across all segments with critical
access hospitals reporting the largest increase at eight percentage
points (see Table AD10).
Ta ble A D3 | Cardiology Information Systems
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
157
1,658
1,482
333
97
1,718
78
1,737
1,286
529
1,815
Percent
88.20%
41.05%
60.44%
18.87%
8.45%
55.98%
7.99%
53.59%
49.60%
32.57%
43.04%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
158
1,754
1,558
354
118
1,794
91
1,821
1,323
589
1,912
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
173
3,083
2,246
1,010
742
2,514
646
2,610
2,047
1,209
3,256
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
154
2,085
1,628
611
276
1,963
231
2,008
1,512
727
2,239
Percent
88.76%
43.43%
63.54%
20.06%
10.28%
58.46%
9.32%
56.19%
51.02%
36.27%
45.34%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
158
1,812
1,601
369
137
1,833
111
1,859
1,348
622
1,970
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
3,282
2,317
1,137
863
2,591
749
2,705
2,104
1,350
3,454
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
159
2,226
1,739
646
307
2,078
272
2,113
1,590
795
2,385
Percent
88.76%
44.86%
65.29%
20.91%
11.93%
59.73%
11.37%
57.36%
51.99%
38.30%
46.72%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D 4 | Emergency Department Systems
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
171
2,893
2,171
893
630
2,434
544
2,520
1,993
1,071
3,064
Percent
96.07%
71.63%
88.54%
50.59%
54.88%
79.31%
55.74%
77.75%
76.86%
65.95%
72.66%
2011
Percent
97.19%
76.33%
91.60%
57.22%
64.63%
81.92%
66.19%
80.53%
78.94%
74.45%
77.21%
2012
Percent
96.63%
81.26%
94.49%
64.42%
75.17%
84.42%
76.74%
83.46%
81.14%
83.13%
81.91%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D5 | Intensive Care
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
146
1,982
1,535
593
266
1,862
215
1,913
1,465
663
2,128
Percent
82.02%
49.07%
62.60%
33.60%
23.17%
60.67%
22.03%
59.02%
56.50%
40.83%
50.46%
2011
Percent
86.52%
51.62%
66.39%
34.62%
24.04%
63.96%
23.67%
61.96%
58.31%
44.77%
53.09%
2012
Percent
89.33%
55.11%
70.92%
36.60%
26.74%
67.71%
27.87%
65.20%
61.32%
48.95%
56.56%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D6 | Laboratory Information System
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
178
3,934
2,443
1,669
1,074
3,038
920
3,192
2,550
1,562
4,112
Percent
100.00%
97.40%
99.63%
94.56%
93.55%
98.99%
94.26%
98.49%
98.34%
96.18%
97.51%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,968
2,445
1,701
1,096
3,050
933
3,213
2,569
1,577
4,146
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
144
1,989
1,694
439
263
1,870
244
1,889
1,388
745
2,133
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,869
2,442
1,605
1,001
3,046
850
3,197
2,549
1,498
4,047
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,823
2,424
1,577
1,002
2,999
855
3,146
2,504
1,497
4,001
Percent
100.00%
98.24%
99.71%
96.37%
95.47%
99.38%
95.59%
99.14%
99.07%
97.11%
98.32%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,991
2,447
1,722
1,113
3,056
945
3,224
2,576
1,593
4,169
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
146
2,080
1,748
478
299
1,927
275
1,951
1,419
807
2,226
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,917
2,444
1,651
1,045
3,050
890
3,205
2,553
1,542
4,095
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,891
2,435
1,633
1,049
3,019
894
3,174
2,526
1,542
4,068
Percent
100.00%
98.81%
99.80%
97.56%
96.95%
99.58%
96.82%
99.48%
99.34%
98.09%
98.86%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D7 | Obstetrical Systems (Labor and Delivery)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
141
1,894
1,630
405
231
1,804
202
1,833
1,358
677
2,035
Percent
79.21%
46.89%
66.48%
22.95%
20.12%
58.78%
20.70%
56.56%
52.37%
41.69%
48.26%
2011
Percent
80.90%
49.24%
69.09%
24.87%
22.91%
60.93%
25.00%
58.28%
53.53%
45.87%
50.58%
2012
Percent
82.02%
51.50%
71.29%
27.08%
26.05%
62.79%
28.18%
60.20%
54.72%
49.69%
52.79%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D8 | Pharmacy Management System
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
178
3,814
2,438
1,554
963
3,029
818
3,174
2,530
1,462
3,992
Percent
100.00%
94.43%
99.43%
88.05%
83.89%
98.70%
83.81%
97.93%
97.57%
90.02%
94.66%
2011
Percent
100.00%
95.79%
99.59%
90.93%
87.20%
99.25%
87.09%
98.64%
98.30%
92.24%
95.97%
2012
Percent
100.00%
96.98%
99.67%
93.54%
91.03%
99.38%
91.19%
98.89%
98.46%
94.95%
97.11%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble A D9 | Radiology Information System
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
178
3,785
2,416
1,547
969
2,994
825
3,138
2,503
1,460
3,963
Percent
100.00%
93.71%
98.53%
87.65%
84.41%
97.56%
84.53%
96.82%
96.53%
89.90%
93.98%
2011
Percent
100.00%
94.65%
98.86%
89.35%
87.28%
97.72%
87.60%
97.07%
96.57%
92.18%
94.88%
2012
Percent
99.44%
96.34%
99.31%
92.52%
91.38%
98.37%
91.60%
97.93%
97.42%
94.95%
96.47%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
47
Ta ble A D10 | Respiratory Care Information System
2010
Segment
Count
109
1,725
1,261
573
302
1,532
253
1,581
1,202
632
1,834
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Percent
61.24%
42.71%
51.43%
32.46%
26.31%
49.92%
25.92%
48.78%
46.36%
38.92%
43.49%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
The analysis of the ancillary market by bed size from 2010–2012
is exhibited in Tables AD11–AD17. In evaluating the bed segments,
the data indicates:
• 0–100 beds: ED demonstrated the highest growth within this
segment at more than seven percentage points. There was also
growth of nearly seven percentage points in the respiratory care
market (see Table AD11).
• 101–200 beds: the largest year-over-year growth was respiratory
care at six percentage points. Almost all other ancillary
applications indicated growth ranging from less than one to
four percentage points (see Table AD12).
• 201–300 beds: respiratory reported the highest growth at more than
five percentage points. Laboratory and pharmacy, which are fully
saturated, indicated no growth. Radiology is the only application
within this segment to report a decline (see Table AD13).
• 301–400 beds: four of the eight applications reported growth from
2011 to 2012; ranging from one to five percentage points. Laboratory,
OB, pharmacy and radiology, which are all at or near market
saturation, reported no growth from last year (see Table AD14).
• 401–500 beds: respiratory care indicated a growth of nearly six
percentage points. ICU, OB and cardiology also reported positive
growth. All other applications are at or approaching market segmentation and indicated no growth in the past year (see Table AD15).
• 501–600 beds: respiratory systems demonstrated a six percentage
point increase from 2011 to 2012. Having already achieved
market saturation, laboratory, pharmacy, radiology are the only
ancillary applications to remain the same compared to last year
(see Table AD16).
• Over 600 beds: respiratory care and ICU reported an increase of
more than three percentage points from 2011 to 2012. Cardiology
is the only ancillary application to indicate a decline in adoption
level from 2011 (see Table AD17).
Ta ble A D11
0–100 Beds
Intensive Care
Obstetrical Systems
(Labor and Delivery)
Respiratory Care
Information Systems
2010
2011
2012
348 16.07%
384 17.74%
1,355 62.59% 1,518 70.12%
746 34.46%
816 37.69%
2,094 96.72% 2,117 97.78%
308
1,201
712
2,061
14.23%
55.47%
32.89%
95.20%
572
1,941
1,922
26.42%
89.65%
88.78%
627
1,996
1,960
28.96%
92.19%
90.53%
677
2,043
2,024
31.27%
94.36%
93.49%
688
31.78%
849
39.21%
999
46.14%
Segment
Count
114
1,985
1,418
681
396
1,703
332
1,767
1,345
754
2,099
Percent
64.04%
49.15%
57.83%
38.58%
34.49%
55.49%
34.02%
54.52%
51.87%
46.43%
49.77%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
126
2,234
1,572
788
487
1,873
407
1,953
1,491
869
2,360
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
70.79%
55.31%
64.11%
44.65%
42.42%
61.03%
41.70%
60.26%
57.50%
53.51%
55.96%
Ta ble A D12
101–200 Beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
2011
% of 802 Hospitals
520 64.84%
709 88.40%
538 67.08%
802 100.00%
2012
491
690
512
801
61.22%
86.03%
63.84%
99.88%
527 65.71%
730 91.02%
568 70.82%
802 100.00%
523
801
792
65.21%
99.88%
98.75%
541
801
793
67.46%
99.88%
98.88%
564 70.32%
802 100.00%
797 99.38%
410
51.12%
455
56.73%
500
62.34%
Ta ble A D13
201–300 Beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
360 74.53%
452 93.58%
337 69.77%
483 100.00%
2011
% of 483 Hospitals
378 78.26%
459 95.03%
360 74.53%
483 100.00%
382 79.09%
469 97.10%
385 79.71%
483 100.00%
331 68.53%
483 100.00%
483 100.00%
348 72.05%
483 100.00%
482 99.79%
362 74.95%
483 100.00%
481 99.59%
271
290
316
56.11%
60.04%
2012
65.42%
Ta ble A D14
301–400 Beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
253 81.09%
286 91.67%
208 66.67%
312 100.00%
2011
% of 312 Hospitals
255 81.73%
292 93.59%
220 70.51%
312 100.00%
264 84.62%
295 94.55%
227 72.76%
312 100.00%
236 75.64%
312 100.00%
311 99.68%
241 77.24%
312 100.00%
311 99.68%
241 77.24%
312 100.00%
311 99.68%
170
187
203
54.49%
59.94%
2012
65.06%
Ta ble A D15
401–500 Beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
165 87.77%
179 95.21%
141 75.00%
188 100.00%
2011
% of 188 Hospitals
166 88.30%
183 97.34%
143 76.06%
188 100.00%
168 89.36%
183 97.34%
150 79.79%
188 100.00%
149 79.26%
188 100.00%
188 100.00%
150 79.79%
188 100.00%
188 100.00%
153 81.38%
188 100.00%
188 100.00%
120
130
141
63.83%
69.15%
2012
75.00%
Ta ble A D16
Ta ble A D19
501–600 Beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
98 84.48%
107 92.24%
95 81.90%
116 100.00%
2011
% of 116 Hospitals
101 87.07%
107 92.24%
99 85.34%
116 100.00%
96 82.76%
116 100.00%
116 100.00%
69
96 82.76%
116 100.00%
116 100.00%
59.48%
74
63.79%
2012
102 87.93%
108 93.10%
101 87.07%
116 100.00%
98 84.48%
116 100.00%
116 100.00%
81
69.83%
Ta ble A D17
Over 600 beds
Intensive Care
Obstetrical Systems
Respiratory Care
Information Systems
2010
140 92.72%
149 98.68%
123 81.46%
151 100.00%
2011
% of 151 Hospitals
144 95.36%
151 100.00%
133 88.08%
151 100.00%
143 94.70%
151 100.00%
138 91.39%
151 100.00%
128 84.77%
151 100.00%
151 100.00%
130 86.09%
151 100.00%
151 100.00%
131 86.75%
151 100.00%
151 100.00%
106
114
120
70.20%
75.50%
2012
79.47%
An evaluation of contract purchasing time frames for ancillary
department applications reveals that more than 20 percent
of contracts purchased for respiratory, OB and ED were made
between 2010 to 2012 (see Tables AD18–AD20). For the other
ancillary applications, more than 15 to 20 percent of the contracts
were signed in the same time frame. This could indicate that
replacement purchases are being made, particularly in the
laboratory, radiology and pharmacy markets in favor of a onevendor integrated systems approach. Ancillary department systems
contracted before 1995 will have the highest probability for
replacement purchases through 2015.
Ta ble A D18
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Intensive Care
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
5
16
56
274
340
162
853
853
853
853
853
853
853
853
0.60%
1.92%
6.73%
32.93%
40.87%
19.47%
100.00%
9
43
129
634
672
558
2,045
2,045
2,045
2,045
2,045
2,045
2,045
2,045
0.44%
2.11%
6.32%
31.08%
32.94%
27.35%
100.00%
6
117
132
483
478
282
1,498
1,498
1,498
1,498
1,498
1,498
1,498
1,498
0.40%
7.84%
8.84%
32.35%
32.02%
18.89%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
121
225
512
677
617
369
2,521
2,521
2,521
2,521
2,521
2,521
2,521
2,521
4.80%
8.93%
20.31%
26.85%
24.47%
14.64%
100.00%
0
29
95
326
301
227
978
978
978
978
978
978
978
978
0.00%
2.97%
9.71%
33.33%
30.78%
23.21%
100.00%
28
195
343
888
771
512
2,737
2,737
2,737
2,737
2,737
2,737
2,737
2,737
1.02%
7.12%
12.53%
32.44%
28.17%
18.71%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
42
136
297
817
860
469
2,621
2,621
2,621
2,621
2,621
2,621
2,621
2,621
1.60%
5.20%
11.35%
31.22%
32.86%
17.92%
100.00%
9
116
108
394
418
336
1,381
1,381
1,381
1,381
1,381
1,381
1,381
1,381
0.65%
8.42%
7.84%
28.61%
30.36%
24.40%
100.00%
Laboratory Information System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Obstetrical System (Labor and Delivery)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Pharmacy Management System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Ta ble A D20
Radiology Information System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Respiratory Care Information System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
The ancillary department IT application market has been and will
most likely continue to be impacted by the following market forces:
• The need to reduce or eliminate medical and medication errors.
• The continued hospital focus on patient safety.
• The need to capture more clinical data electronically to support
Meaningful Use, HIE and personal health record (PHR)
initiatives.
• The continued drive towards integrated clinical systems and away
from “best of breed” will drive some replacement purchases of
essentially stand-alone ancillary systems.
• The need to have CPOE systems tightly coupled with pharmacy
systems.
• The need to have pharmacy systems tightly coupled with eMAR
systems.
• The push by the government for pay for performance and the
continued need of hospitals to have discrete data with which to
report against ARRA Meaningful Use criteria by 2011 and beyond.
49
• The need to have complete clinical transaction data for C&BI
analytics for quality and efficiency improvements.
• The need to create improved data sharing/integration between
clinical and financial systems to support improved claims
processing accuracy and for performance analysis and reporting
under bundled payment contracts.
• Intense competition for limited capital funds in a period when
government-mandated initiatives will determine the applications
that receive the highest priority.
• The push by the government to improve the capture,
management, and sharing of electronic health information in
summary data formats between all healthcare stakeholders.
• The need to provide a higher level of integration of order
communications and results reporting with external providers
and reference laboratories.
• Complex molecular and genomics testing in laboratories to
deliver “personalized medicine.”
▶▶ Laboratory Environment
The applications that are part of the laboratory environment
include anatomical pathology, blood bank, laboratory-molecular
diagnostics, laboratory-outreach services and microbiology.
These solutions focus on providing automation and efficiency in
laboratory operations. Although general laboratory information
system solutions could also be considered to be a part of this
environment, this solution has historically appeared in the ancillary
section of the HIMSS Analytics Annual Report. At least for 2012,
general laboratory information systems will continue to be included
in the ancillary environment section of this report.
Microbiology had the highest market penetration in 2012 at 80
percent; followed by blood bank (68 percent) and anatomical
pathology (62 percent). Laboratory-molecular diagnostics has
the lowest rate of adoption at just under 15 percent. Between 2011
and 2012, laboratory-outreach services demonstrated the largest
year-over-year growth at approximately four percentage points
(see Table LAB1).
The majority of future purchases in the laboratory environment
are expected to be replacement purchases. While the laboratorymolecular diagnostics application is evenly split between first time
Ta ble L A B1 | Laboratory
N=4,217
2010
2011
2012
Anatomical Pathology
58.88%
59.24%
62.01%
Blood Bank
67.61%
67.44%
67.77%
Laboratory–Molecular Diagnostics
11.43%
13.45%
14.75%
Laboratory–Outreach Services
21.15%
26.08%
30.31%
Microbiology
77.31%
79.23%
80.72%
NOTE: installed does not necessarily indicate full usage across all patient units or by all
categories of clinician
and replacement purchase plans, this data needs to be evaluated
with caution, as only two hospitals reported plans to purchase this
technology (see Table LAB2).
An evaluation of this environment from 2011 to 2012 by hospital
type shows the highest growth by application occurred as follows:
• Anatomical pathology: the greatest growth was demonstrated
in the critical access hospital segment at more than five
percentage points. The rural, non-medical/surgical and multihospital system segments each had growth more than three
percentage points. The academic medical center segment is
saturated with 99 percent market adoption (see Table LAB3).
• Blood Bank: at just over one percentage point, the multi-hospital
system segment had the greatest growth. The rural and single
hospital segments saw a decrease in adoption of just more
than one percentage point. While displaying a slight decrease,
the academic medical center segment is still saturated, with
98 percent adoption (see Table LAB4).
• Laboratory-Molecular Diagnostics: adoption of this technology
grew more than two percentage points in the academic medical
center segment from 2011 to 2012. Growth in the remaining market
segments was less than two percentage points (see Table LAB5).
• Laboratory-Outreach Services: the academic medical center
segment reported the highest increase in adoption over the past
year at nearly seven percentage points. The remaining segments
grew between three to five percentage points (see Table LAB6).
• Microbiology: both the rural hospital and the critical access segments
showed growth at more than three percentage points. Academic
medical centers have almost reached full market penetration (99
percent adoption), while general medical/surgical hospitals are
approaching saturation at 94 percent adoption (see Table LAB7).
Ta ble L A B2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
39
95.12%
Blood Bank
44
77.19%
1
50.00%
28
90.32%
Microbiology
48
94.12%
for the First Time
2
13
1
3
3
for the First Time
4.88%
22.81%
50.00%
9.68%
5.88%
N = Total Number of
Hospitals Planning
41
57
2
31
51
▶▶ Laboratory Environment con tinued
Ta ble L A B 3 | Anatomical Pathology
2010
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
177
2,306
1,884
599
271
2,212
229
2,254
1,728
755
2,483
Percent
99.44%
57.09%
76.84%
33.94%
23.61%
72.08%
23.46%
69.55%
66.64%
46.49%
58.88%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
2,323
1,882
616
294
2,204
244
2,254
1,713
785
2,498
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
2,669
2,084
760
423
2,421
357
2,487
1,956
888
2,844
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
80
487
399
168
43
524
34
533
438
129
567
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
88
1,012
793
307
130
970
94
1,006
784
316
1,100
Percent
98.31%
57.51%
76.75%
34.90%
25.61%
71.81%
25.00%
69.55%
66.06%
48.34%
59.24%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
2,439
1,936
679
353
2,262
281
2,334
1,804
811
2,615
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
174
2,684
2,106
752
417
2,441
344
2,514
1,989
869
2,858
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
84
538
439
183
48
574
36
586
483
139
622
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
100
1,178
914
364
169
1,109
126
1,152
917
361
1,278
Percent
98.88%
60.39%
78.96%
38.47%
30.75%
73.70%
28.79%
72.01%
69.57%
49.94%
62.01%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble L A B4 | Blood Bank
2010
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
176
2,675
2,106
745
401
2,450
341
2,510
1,978
873
2,851
Percent
98.88%
66.23%
85.89%
42.21%
34.93%
79.83%
34.94%
77.45%
76.28%
53.76%
67.61%
2011
Percent
98.31%
66.08%
84.99%
43.06%
36.85%
78.89%
36.58%
76.74%
75.43%
54.68%
67.44%
2012
Percent
97.75%
66.45%
85.89%
42.61%
36.32%
79.54%
35.25%
77.57%
76.71%
53.51%
67.77%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble L A B5 | Laboratory–Molecular Diagnostics
2010
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
71
411
347
135
25
457
21
461
374
108
482
Percent
39.89%
10.18%
14.15%
7.65%
2.18%
14.89%
2.15%
14.22%
14.42%
6.65%
11.43%
2011
Percent
44.94%
12.06%
16.27%
9.52%
3.75%
17.07%
3.48%
16.45%
16.89%
7.94%
13.45%
2012
Percent
47.19%
13.32%
17.90%
10.37%
4.18%
18.70%
3.69%
18.08%
18.63%
8.56%
14.75%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble L A B6 | Laboratory–Outreach Services
2010
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
76
816
657
235
87
805
61
831
629
263
892
Percent
42.70%
20.20%
26.79%
13.31%
7.58%
26.23%
6.25%
25.64%
24.26%
16.19%
21.15%
2011
Percent
49.44%
25.06%
32.34%
17.39%
11.32%
31.61%
9.63%
31.04%
30.24%
19.46%
26.08%
2012
Percent
56.18%
29.17%
37.28%
20.62%
14.72%
36.14%
12.91%
35.54%
35.36%
22.23%
30.31%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
51
Ta ble L A B7 | Microbiology
2010
Segment
Count
174
3,086
2,258
1,002
563
2,697
487
2,773
2,152
1,108
3,260
Type
Academic/Teaching
Not Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Percent
97.75%
76.41%
92.09%
56.77%
49.04%
87.88%
49.90%
85.56%
82.99%
68.23%
77.31%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Microbiology is reaching market saturation (more than 94 percent)
in each bed segment except the 0–100 bed segment. Additional
analysis of the laboratory market by bed size in 2012 indicates the
following (see Tables LAB8–LAB14):
• 0–100 beds: anatomical pathology showed the highest growth at
four percentage points, followed by laboratory-outreach services
at slightly more than three percentage points (see Table LAB8).
• 101–200 beds: laboratory-outreach services demonstrated the
highest growth at nearly five percentage points. Anatomical
pathology, laboratory-molecular diagnostics and blood bank
each grew by one to two percentage points (see Table LAB9).
• 201–300 beds: the greatest growth in this segment was for
laboratory-outreach services at close to five percentage points,
followed by laboratory-molecular diagnostics at nearly two
percentage points (see Table LAB10).
• 301–400 beds: laboratory-outreach services and anatomical
pathology each grew by more than two percentage points
between 2011 and 2012 (see Table LAB11).
• 401–500 beds: the greatest growth in this segment was for
laboratory-outreach services, which demonstrated an eight
percentage point growth. Microbiology’s market penetration was
unchanged from last year and the remaining applications grew
by less than one percentage point (see Table LAB12).
• 501–600 beds: anatomical pathology, blood bank and
microbiology reached near complete market saturation (more
than 95 percent) in 2011 and saw little to no change in 2012.
Laboratory-outreach services showed a six percentage point
growth since last year (see Table LAB13).
• Over 600 beds: the greatest growth was for laboratory-outreach
services at six percentage points. Blood bank and laboratorymolecular diagnostics each grew by slightly more than one
percentage point from 2011 to 2012 (see Table LAB14).
Ta ble L A B8
0–100 Beds
Blood Bank
Laboratory–Molecular
Diagnostics
Microbiology
2010
716
946
85
238
1,280
2011
2012
33.07%
734 33.90%
819 37.83%
43.70%
963 44.48%
963 44.48%
3.93%
10.99%
59.12%
119
331
1,356
5.50%
15.29%
62.63%
141
406
1,416
6.51%
18.75%
65.40%
Segment
Count
175
3,166
2,282
1,059
609
2,732
530
2,811
2,183
1,158
3,341
Percent
98.31%
78.39%
93.07%
60.00%
53.05%
89.02%
54.30%
86.73%
84.19%
71.31%
79.23%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,228
2,300
1,104
649
2,755
568
2,836
2,210
1,194
3,404
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
98.88%
79.92%
93.80%
62.55%
56.53%
89.77%
58.20%
87.50%
85.23%
73.52%
80.72%
Ta ble L A B9
101–200 Beds
Blood Bank
Diagnostics
Microbiology
2010
612
699
2011
% of 802 Hospitals
76.31%
607 75.69%
87.16%
682 85.04%
625
690
77.93%
86.03%
111
193
756
13.84%
24.06%
94.26%
134
263
759
16.71%
32.79%
94.64%
118
223
757
14.71%
27.81%
94.39%
2012
Ta ble L A B10
201–300 Beds
Blood Bank
Diagnostics
Microbiology
2010
432
460
2011
% of 483 Hospitals
89.44%
437 90.48%
95.24%
458 94.82%
441
460
91.30%
95.24%
72
150
472
14.91%
31.06%
97.72%
91
202
473
18.84%
41.82%
97.93%
83
179
472
17.18%
37.06%
97.72%
2012
Ta ble L A B11
301–400 Beds
Blood Bank
Diagnostics
Microbiology
2010
288
306
2011
% of 312 Hospitals
92.31%
286 91.67%
98.08%
300 96.15%
294
301
94.23%
96.47%
73
114
305
23.40%
36.54%
97.76%
86
148
306
27.56%
47.44%
98.08%
81
139
307
25.96%
44.55%
98.40%
2012
Ta ble L A B12
401–500 Beds
Blood Bank
Diagnostics
Microbiology
2010
174
181
2011
% of 188 Hospitals
92.55%
173 92.02%
96.28%
182 96.81%
174
183
92.55%
97.34%
42
74
186
22.34%
39.36%
98.94%
53
98
187
28.19%
52.13%
99.47%
52
83
187
27.66%
44.15%
99.47%
2012
Ta ble L A B13
501–600 Beds
Blood Bank
Diagnostics
Microbiology
2010
113
114
2011
% of 116 Hospitals
97.41%
113 97.41%
98.28%
114 98.28%
114
114
98.28%
98.28%
31
46
113
26.72%
39.66%
97.41%
35
61
113
30.17%
52.59%
97.41%
34
54
113
29.31%
46.55%
97.41%
2012
Ta ble L A B14
Ta ble L A B15
Over 600 beds
Blood Bank
Diagnostics
Microbiology
2010
148
145
2011
% of 151 Hospitals
98.01%
148 98.01%
96.03%
145 96.03%
148
147
98.01%
97.35%
68
77
148
45.03%
50.99%
98.01%
82
100
150
54.30%
66.23%
99.34%
80
91
149
52.98%
60.26%
98.68%
2012
More than half of all the contracting for anatomical pathology,
blood bank and microbiology took place before 2005, while more
than half of the contracting for laboratory-molecular diagnostics and
laboratory-outreach services took place during 2005 to 2012 (see
Tables LAB15–LAB16).
The laboratory environment market has been or will likely be
• An increased focus on complying with ARRA Meaningful Use
process and reporting criteria in order to qualify for EMR
adoption incentives and avoid Medicare reimbursement penalties.
• Increased pressures on hospitals by federal and state authorities to
participate in HIE and public health reporting activities for disease
indexes and syndromic reporting.
• An increased use of laboratory components from the enterprise
clinical systems vendor and a general movement away from
niche vendors.
• Intense competition for capital funding, and staff resources
between financial (e.g. ICD-10 coding mandate and payment
reform) and clinical (e.g. ARRA Meaningful Use measurements)
IT projects.
• Accelerated mergers and acquisitions in the provider market which
will drive some laboratory and pathology service consolidation.
• With increased mergers and the continued growth of IDNs there
will be an increase in demand from the medical staff for leading
edge molecular diagnostics capabilities to develop a personalized
medicine program.
• Tight capital markets may continue to impact the acquisition
and installation of EMR products through 2015, especially for
small community and critical access hospitals, in spite of the
availability of ARRA incentives.
• The increased need to acquire, manage, and analyze clinical data for
business intelligence, outcomes improvement, pay for performance
incentive programs and government compliance reporting.
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Blood Bank
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
38
117
234
445
333
193
1,360
1,360
1,360
1,360
1,360
1,360
1,360
1,360
2.79%
8.60%
17.21%
32.72%
24.49%
14.19%
100.00%
63
137
211
383
437
205
1,436
1,436
1,436
1,436
1,436
1,436
1,436
1,436
4.39%
9.54%
14.69%
26.67%
30.43%
14.28%
100.00%
5
4
22
21
48
10
110
110
110
110
110
110
110
110
4.55%
3.64%
20.00%
19.09%
43.64%
9.09%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
6
23
57
88
168
91
433
433
433
433
433
433
433
433
1.39%
5.31%
13.16%
20.32%
38.80%
21.02%
100.00%
80
167
375
542
469
280
1,913
1,913
1,913
1,913
1,913
1,913
1,913
1,913
4.18%
8.73%
19.60%
28.33%
24.52%
14.64%
100.00%
Ta ble L A B16
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Microbiology
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
53
▶▶ Surgical Information System
The surgical information system environment focuses on IT
applications used in the operating room (OR) and surgery setting.
HIMSS Analytics monitors the following applications in this
environment: OR scheduling, pre-operative and post-operative
systems. As of this year, HIMSS Analytics no longer tracks perioperative systems (see Table OR1). Moreover, all three applications
increased in market adoption this year with increases ranging from
three to four percentage points.
Approximately three-quarters of planned purchases across all three
surgical information system applications were by hospitals intending
to replace their current solution (see Table OR2).
An evaluation of the surgical information system application market
by the various hospital market segments in 2012 reveals the following:
• Post-operative: the rural hospital segment had the highest yearover-year growth for this segment, at nearly eight percentage
points. This is followed by the critical access and single hospital
system segments, which each had growths of six to seven
percentage points (see Table OR3). All other segments indicated
an increase of less than five percentage points.
• Pre-operative: all segments grew between 2011 and 2012, with
the largest gains occurring in the critical access and rural hospital
segments (see Table OR4). Academic medical centers, which have
Ta ble OR1 | Operating Room
N=4,217
2010
2011
Post-Operative
60.52%
64.71%
Pre-Operative
64.64%
67.68%
OR Scheduling
67.63%
70.41%
2012
68.72%
71.16%
73.35%
achieved near market saturation, reflected the smallest increase
in market penetration at less than one percentage point.
• OR scheduling: the rural hospital segment reported the largest
year-over-year growth at approximately seven percentage points.
Strong growth (six percentage points) was also observed in the
critical access hospital segment. All of the other hospital segments
demonstrated an increase ranging from less than one percentage
point to approximately five percentage points (see Table OR5).
An evaluation of the surgical information system market by bed
size in 2012 demonstrated the following (see Tables OR6–OR12):
• 0–100 beds: all three OR applications showed a growth of
approximately five percentage points (see Table OR6).
• 101–200 beds: OR scheduling is the only application to report a
growth of less than two percentage points. Post-operative and
pre-operative adoption grew by two to three percentage points
(see Table OR7).
Ta ble OR 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Post-Operative
53
75.71%
Pre-Operative
55
73.33%
OR Scheduling
59
85.51%
for the First Time
17
20
10
for the First Time
24.29%
26.67%
14.49%
N = Total Number of
Hospitals Planning
70
75
69
Ta ble OR3 | Post-Operative
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
161
2,391
1,876
676
401
2,151
320
2,232
1,693
859
2,552
Percent
90.45%
59.20%
76.51%
38.30%
34.93%
70.09%
32.79%
68.87%
65.29%
52.89%
60.52%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
166
2,563
1,966
763
476
2,253
388
2,341
1,774
955
2,729
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
172
2,682
2,057
797
501
2,353
408
2,446
1,844
1,010
2,854
Percent
93.26%
63.46%
80.18%
43.23%
41.46%
73.41%
39.75%
72.23%
68.41%
58.81%
64.71%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
169
2,729
2,053
845
556
2,342
463
2,435
1,842
1,056
2,898
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
173
2,828
2,125
876
579
2,422
478
2,523
1,901
1,100
3,001
Percent
94.94%
67.57%
83.73%
47.88%
48.43%
76.31%
47.44%
75.13%
71.04%
65.02%
68.72%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble OR4 | Pre-Operative
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
170
2,556
1,994
732
440
2,286
347
2,379
1,796
930
2,726
Percent
95.51%
63.28%
81.32%
41.47%
38.33%
74.49%
35.55%
73.40%
69.26%
57.27%
64.64%
2011
Percent
96.63%
66.40%
83.89%
45.16%
43.64%
76.67%
41.80%
75.47%
71.11%
62.19%
67.68%
2012
Percent
97.19%
70.02%
86.66%
49.63%
50.44%
78.92%
48.98%
77.85%
73.31%
67.73%
71.16%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
▶▶ Surgical Information System con tinue d
Ta ble OR5 | OR Scheduling
2010
Segment
Count
176
2,676
2,074
778
473
2,379
366
2,486
1,892
960
2,852
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
98.88%
66.25%
84.58%
44.08%
41.20%
77.52%
37.50%
76.70%
72.97%
59.11%
67.63%
• 201–300 beds: all three applications reported an increase in
adoption from 2011 to 2012, ranging from one to two percentage
points (see Table OR8), with post-operative reflecting the largest
increase.
• 301–400 beds: post-operative and pre-operative grew between
2011 and 2012, while OR scheduling reflected a small decline
during time (see Table OR9).
• 401–500 beds: post-operative applications indicated the highest
year-over-year growth from 2011 to 2012, at more than two
percentage points (see Table OR10). The other two OR
applications also grew during this period.
• 501–600 beds: post-operative and pre-operative systems grew less
than one percent from 2011 to 2012, while there was no change
in the highly saturated OR scheduling market (see Table OR11).
• Over 600 beds: all three OR applications are close to
approaching, or have already achieved, market saturation
(95-100 percent) in this bed segment. No growth was reported
for OR scheduling, while post-operative adoption increased by
more than one percentage point (see Table OR12).
Ta ble OR6
0–100 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
863
941
993
2011
2012
39.86%
987 45.59% 1,109 51.22%
43.46% 1,037 47.90% 1,149 53.07%
45.87% 1,078 49.79% 1,185 54.73%
Ta ble OR7
101–200 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
606
640
671
2011
% of 802 Hospitals
75.56%
633 78.93%
79.80%
660 82.29%
83.67%
696 86.78%
2012
656
678
705
81.80%
84.54%
87.91%
Ta ble OR8
201–300 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
407
432
452
2011
% of 483 Hospitals
84.27%
409 84.68%
89.44%
434 89.86%
93.58%
452 93.58%
2012
420
443
458
86.96%
91.72%
94.82%
Ta ble OR9
301–400 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
264
279
292
2011
% of 312 Hospitals
84.62%
277 88.78%
89.42%
287 91.99%
93.59%
295 94.55%
2012
282
290
294
90.38%
92.95%
94.23%
Segment
Count
177
2,792
2,136
833
532
2,437
426
2,543
1,925
1,044
2,969
Percent
99.44%
69.13%
87.11%
47.20%
46.34%
79.41%
43.65%
78.46%
74.24%
64.29%
70.41%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
2,915
2,188
905
603
2,490
496
2,597
1,975
1,118
3,093
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Percent
100.00%
72.17%
89.23%
51.27%
52.53%
81.13%
50.82%
80.13%
76.17%
68.84%
73.35%
Ta ble OR10
401–500 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
167
178
180
2011
% of 188 Hospitals
88.83%
170 90.43%
94.68%
178 94.68%
95.74%
183 97.34%
2012
175
181
186
93.09%
96.28%
98.94%
Ta ble OR11
501–600 Beds
Post-Operative
Pre-Operative
OR Scheduling
2010
104
110
114
2011
% of 116 Hospitals
89.66%
107 92.24%
94.83%
110 94.83%
98.28%
114 98.28%
2012
108
111
114
93.10%
95.69%
98.28%
Ta ble OR12
Over 600 beds
Post-Operative
Pre-Operative
OR Scheduling
2010
141
146
150
2011
% of 151 Hospitals
93.38%
146 96.69%
96.69%
148 98.01%
99.34%
151 100.00%
2012
148 98.01%
149 98.68%
151 100.00%
At least 20 percent of the contracts in the surgical information
system market were signed in the past two years (see Table OR13),
while approximately two-thirds of all contracts were signed
between 2000 and 2009.
Ta ble OR13
Post-Operative
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Pre-Operative
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
OR Scheduling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
16
63
200
660
554
388
1,881
1,881
1,881
1,881
1,881
1,881
1,881
1,881
0.85%
3.35%
10.63%
35.09%
29.45%
20.63%
100.00%
17
52
160
610
595
403
1,837
1,837
1,837
1,837
1,837
1,837
1,837
1,837
0.93%
2.84%
8.72%
33.26%
32.44%
21.97%
100.00%
17
52
160
610
595
403
1,837
1,837
1,837
1,837
1,837
1,837
1,837
1,837
0.93%
2.84%
8.72%
33.26%
32.44%
21.97%
100.00%
55
▶▶ Surgical Information System con tinued
The surgical information system market for U.S. hospitals has been
and will continue to be impacted through 2015 by:
• Internally and externally initiated quality outcomes and
performance improvement efforts.
• A continuing focus on reducing medical and medication errors at
the point-of-care and during surgical procedures, which is again
likely to be tied to ARRA reporting measures.
• An increased need to capture, share, manage, analyze, and report
OR data to improve processes and drive down costs, some of
which will be for ARRA measurement reporting purposes, as
well as to prepare the organization to price appropriately to
accept more bundled pricing risk in an ACO environment.
• Intense competition for limited capital funds, which are likely to be
allocated to higher priority applications, such electronic medical
record (EMR) and financial projects (e.g. ICD-10 encoding
conversions) which may slow this market through at least 2015.
• The increased focus of the federal government via ARRA to
improve data sharing across modalities of care and among all
care providers (e.g. patient summary data).
• Increasingly stringent claims coding and supporting
documentation requirements mandated by federal regulations and
public and private reimbursement requirements.
• An increased consumer demand to access and evaluate hospital
service performance indicators related to hospital performance
score cards.
▶▶ Radiology PACS
Radiology picture archive and communications systems (R-PACS) are
used by hospitals to capture medical images and provide convenient
access to clinicians throughout the healthcare system. The R-PACS
suite monitored by HIMSS Analytics is comprised of the following
10 modalities: angiography, computed radiography, computerized
tomography (CT), digital fluoroscopy, digital mammography, digital
radiography, magnetic resonance imaging (MRI), nuclear medicine,
orthopedic surgical templating and ultrasound.
In 2012, the R-PACS environment demonstrated market penetration
growth in all modalities (see Table RP1). The rate of increase from
2011 to 2012 was generally lower than those indicated from 2010 to
2011. The digital mammography modality had the highest year-overyear growth from 2011 to 2012 at just more than five percentage points.
Relatively few hospitals indicated plans to purchase an R-PACS
modality in the near distant future. Of those that did, the majority
Ta ble RP1 | R-PACS
N=4,217
2010
2011
Angiography
63.86%
65.26%
Computed Radiography (CR)
82.88%
86.01%
Computerized Tomography (CT)
84.63%
87.05%
Digital Fluoroscopy (DF)
71.61%
74.18%
Digital Mammography
50.46%
58.41%
Digital Radiography (DR)
74.48%
77.12%
Magnetic Resonance Imaging
79.18%
81.53%
Nuclear Medicine
73.70%
75.84%
Orthopedic
42.54%
47.33%
Ultrasound (US)
82.90%
86.10%
2012
66.54%
88.10%
88.78%
76.22%
63.46%
78.35%
83.16%
77.28%
49.99%
87.72%
of hospitals would be classified as first time buyers of an R-PACS
modality (see Table RP2). The clear exception to this general trend
involved the orthopedic surgical templating modality. More than
70 percent of the planned purchases for CT, digital fluoroscopy,
digital mammography, digital radiography, nuclear medicine and
ultrasound were for hospitals that do not have these solutions.
The following are some of the key findings for each R-PACS
modality by hospital segment:
• Angiography: all hospital segments reported a slight increase in
adoption from 2011 to 2012 (see Table RP3). This modality
appears to be a good market opportunity (34 percent of hospitals
have yet to acquire this technology).
• Computed radiography: the critical access and rural hospital
segments reported the highest increase in adoption from 2011
to 2012 at approximately five percentage points. The academic
medical center segment, which is a saturated market, had
growth of less than one percentage point (see Table RP4).
• Computerized tomography: critical access and rural hospital
segments were the only segments to report a growth in adoption
from 2011 to 2012 at more than four percentage points. All other
segments, except academic medical centers, reported a growth
from one to three percentage points. The academic medical
center segment has reached market segmentation and registered
no market penetration change (see Table RP5).
• Digital fluoroscopy: All segments indicated growth from 2011 to
2012 with the largest growth evidenced in the rural and critical
access hospital segments (see Table RP6).
Ta ble rp 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Angiography
4
40.00%
CR (Computed Radiography)
2
33.33%
CT (Computerized Tomography)
3
30.00%
DF (Digital Fluoroscopy
2
28.57%
Digital Mammography
2
13.33%
DR (Digital Radiography)
2
28.57%
MRI (Magnetic Resonance Imaging)
2
33.33%
Nuclear Medicine
2
28.57%
Orthopedic
3
60.00%
US (Ultrasound)
2
25.00%
for the First Time
6
4
7
5
13
5
4
5
2
6
for the First Time
60.00%
66.67%
70.00%
71.43%
86.67%
71.43%
66.67%
71.43%
40.00%
75.00%
N = Total Number of
Hospitals Planning
10
6
10
7
15
7
6
7
5
8
▶▶ Radiology PACS con tinued
• Digital Mammography: all segments grew by four to eight
percentage points from 2011 to 2012. The rural and critical
access hospital segments reported made the biggest gains this
past year (see Table RP7).
• Digital radiography: rural hospitals had the largest increase at
slightly more than three percentage points; the medical/surgical
and urban segments reported the lowest growth at less than
one percentage point each (see Table RP8).
• MRI: the rural hospital and critical access hospital segments
experienced the most growth from 2011 to 2012 at more than
three percentage points. The academic medical center segment,
which is approaching market saturation, showed no growth.
The remaining segments showed growth of less than three
percentage points (see Table RP9).
• Nuclear medicine: all of the hospital segments reported a
growth of under four percentage points, with the critical
access segment reflecting the largest year-over-year increase
(see Table RP10).
• Orthopedic: academic medical centers had the highest growth
in this segment with more than a five percentage point increase.
The next highest increase was in the general medical/surgical
segment at three percentage points (see Table RP11).
• Ultrasound: almost all segments indicated growth from 2011 to
20112. The exception being the academic medical center segment
which is fully saturated had reported no change from 2011. The
highest year-over-year growth of nearly four percentage points
was found in critical access and rural hospitals (see Table RP12).
Ta ble RP 3 | Angiography
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
172
2,521
1,987
706
394
2,299
330
2,363
1,844
849
2,693
Percent
96.63%
62.42%
81.04%
40.00%
34.32%
74.91%
33.81%
72.91%
71.11%
52.28%
63.86%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
173
2,579
2,035
717
416
2,336
356
2,396
1,889
863
2,752
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,452
2,290
1,337
897
2,730
760
2,867
2,251
1,376
3,627
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,494
2,359
1,312
968
2,703
816
2,855
2,216
1,455
3,671
Percent
97.19%
63.85%
82.99%
40.62%
36.24%
76.12%
36.48%
73.93%
72.85%
53.14%
65.26%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
2,631
2,065
741
437
2,369
381
2,425
1,928
878
2,806
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,539
2,316
1,399
954
2,761
811
2,904
2,290
1,425
3,715
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,567
2,383
1,361
1,014
2,730
860
2,884
2,253
1,491
3,744
Percent
98.31%
65.14%
84.22%
41.98%
38.07%
77.19%
39.04%
74.82%
74.35%
54.06%
66.54%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP4 | Computed Radiography (CR)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
175
3,320
2,235
1,260
828
2,667
693
2,802
2,166
1,329
3,495
Percent
98.31%
82.20%
91.15%
71.39%
72.13%
86.90%
71.00%
86.45%
83.53%
81.83%
82.88%
2011
Percent
98.31%
85.47%
93.39%
75.75%
78.14%
88.95%
77.87%
88.46%
86.81%
84.73%
86.01%
2012
Percent
98.88%
87.62%
94.45%
79.26%
83.10%
89.96%
83.09%
89.60%
88.31%
87.75%
88.10%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP5 | Computerized Tomography (CT)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
177
3,392
2,312
1,257
899
2,670
752
2,817
2,158
1,411
3,569
Percent
99.44%
83.98%
94.29%
71.22%
78.31%
87.00%
77.05%
86.92%
83.22%
86.88%
84.63%
2011
Percent
99.44%
86.51%
96.21%
74.33%
84.32%
88.07%
83.61%
88.09%
85.46%
89.59%
87.05%
2012
Percent
99.44%
88.31%
97.19%
77.11%
88.33%
88.95%
88.11%
88.98%
86.89%
91.81%
88.78%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
57
Ta ble RP6 | Digital Fluoroscopy (DF)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
170
2,850
2,132
888
552
2,468
459
2,561
1,972
1,048
3,020
Percent
95.51%
70.56%
86.95%
50.31%
48.08%
80.42%
47.03%
79.02%
76.05%
64.53%
71.61%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
171
2,957
2,187
941
599
2,529
503
2,625
2,038
1,090
3,128
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
139
2,324
1,753
710
524
1,939
421
2,042
1,569
894
2,463
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
173
3,079
2,190
1,062
656
2,596
560
2,692
2,099
1,153
3,252
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,263
2,299
1,139
821
2,617
692
2,746
2,131
1,307
3,438
Percent
96.07%
73.21%
89.19%
53.31%
52.18%
82.40%
51.54%
80.99%
78.60%
67.12%
74.18%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,039
2,223
991
643
2,571
542
2,672
2,084
1,130
3,214
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
150
2,526
1,867
809
612
2,064
496
2,180
1,680
996
2,676
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
174
3,130
2,202
1,102
692
2,612
596
2,708
2,123
1,181
3,304
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,332
2,326
1,181
864
2,643
730
2,777
2,166
1,341
3,507
Percent
98.31%
75.24%
90.66%
56.15%
56.01%
83.77%
55.53%
82.44%
80.37%
69.58%
76.22%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP7 | Digital Mammography
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
126
2,002
1,529
599
413
1,715
322
1,806
1,385
743
2,128
Percent
70.79%
49.57%
62.36%
33.94%
35.98%
55.88%
32.99%
55.72%
53.41%
45.75%
50.46%
2011
Percent
78.09%
57.54%
71.49%
40.23%
45.64%
63.18%
43.14%
63.01%
60.51%
55.05%
58.41%
2012
Percent
84.27%
62.54%
76.14%
45.84%
53.31%
67.25%
50.82%
67.26%
64.79%
61.33%
63.46%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP 8 | Digital Radiography (DR)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
172
2,969
2,133
1,008
606
2,535
508
2,633
2,041
1,100
3,141
Percent
96.63%
73.51%
86.99%
57.11%
52.79%
82.60%
52.05%
81.24%
78.71%
67.73%
74.48%
2011
Percent
97.19%
76.23%
89.31%
60.17%
57.14%
84.59%
57.38%
83.06%
80.95%
71.00%
77.12%
2012
Percent
97.75%
77.49%
89.80%
62.44%
60.28%
85.11%
61.07%
83.55%
81.87%
72.72%
78.35%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP 9 | Magnetic Resonance Imaging (MRI)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
174
3,165
2,245
1,094
763
2,576
629
2,710
2,072
1,267
3,339
Percent
97.75%
78.36%
91.56%
61.98%
66.46%
83.94%
64.45%
83.62%
79.91%
78.02%
79.18%
2011
Percent
98.31%
80.79%
93.76%
64.53%
71.52%
85.27%
70.90%
84.73%
82.18%
80.48%
81.53%
2012
Percent
98.31%
82.50%
94.86%
66.91%
75.26%
86.12%
74.80%
85.68%
83.53%
82.57%
83.16%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP10 | Nuclear Medicine
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
169
2,939
2,210
898
586
2,522
498
2,610
1,988
1,120
3,108
Percent
94.94%
72.77%
90.13%
50.88%
51.05%
82.18%
51.02%
80.53%
76.67%
68.97%
73.70%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
169
3,029
2,256
942
645
2,553
552
2,646
2,039
1,159
3,198
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
127
1,869
1,393
603
364
1,632
288
1,708
1,272
724
1,996
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,455
2,341
1,290
936
2,695
788
2,843
2,214
1,417
3,631
Percent
94.94%
74.99%
92.01%
53.37%
56.18%
83.19%
56.56%
81.64%
78.63%
71.37%
75.84%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
170
3,089
2,275
984
685
2,574
584
2,675
2,074
1,185
3,259
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
137
1,971
1,469
639
385
1,723
309
1,799
1,337
771
2,108
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
176
3,523
2,363
1,336
979
2,720
827
2,872
2,246
1,453
3,699
Percent
95.51%
76.48%
92.78%
55.75%
59.67%
83.87%
59.84%
82.54%
79.98%
72.97%
77.28%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP11 | Orthopedic
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
122
1,672
1,261
533
304
1,490
232
1,562
1,160
634
1,794
Percent
68.54%
41.40%
51.43%
30.20%
26.48%
48.55%
23.77%
48.20%
44.74%
39.04%
42.54%
2011
Percent
71.35%
46.27%
56.81%
34.16%
31.71%
53.18%
29.51%
52.70%
49.06%
44.58%
47.33%
2012
Percent
76.97%
48.80%
59.91%
36.20%
33.54%
56.14%
31.66%
55.51%
51.56%
47.48%
49.99%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble RP12 | Ultrasound (US)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
175
3,321
2,289
1,207
859
2,637
715
2,781
2,127
1,369
3,496
Percent
98.31%
82.22%
93.35%
68.39%
74.83%
85.92%
73.26%
85.81%
82.03%
84.30%
82.90%
2011
The evaluation of R-PACS market by bed size for 2012 indicates
that growth was slightly higher among the smaller hospital bed
segments than larger bed segments. The adoption of digital
mammography demonstrated the largest increase from 2011 to 2012
across most of the bed segments. The following list represents some
key modality findings within each bed segment:
• 0–100 beds: digital mammography indicated the largest yearover-year increase at more than six percentage points, while the
other modalities experienced increases ranging from one to four
percentage points (see Table RP13).
• 101–200 beds: digital mammography reported the highest growth
at more than four percentage points, while all other segments
indicated growth two percentage points or less (see Table RP14).
• 201–300 beds: digital mammography demonstrated the highest
increase from 2011 to 2012 at more than four percentage points,
followed by orthopedic at more than two percentage points.
Digital radiography is the only R-PACS modality to indicate a
decrease in adoption (see Table RP15).
Percent
98.88%
85.54%
95.47%
73.09%
81.53%
87.81%
80.74%
87.72%
85.38%
87.25%
86.10%
2012
Percent
98.88%
87.22%
96.37%
75.69%
85.28%
88.63%
84.73%
88.61%
86.62%
89.47%
87.72%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
• 301–400 beds: at more than five percentage points, digital
mammography had the highest adoption from 2011 to 2012,
followed by orthopedic at more than four percentage points. All
other modalities indicated growth of approximately one
percentage point (see Table RP16).
• 401–500 beds: orthopedic indicated the largest increase from
2011 to 2012 at approximately two percentage points, followed by
digital mammography, MRI and nuclear medicine. All other
modalities reported no change from 2011 (see Table RP17).
• 501–600 beds: digital mammography had the highest increase in
adoption from 2011 to 2012 at more than five percentage points,
while digital radiography reported a decline of more than two
percentage points. None of the other modalities reported a change
from 2011 (see Table RP18).
• Over 600 beds: digital fluoroscopy, digital mammography and
digital radiography are the only modalities to indicate an increase
from 2011 to 2012. All other modalities reported no change in the
past year (see Table RP19).
59
Ta ble RP13
Ta ble RP18
0–100 Beds
Angiography
Digital Mammography
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
2010
895
1,560
1,607
1,162
768
1,267
1,415
1,194
608
1,548
41.34%
72.06%
74.23%
53.67%
35.47%
58.52%
65.36%
55.15%
28.08%
71.50%
2011
2012
926 42.77%
960 44.34%
1,673 77.27% 1,751 80.88%
1,697 78.38% 1,760 81.29%
1,240 57.27% 1,301 60.09%
956 44.16% 1,087 50.21%
1,355 62.59% 1,404 64.85%
1,492 68.91% 1,549 71.55%
1,268 58.57% 1,318 60.88%
706 32.61%
770 35.57%
1,667 77.00% 1,726 79.72%
Ta ble RP14
2010
635
734
739
687
482
698
716
716
416
729
79.18%
91.52%
92.14%
85.66%
60.10%
87.03%
89.28%
89.28%
51.87%
90.90%
2011
% of 802 Hospitals
649 80.92%
748 93.27%
749 93.39%
705 87.91%
558 69.58%
713 88.90%
734 91.52%
729 90.90%
463 57.73%
742 92.52%
2012
661
753
755
720
592
716
739
733
482
748
82.42%
93.89%
94.14%
89.78%
73.82%
89.28%
92.14%
91.40%
60.10%
93.27%
Ta ble RP15
201–300 Beds
Angiography
Digital Mammography
Nuclear Medicine
Orthopedic
Ultrasound (US)
2010
433
452
467
440
319
442
459
457
272
465
89.65%
93.58%
96.69%
91.10%
66.05%
91.51%
95.03%
94.62%
56.31%
96.27%
2011
% of 483 Hospitals
442 91.51%
457 94.62%
469 97.10%
447 92.55%
343 71.01%
444 91.93%
461 95.45%
459 95.03%
295 61.08%
468 96.89%
2012
447
460
472
450
363
442
465
462
306
470
92.55%
95.24%
97.72%
93.17%
75.16%
91.51%
96.27%
95.65%
63.35%
97.31%
Ta ble RP16
301–400 Beds
Angiography
Digital Mammography
Nuclear Medicine
Orthopedic
Ultrasound (US)
2010
286
300
304
292
218
290
301
299
184
302
91.67%
96.15%
97.44%
93.59%
69.87%
92.95%
96.47%
95.83%
58.97%
96.79%
2011
% of 312 Hospitals
289 92.63%
301 96.47%
304 97.44%
295 94.55%
236 75.64%
295 94.55%
302 96.79%
299 95.83%
193 61.86%
302 96.79%
2012
292
303
305
298
252
299
304
302
207
303
93.59%
97.12%
97.76%
95.51%
80.77%
95.83%
97.44%
96.79%
66.35%
97.12%
Ta ble RP17
401–500 Beds
Angiography
Digital Mammography
Digital Radiography ( DR)
Nuclear Medicine
Orthopedic
Ultrasound (US)
Angiography
Digital Mammography
Nuclear Medicine
Orthopedic
Ultrasound (US)
2010
113
115
115
114
84
114
115
113
72
115
97.41%
99.14%
99.14%
98.28%
72.41%
98.28%
99.14%
97.41%
62.07%
99.14%
2011
% of 116 Hospitals
113 97.41%
115 99.14%
115 99.14%
114 98.28%
95 81.90%
114 98.28%
115 99.14%
113 97.41%
79 68.10%
115 99.14%
2012
113
115
115
114
101
111
115
113
79
115
97.41%
99.14%
99.14%
98.28%
87.07%
95.69%
99.14%
97.41%
68.10%
99.14%
Ta ble RP19
101–200 Beds
Angiography
Digital Mammography
Nuclear Medicine
Orthopedic
Ultrasound (US)
501–600 Beds
2010
182
184
186
180
139
181
184
182
131
186
96.81%
97.87%
98.94%
95.74%
73.94%
96.28%
97.87%
96.81%
69.68%
98.94%
2011
% of 188 Hospitals
182 96.81%
183 97.34%
186 98.94%
180 95.74%
147 78.19%
182 96.81%
184 97.87%
183 97.34%
139 73.94%
186 98.94%
2012
182
183
186
180
150
182
185
184
143
186
96.81%
97.34%
98.94%
95.74%
79.79%
96.81%
98.40%
97.87%
76.06%
98.94%
Over 600 beds
Angiography
Computerized Tomography(CT)
Digital Mammography
Nuclear Medicine
Orthopedic
Ultrasound (US)
2010
149 98.68%
150 99.34%
151 100.00%
145 96.03%
118 78.15%
149 98.68%
149 98.68%
147 97.35%
111 73.51%
151 100.00%
2011
% of 151 Hospitals
151 100.00%
150 99.34%
151 100.00%
147 97.35%
128 84.77%
149 98.68%
150 99.34%
147 97.35%
121 80.13%
151 100.00%
2012
151
150
151
151
131
150
150
147
121
151
100.00%
99.34%
100.00%
100.00%
86.75%
99.34%
99.34%
97.35%
80.13%
100.00%
Most R-PACS application contracts were signed prior to 2010 with
less than 10 percent of contracts signed across almost all modalities
occurring between 2010 and 2012. Digital mammography is the
only modality to have more than 10 percent of the contracts signed
after 2010 (see Tables RP20–RP23).
Ta ble RP 20
Angiography
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
54
799
874
99
1,826
1,826
1,826
1,826
1,826
1,826
1,826
1,826
0.00%
0.00%
2.96%
43.78%
47.89%
5.42%
100.00%
0
0
56
910
1,205
163
2,334
2,334
2,334
2,334
2,334
2,334
2,334
2,334
0.00%
0.00%
2.40%
39.04%
51.69%
6.99%
100.00%
0
0
58
935
1,198
158
2,349
2,349
2,349
2,349
2,349
2,349
2,349
2,349
0.00%
0.00%
2.20%
35.63%
47.93%
6.63%
100.00%
Ta ble RP 21
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Digital Mammography
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Ta ble RP 23
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
54
856
1,028
124
2,062
2,062
2,062
2,062
2,062
2,062
2,062
2,062
0.00%
0.00%
2.62%
41.53%
49.88%
6.02%
100.00%
0
0
17
320
749
173
1,259
1,259
1,259
1,259
1,259
1,259
1,259
1,259
0.00%
0.00%
1.35%
25.44%
59.54%
13.75%
100.00%
0
0
48
820
1,030
130
2,028
2,028
2,028
2,028
2,028
2,028
2,028
2,028
0.00%
0.00%
2.37%
40.45%
50.81%
6.41%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
58
904
1,095
147
2,204
2,204
2,204
2,204
2,204
2,204
2,204
2,204
0.00%
0.00%
2.63%
41.03%
49.70%
6.67%
100.00%
0
0
55
858
1,050
128
2,091
2,091
2,091
2,091
2,091
2,091
2,091
2,091
0.00%
0.00%
2.63%
41.05%
50.24%
6.12%
100.00%
0
0
21
365
562
84
1,032
1,032
1,032
1,032
1,032
1,032
1,032
1,032
0.00%
0.00%
2.03%
35.37%
54.46%
8.14%
100.00%
Ta ble RP 22
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Nuclear Medicine
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Orthopedic
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
US (Ultrasound)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
57
930
1,175
156
2,318
2,318
2,318
3,218
2,318
2,318
2,318
2,318
0.00%
0.00%
1.77%
40.16%
50.73%
6.74%
100.00%
The R-PACS IT application market will most likely continue to
experience growth, driven by continued first-time purchases among
smaller hospitals and the early stages of replacement purchases by
the larger hospitals, including academic medical centers and other
early adopters. This market segment has been, and will most likely
continue to be, impacted through 2015 by:
• Increased demand to share medical images between care
providers in HIEs, a need that will be driven by ARRA Stage 2
and Stage 3 Meaningful Use requirements.
• Increased demand for the electronic transmittal and integration
of images and reports from owned, affiliated and other
ambulatory practices for which the hospital provides diagnostic
imaging services.
• Ongoing market consolidation where a growing IDN elects to
standardize on one R-PACS vendor solution for the entire system.
• Continued acquisitions of ambulatory centers by IDNs where
they elect to standardize on one PACS vendor solution.
• Ongoing demand to drive down radiology service and storage
costs and eliminate film costs.
• The increasing demand for orthopedic pre-surgical templating to
improve quality related to implant surgery for a growing elderly
population.
• The need to attach medical images to claims for improved payer
reimbursement processes.
• The increasing adoption of care delivery models that emphasize
care coordination, and reward participants for producing
improved clinical outcomes, reducing redundant testing, and
sharing results electronically.
• Increasing consumer demands to have access to their medical
information and images.
61
▶▶ Cardiology PACS
A cardiology picture archive and communications system (C-PACS)
solution refers to electronic storage of images in a networked digital
archive that stores, manages, transmits and displays cardiology
images. The C-PACS market is comprised five different modalities
including cath lab, computerized tomography (CT), echocardiology,
intravascular ultrasound and nuclear cardiology.
More than one-third of U.S. hospitals have incorporated the
echocardiology and cath lab modalities, while approximately
20 percent of hospitals have the other C-PACS modalities in place.
The C-PACS environment demonstrated a growth ranging from
one to three percent for all modalities (see Table CP1). The
growth from 2011 to 2012 slowed in comparison to 2010 to 2011.
Historically, C-PACS tend to grow at a slow but steady pace. The
C-PACS growth is thought to be slower than the R-PACS growth
due to a lack of significant cost reduction from the replacement
of film.
When evaluating planned purchases, CT is the only C-PACS
modality to indicate more plans for replacements than first time
purchases. Intravascular ultrasound purchase plans reflect more first
time purchasers than replacements. The remaining modalities
Ta ble CP1 | C-PACS
N=4,217
2010
2011
Cardiology–Cath Lab
31.04%
32.30%
Cardiology–Computerized Tomography (CT)
19.99%
22.15%
Cardiology–Echocardiology
30.78%
33.55%
Cardiology–Intravascular Ultrasound
18.90%
21.22%
Cardiology–Nuclear Cardiology
18.00%
20.99%
2012
34.01%
24.02%
36.19%
23.17%
23.12%
indicated almost the same amount of first time and replacement
purchases (see Table CP2).
An evaluation of market segments in 2012 by hospital type reveals
the following highlights for each C-PACS modality:
• Cath lab: the academic medical center segment indicated the
highest increase from 2011 to 2012 at slightly less than three
percentage points. The general medical/surgical, non-critical
access, urban and multi-hospital segments all grew by more than
two percentage points. The critical access hospital segment is the
only segment to report a decrease from 2011 (see Table CP3).
• Computerized tomography: all of the hospital segments reported
a growth from 2011 to 2012 with general medical/surgical
reporting the largest year-over-year increase at about three
percentage points (see Table CP4). Growth ranged from less than
one to slightly under three percentage points across all segments.
• Echocardiology: growth for academic medical center, general
medical/surgical and non-critical access segments all exceeded
three percentage points from 2011 to 2012 (see Table CP5). All
other segments demonstrated an increase of one to three
percentage points.
• Intravascular ultrasound: the academic medical center segment
demonstrated the largest year-over-year growth at approximately
four percentage points. The critical access hospital segment
demonstrated the lowest increase (see Table CP6).
• Nuclear cardiology: with more than a five percentage point
increase, the academic medical center market segment reflected
the highest year-over-year growth, followed by the general medical/
surgical and non-critical access segments (see Table CP7).
Ta ble CP 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
7
50.00%
6
75.00%
7
50.00%
1
25.00%
5
45.45%
for the First Time
7
2
7
3
6
for the First Time
50.00%
25.00%
50.00%
75.00%
54.55%
N = Total Number of
Hospitals Planning
14
8
14
4
11
Ta ble CP 3 | Cardiology–Cath Lab
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
140
1,169
1,094
215
21
1,288
18
1,291
962
347
1,309
Percent
78.65%
28.94%
44.62%
12.18%
1.83%
41.97%
1.84%
39.83%
37.10%
21.37%
31.04%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
139
1,223
1,148
214
20
1,342
18
1,344
984
378
1,362
Percent
78.09%
30.28%
46.82%
12.12%
1.74%
43.73%
1.84%
41.47%
37.95%
23.28%
32.30%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
144
1,290
1,214
220
18
1,416
24
1,410
1,036
398
1,434
Percent
80.90%
31.94%
49.51%
12.46%
1.57%
46.14%
2.46%
43.51%
39.95%
24.51%
34.01%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
▶▶ Cardiology PACS con tinued
Ta ble CP4 | Cardiology–Computerized Tomography (CT)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
90
753
684
159
41
802
23
820
612
231
843
Percent
50.56%
18.64%
27.90%
9.01%
3.57%
26.13%
2.36%
25.30%
23.60%
14.22%
19.99%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
96
838
761
173
48
886
28
906
673
261
934
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
131
1,284
1,137
278
89
1,326
63
1,352
973
442
1,415
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
98
797
735
160
33
862
27
868
627
268
895
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
91
794
721
164
47
838
38
847
601
284
885
Percent
53.93%
20.75%
31.04%
9.80%
4.18%
28.87%
2.87%
27.95%
25.95%
16.07%
22.15%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
100
913
830
183
50
963
36
977
724
289
1,013
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
138
1,388
1,218
308
106
1,420
83
1,443
1,038
488
1,526
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
105
872
804
173
35
942
37
940
686
291
977
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
101
874
787
188
57
918
48
927
653
322
975
Percent
56.18%
22.60%
33.85%
10.37%
4.36%
31.38%
3.69%
30.15%
27.92%
17.80%
24.02%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble CP5 | Cardiology–Echocardiology
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
130
1,168
1,046
252
69
1,229
45
1,253
910
388
1,298
Percent
73.03%
28.92%
42.66%
14.28%
6.01%
40.05%
4.61%
38.66%
35.09%
23.89%
30.78%
2011
Percent
73.60%
31.79%
46.37%
15.75%
7.75%
43.21%
6.45%
41.72%
37.52%
27.22%
33.55%
2012
Percent
77.53%
34.36%
49.67%
17.45%
9.23%
46.27%
8.50%
44.52%
40.03%
30.05%
36.19%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble CP 6 | Cardiology–Intravascular Ultrasound
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
94
703
652
145
26
771
19
778
565
232
797
Percent
52.81%
17.41%
26.59%
8.22%
2.26%
25.12%
1.95%
24.00%
21.79%
14.29%
18.90%
2011
Percent
55.06%
19.73%
29.98%
9.07%
2.87%
28.09%
2.77%
26.78%
24.18%
16.50%
21.22%
2012
Percent
58.99%
21.59%
32.79%
9.80%
3.05%
30.69%
3.79%
29.00%
26.46%
17.92%
23.17%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble CP7 | Cardiology–Nuclear Cardiology
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Not Critical Access
Rural
Urban
All
Segment
Count
88
671
611
148
35
724
25
734
523
236
759
Percent
49.44%
16.61%
24.92%
8.39%
3.05%
23.59%
2.56%
22.65%
20.17%
14.53%
18.00%
2011
Percent
51.12%
19.66%
29.40%
9.29%
4.09%
27.31%
3.89%
26.13%
23.18%
17.49%
20.99%
2012
Percent
56.74%
21.64%
32.10%
10.65%
4.97%
29.91%
4.92%
28.60%
25.18%
19.83%
23.12%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
63
The evaluation of the C-PACS market by bed size segments for
2012 reveals the following (see Tables CP8–CP14):
• 0–100 beds: echocardiology had the highest growth at nearly two
percentage points, while the other modalities reported an increase
of under two percentage points (see Table CP8).
• 101–200 beds: for the second year in a row, echocardiology
indicated the highest increase at more than four percentage
points, followed by nuclear cardiology at slightly more than three
percentage points (see Table CP9). All other modalities indicated
an increase of at least two percentage points from last year.
• 201–300 beds: nuclear cardiology grew by almost four percentage
points, followed by cath lab at slightly more than three percentage
points. All other modalities reported a growth of slightly under
three percentage points (see Table CP10).
• 301–400 beds: the cath lab modality increased by more than five
percentage points from 2011 to 2012. All other modalities grew
by two to four percentage points (see Table CP11).
• 401–500 beds: echocardiology and nuclear cardiology are tied
for the highest increase in adoption from 2011 to 2012, at close
to four percentage points (see Table CP12).
• 501–600 beds: intravascular ultrasound reported the largest
increase in adoption from 2011 to 2012 at more than four
percentage points. The level of adoption for cath lab declined
slightly in this segment (see Table CP13).
• Over 600 beds: at more than six percentage points, the largest
year-over-year growth in this bed segment was intravascular
ultrasound, followed by computerized tomography at more than
five percentage points (see Table CP14).
When evaluating the historical contracting activity in the C-PACS
modalities market, we discovered that more than 10 percent of
contracts were signed between 2010 and 2012 (see Tables CP15–
CP16), while more than half of contracts for all modalities were
signed from 2005 to 2009. In addition, as EMR deployments in
academic medical centers and the larger and multi-hospital market
segments have matured, we are seeing an increase in EMR
deployments that incorporate digital images of all types into their
contents. We expect digital imaging modalities of all types to
continue to proliferate over the next several years as the industry
embraces various forms of HIE. Not all of these types of images
will neatly fit into cardiology or R-PACS, since they will
be from other sources, such as gastroenology, pthalmology,
dermatology, tele-medicine, etc.
Ta ble CP 8
0–100 Beds
Cardiology–Computerized
Tomography (CT)
Cardiology–Intravascular
Ultrasound
2010
125
2011
2012
5.77%
128
5.91%
143
6.61%
105
190
4.85%
8.78%
124
232
5.73%
10.72%
144
273
6.65%
12.61%
87
97
4.02%
4.48%
109
134
5.03%
6.19%
129
157
5.96%
7.25%
Ta ble CP 9
101–200 Beds
Tomography (CT)
Ultrasound
2010
323
2011
% of 802 Hospitals
40.27%
334 41.65%
2012
357
44.51%
211
314
26.31%
39.15%
234
340
29.18%
42.39%
257
377
32.04%
47.01%
181
178
22.57%
22.19%
202
207
25.19%
25.81%
226
232
28.18%
28.93%
Ta ble CP10
201–300 Beds
Tomography (CT)
Ultrasound
2010
275
2011
% of 483 Hospitals
56.94%
300 62.11%
2012
316
65.42%
166
249
34.37%
51.55%
189
273
39.13%
56.52%
203
284
42.03%
58.80%
158
143
32.71%
29.61%
185
174
38.30%
36.02%
196
193
40.58%
39.96%
Ta ble CP11
301–400 Beds
Tomography (CT)
Ultrasound
2010
211
2011
% of 312 Hospitals
67.63%
218 69.87%
2012
234
75.00%
123
198
39.42%
63.46%
130
210
41.67%
67.31%
140
222
44.87%
71.15%
131
118
41.99%
37.82%
139
126
44.55%
40.38%
146
133
46.79%
42.63%
Ta ble CP12
401–500 Beds
Tomography (CT)
Ultrasound
2010
150
2011
% of 188 Hospitals
79.79%
154 81.91%
2012
155
82.45%
97
136
51.60%
72.34%
104
143
55.32%
76.06%
106
150
56.38%
79.79%
94
85
50.00%
45.21%
104
93
55.32%
49.47%
109
100
57.98%
53.19%
Ta ble CP13
501–600 Beds
Tomography (CT)
Ultrasound
2010
99
2011
% of 116 Hospitals
85.34%
100 86.21%
2012
99
85.34%
59
89
50.86%
76.72%
63
92
54.31%
79.31%
65
92
56.03%
79.31%
62
61
53.45%
52.59%
65
66
56.03%
56.90%
70
68
60.34%
58.62%
Ta ble CP14
Over 600 beds
Tomography (CT)
Ultrasound
2010
126
2011
% of 151 Hospitals
83.44%
128 84.77%
2012
130
86.09%
82
122
54.30%
80.79%
90
125
59.60%
82.78%
98
128
64.90%
84.77%
84
77
55.63%
50.99%
91
85
60.26%
56.29%
101
92
66.89%
60.93%
Ta ble CP15
Ta ble CP15
# for Contract
Range
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Total
Responding
% of Total
Responding
0
1
9
150
319
79
558
558
558
558
558
558
558
558
0.00%
0.18%
1.63%
27.17%
57.79%
14.31%
100.00%
0
0
5
101
196
34
336
336
336
336
336
336
336
336
0.00%
0.00%
1.49%
30.06%
58.33%
10.12%
100.00%
0
1
8
133
336
84
562
562
562
562
562
562
562
562
0.00%
0.18%
1.42%
23.67%
59.79%
14.95%
100.00%
Despite the near-term mixed outlook for capital budgets, which will
tend to moderate demand, the prospects for long-term growth in this
market segment are very positive. The C-PACS IT application
market has been and will most likely continue to be impacted by:
• The demand to increase medical image sharing among providers
in an EMR environment.
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
5
94
214
40
353
353
353
353
353
353
353
353
0.00%
0.00%
1.42%
26.70%
60.80%
11.36%
100.00%
0
0
6
98
206
41
351
351
351
351
351
351
351
351
0.00%
0.00%
1.71%
27.92%
58.69%
11.68%
100.00%
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
• The demand to share medical images within emerging healthcare
information exchanges.
• The highly competitive landscape for cardiology and cardiac
surgery, and the ability to recruit recent residency graduates who
have been users of C-PACS.
• The demand to decrease costs for medical imaging services.
• The increased acceptance and adoption of standards that will
facilitate the capture, rendering, and transmission of various
types of medical images across digital imaging modalities and
between vendor PACS solutions.
• Continued favorable cost trends for on-line and archival storage,
including the impact of storage virtualization technologies.
▶▶ Bar Code Technology
This section tracks the use of bar code technology across eight
different hospital departments/functions. Bar coding technology is
most widely used in the laboratory as more than 85 percent of U.S.
hospitals had a laboratory bar coding system in place in 2012.
During this past year, the market penetration all of the bar code
technologies tracked by HIMSS Analytics increased. Medication
administration and pharmacy administration demonstrated the
largest increases, at eight and seven percent respectively (see Table
BC1). Bar code technology is least likely to be used for fixed assets/
equipment tracking, as only seven percent of U.S. hospitals use bar
codes in this area. The use of bar code technology for patient
registration applications is expected to grow as these applications
support a very key area of the hospital, point-of-care medication
administration.
With respect to bar coding purchasing plans, medication
administration once again tops the list (31 percent of all U.S.
hospitals) (see Table BC2). The projected use of the other bar
coding technologies increased from 2011 to 2012.
Ta ble BC1 | Bar Coding (Current)
Count
2010
Percent
Count
2011
Percent
Count
2012
Percent
165
3,442
1,981
1,868
390
2,602
2,098
3.91%
81.62%
46.98%
44.30%
9.25%
61.70%
49.75%
212
3,519
2,101
2,096
497
2,825
2,122
5.03%
83.45%
49.82%
49.70%
11.79%
66.99%
50.32%
281
3,605
2,207
2,447
594
3,119
2,153
6.66%
85.49%
52.34%
58.03%
14.09%
73.96%
51.06%
N=4,217
Fixed Assets/Equipment
Tracking
Laboratory
Medication Administration
Patient Registration
Pharmacy Administration
Radiology
Ta ble BC 2 | Bar Coding (Planned)
Count
2010
Percent
Count
2011
Percent
Count
2012
Percent
62
195
325
1,549
90
908
138
1.47%
4.62%
7.71%
36.73%
2.13%
21.53%
3.27%
96
209
351
1,468
120
848
145
2.28%
4.96%
8.32%
34.81%
2.85%
20.11%
3.44%
115
221
368
1,304
131
694
156
2.73%
5.24%
8.73%
30.92%
3.11%
16.46%
3.70%
N=4,217
Fixed Assets/Equipment
Tracking
Laboratory
Medication Administration
Patient Registration
Pharmacy Administration
Radiology
65
▶▶ Bar Code Technology con tinued
Use of bar coding technologies is expected to increase for a multiplicity
of reasons. For example, bar coding supports patient safety efforts
by ensuring hospitals follow the “five rights” of medication
administration (right patient, right dose, right drug, right time and
right route). Bar coding is also associated with automated medication
administration that is an “assistive technology” used in conjunction
with an eMAR, which is a Stage 2 Meaningful Use requirement for
any acute care hospital with an average daily census of greater than
nine patients.
The bar code technology market has been and will continue to be
• The drive for hospitals to implement the “five rights” of
medication administration and to improve patient safety through
information technology.
• The drive for hospitals to implement the “five rights” of
medication administration and to improve nurse satisfaction
and patient experience.
• Stage 2 ARRA Meaningful Use requirements which require
the use of assistive technologies in conjunction with an eMAR
for medication administration processes.
• The growing use of bar code usage in blood tracking and blood
administration.
• The need to effectively manage patient tracking and patient flows.
• The desire to improve supply chain management functions
throughout the hospital to reduce inventory and management
costs.
• Though a nascent market now, asset tracking and real time
location tracking with also drive some bar code technology
adoption.
• The lack of consistent standards for the technology of materials
packaging and medication packaging.
• The adoption of RFID technologies in patient tracking and
material management, which may begin to reduce some growth
of bar code technologies in these applications over the next
several years.
▶▶ Electronic Medical Record Environment
HIMSS Analytics monitors the following seven applications as
part of the EMR application suite: clinical data repository; clinical
decision support system; computerized practitioner order entry;
order entry; patient portal; physician documentation; physician
portal. These applications have the ability to significantly impact
clinical outcomes, patient safety and efficiency for hospitals if
implemented as part of a comprehensive change management
process and used directly by all clinicians, including physicians.
While nursing applications are also part of the EMR suite, we
have broken them out for separate analysis (please refer to the
Nursing IT section for additional information).
All of the applications in this suite grew in their market penetration
in the past year. The highest increases were for CPOE (over ten
percentage points), physician documentation (seven percentage
points) and physician portal (over five percentage points). All other
Ta ble E MR1 | Electronic Medical Record
N=4,217
2010
2011
Clinical Data Repository
88.24%
91.11%
Clinical Decision Support Systems (CDSS)
85.72%
88.62%
Computerized Practitioner Order Entry (CPOE)
56.58%
67.77%
Order Entry (includes Order Communication)
91.65%
93.64%
Patient Portal
41.71%
50.34%
Physician Documentation
53.17%
61.80%
Physician Portal
42.87%
50.75%
2012
94.00%
91.25%
78.35%
95.26%
54.59%
68.98%
56.27%
applications, except general order entry, increased by at least
2.5 percentage points (see Table EMR1). General order entry is
reaching market saturation (over 95 percent penetration) and may
become an obsolete application as hospitals adopt CPOE
applications in place of legacy systems. Clinical data repositories
are also nearing market saturation, rising to 94 percent in 2012.
The majority of purchases for CPOE and physician documentation
solutions will be made by hospitals that are planning to purchase
this technology for the first time. The remaining applications in the
EMR segment have more replacement than first time purchase plans
(see Table EMR2).
An evaluation of this market from 2011 to 2012 by hospital type
reveals the following highlights:
• CDR: the rural and critical hospital segments had the highest
growth rates between 2011 and 2012 at around seven percentage
points each, while single hospital systems showed growth of over
five percentage points (see Table EMR3). Academic medical
centers reached full market penetration in 2010 and have seen no
changes since then.
• Clinical decision support: the highest increases from 2011 to 2012
were in the rural and critical access segments, each at nearly
seven percentage points (see Table EMR4). Growth in the single
hospital segment was over 5.5 percentage points.
Ta ble E MR 2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
71
71.00%
Clinical Decision Support Systems (CDSS)
68
70.83%
50
30.86%
67
72.04%
Patient Portal
29
51.79%
51
40.48%
Physician Portal
29
64.44%
for the First Time
29
28
112
26
27
75
16
for the First Time
29.00%
29.17%
69.14%
27.96%
48.21%
59.52%
35.56%
N = Total Number of
Hospitals Planning
100
96
162
93
56
126
45
▶▶ Electronic Medical Record Environment con tinue d
• CPOE: all hospital segments except academic hospitals increased
CPOE implementation by at least eight percentage points (see
Table EMR5). At 96 percent, implementation is nearing market
saturation in the academic medical center segment. Rural
hospitals showed the highest increase with an 18 percentage point
gain from 2011 to 2012.
• Order entry: academic medical centers, medical surgical
hospitals, non-critical access hospitals, urban hospitals and the
multi-hospital system segments are highly saturated markets with
market penetration of more than 95 percent (see Table EMR6).
Critical access and rural hospitals indicated the highest growths
with approximately 4.5 percentage point increases.
• Patient Portal: from 2011 to 2012, there was an increase in market
penetration in each hospital segment (see Table EMR7).
Academic hospitals demonstrated the largest increase (six
percentage points), followed closely by single hospital systems
and critical access hospitals, each just over five percentage points.
• Physician documentation: all hospital segments demonstrated
growth from 2011 to 2012. Critical access, rural hospitals and
single hospital systems indicated at least a ten percentage point
increase (see Table EMR8).
• Physician portal: the academic medical center segment
demonstrated the greatest growth between 2011 and 2012 at almost
nine percentage points (see Table EMR9). All other hospital
segments showed increases of at least five percentage points.
Academic medical centers and larger medical/surgical hospitals
demonstrated the highest adoption rates in physician-focused
applications (e.g. CPOE, physician documentation, physician portal).
These organizations tend to have higher staffing levels of residents and
hospitalists, who are generally required to use the clinical applications
for patient care. Critical access and rural hospitals showed higher
adoption increases as they continue to expand their EMR application
capabilities and increasingly adopt the role of hospitalists.
Ta ble e mr3 | Clinical Data Repository
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
178
3,543
2,332
1,389
811
2,910
693
3,028
2,426
1,295
3,721
Percent
100.00%
87.72%
95.11%
78.70%
70.64%
94.82%
71.00%
93.43%
93.56%
79.74%
88.24%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,664
2,361
1,481
889
2,953
763
3,079
2,459
1,383
3,842
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
173
3,564
2,343
1,394
884
2,853
761
2,976
2,380
1,357
3,737
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
165
2,693
1,710
1,148
631
2,227
500
2,358
1,834
1,024
2,858
Percent
100.00%
90.72%
96.29%
83.91%
77.44%
96.22%
78.18%
95.00%
94.83%
85.16%
91.11%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
178
3,786
2,399
1,565
969
2,995
835
3,129
2,492
1,472
3,964
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
175
3,673
2,373
1,475
961
2,887
827
3,021
2,400
1,448
3,848
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
170
3,134
1,972
1,332
799
2,505
677
2,627
2,046
1,258
3,304
Percent
100.00%
93.74%
97.84%
88.67%
84.41%
97.59%
85.55%
96.54%
96.10%
90.64%
94.00%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble e mr4 | Clinical Decision Support System (CDSS)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
174
3,441
2,297
1,318
811
2,804
699
2,916
2,339
1,276
3,615
Percent
97.75%
85.19%
93.68%
74.67%
70.64%
91.37%
71.62%
89.97%
90.20%
78.57%
85.72%
2011
Percent
97.19%
88.24%
95.55%
78.98%
77.00%
92.96%
77.97%
91.82%
91.79%
83.56%
88.62%
2012
Percent
98.31%
90.94%
96.78%
83.57%
83.71%
94.07%
84.73%
93.21%
92.56%
89.16%
91.25%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble e mr5 | Computerized Practitioner Order Entry (CPOE)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
160
2,226
1,437
949
452
1,934
358
2,028
1,639
747
2,386
Percent
89.89%
55.11%
58.61%
53.77%
39.37%
63.02%
36.68%
62.57%
63.21%
46.00%
56.58%
2011
Percent
92.70%
66.67%
69.74%
65.04%
54.97%
72.56%
51.23%
72.76%
70.73%
63.05%
67.77%
2012
Percent
95.51%
77.59%
80.42%
75.47%
69.60%
81.62%
69.36%
81.06%
78.90%
77.46%
78.35%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
67
Ta ble e mr6 | Order Entry (includes Order Communication)
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
177
3,688
2,373
1,492
905
2,960
788
3,077
2,471
1,394
3,865
Percent
99.44%
91.31%
96.78%
84.53%
78.83%
96.45%
80.74%
94.94%
95.30%
85.84%
91.65%
2011
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,772
2,400
1,549
954
2,995
823
3,126
2,508
1,441
3,949
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
124
1,999
1,503
620
373
1,750
311
1,812
1,578
545
2,123
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
153
2,453
1,618
988
516
2,090
420
2,186
1,745
861
2,606
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
127
2,013
1,490
650
385
1,755
329
1,811
1,459
681
2,140
Percent
99.44%
93.39%
97.88%
87.76%
83.10%
97.59%
84.32%
96.45%
96.72%
88.73%
93.64%
2012
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
177
3,840
2,413
1,604
1,006
3,011
866
3,151
2,523
1,494
4,017
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
135
2,167
1,613
689
436
1,866
357
1,945
1,666
636
2,302
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
161
2,748
1,767
1,142
637
2,272
538
2,371
1,880
1,029
2,909
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Segment
Count
143
2,230
1,623
750
465
1,908
396
1,977
1,586
787
2,373
Percent
99.44%
95.07%
98.41%
90.88%
87.63%
98.11%
88.73%
97.22%
97.30%
92.00%
95.26%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble e mr7 | Patient Portal
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
109
1,650
1,259
500
298
1,461
241
1,518
1,347
412
1,759
Percent
61.24%
40.85%
51.35%
28.33%
25.96%
47.61%
24.69%
46.84%
51.95%
25.37%
41.71%
2011
Percent
69.66%
49.49%
61.30%
35.13%
32.49%
57.02%
31.86%
55.91%
60.86%
33.56%
50.34%
2012
Percent
75.84%
53.65%
65.78%
39.04%
37.98%
60.80%
36.58%
60.01%
64.25%
39.16%
54.59%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble e mr8 | Physician Documentation
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
145
2,097
1,383
859
393
1,849
316
1,926
1,560
682
2,242
Percent
81.46%
51.92%
56.40%
48.67%
34.23%
60.25%
32.38%
59.43%
60.16%
42.00%
53.17%
2011
Percent
85.96%
60.73%
65.99%
55.98%
44.95%
68.10%
43.03%
67.45%
67.30%
53.02%
61.80%
2012
Percent
90.45%
68.04%
72.06%
64.70%
55.49%
74.03%
55.12%
73.16%
72.50%
63.36%
68.98%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Ta ble e mr9 | Physician Portal
2010
Type
Academic/Teaching
Non- Academic
Med/Surg
Other
Critical Access
Rural
Urban
All
Segment
Count
119
1,689
1,296
512
280
1,528
242
1,566
1,262
546
1,808
Percent
66.85%
41.82%
52.85%
29.01%
24.39%
49.79%
24.80%
48.32%
48.67%
33.62%
42.87%
2011
Percent
71.35%
49.84%
60.77%
36.83%
33.54%
57.18%
33.71%
55.88%
56.27%
41.93%
50.75%
2012
Percent
80.34%
55.21%
66.19%
42.49%
40.51%
62.17%
40.57%
61.00%
61.16%
48.46%
56.27%
Total
Count
178
4,039
2,452
1,765
1,148
3,069
976
3,241
2,593
1,624
4,217
Analysis of the EMR market by bed size in 2012 indicates that
CPOE demonstrated the highest growth across almost the majority
of bed segments. The exceptions being the 301–400 and over 600
bed segments. CPOE and physician documentation showed five
percentage point growth in the 401–500 beds segment while CPOE,
patient portal and physician documentation showed six percentage
point growth in the 501–600 bed segment. The following provides
an analyses of growth from 2011 to 2012 by hospital bed size
(see Tables EMR10–EMR16):
• 0–100 beds: CPOE had the highest growth in this segment at
almost 13 percentage points, while physician documentation
grew by nearly ten percentage points. Physician portal showed
the third highest growth in this segment with a six percentage
point increase.
• 101–200 beds: CPOE adoption grew by nearly 11 percentage points,
followed by physician documentation (4.6 percentage points).
• 201–300 beds: the highest growth in the past year was for CPOE
(nearly eight percentage points) followed by physician portal
(nearly six percentage points).
• 301–400 beds: physician documentation and CPOE had similar
growth (nearly six percentage points) from 2011 to 2012.
Physician and patient portals also grew by more than five
percentage points in the past year.
• 401–500 beds: Use of CDR and clinical decision support software
is nearly universal in this bed segment, and there was no growth
in the past year. CPOE and patient portal each demonstrated
growth of at least five percentage points in the past year.
• 501–600 beds: Use of CDR, clinical decision support and order
entry software is universal in this bed segment. CPOE, physician
portal and patient portal each had a growth of six percentage
points in this segment.
• Over 600 beds: CDR, clinical decision support, CPOE and order
entry have achieved market saturation. The highest growth in this
segment was for physician portal (over eight percentage points),
followed by CPOE and patient portal (each over 4.5 percentage
points).
Ta ble E MR10
0–100 Beds
Clinical Decision Support
Systems (CDSS)
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communication)
Patient Portal
Physician Portal
2010
1,714
2011
2012
79.17% 1,828 84.43% 1,934 89.33%
1,659
76.63%
1,763
81.43%
1,859
85.87%
1,021
47.16%
1,298
59.95%
1,578
72.89%
1,853
643
934
626
85.59%
29.70%
43.14%
28.91%
1,928
807
1,124
819
89.05%
37.27%
51.92%
37.83%
1,990
896
1,336
951
91.92%
41.39%
61.71%
43.93%
Ta ble E MR11
101–200 Beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
765
2011
% of 802 Hospitals
95.39%
771 96.13%
2012
784
97.76%
743
92.64%
753
93.89%
764
95.26%
451
56.23%
536
66.83%
623
77.68%
774
405
452
400
96.51%
50.50%
56.36%
49.88%
780
489
529
457
97.26%
60.97%
65.96%
56.98%
784
515
566
488
97.76%
64.21%
70.57%
60.85%
Ta ble E MR12
201–300 Beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
475
2011
% of 483 Hospitals
98.34%
476 98.55%
2012
479
99.17%
466
96.48%
471
97.52%
472
97.72%
328
67.91%
376
77.85%
414
85.71%
474
259
322
274
98.14%
53.62%
66.67%
56.73%
477
310
366
312
98.76%
64.18%
75.78%
64.60%
480
334
384
340
99.38%
69.15%
79.50%
70.39%
Ta ble E MR13
301–400 Beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
2011
% of 312 Hospitals
312 100.00%
312 100.00%
2012
312 100.00%
299
95.83%
302
96.79%
303
97.12%
216
69.23%
253
81.09%
270
86.54%
311
174
197
194
99.68%
55.77%
63.14%
62.18%
310
202
220
213
99.36%
64.74%
70.51%
68.27%
309
218
238
227
99.04%
69.87%
76.28%
72.76%
Ta ble E MR14
401–500 Beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
2011
% of 188 Hospitals
188 100.00%
188 100.00%
2012
188 100.00%
185
98.40%
185
98.40%
185
98.40%
146
77.66%
157
83.51%
167
88.83%
186
106
123
133
98.94%
56.38%
65.43%
70.74%
187
125
136
143
99.47%
66.49%
72.34%
76.06%
187
135
145
151
99.47%
71.81%
77.13%
80.32%
Ta ble E MR15
501–600 Beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
2011
% of 116 Hospitals
116 100.00%
116 100.00%
116 100.00%
115
99.14%
115
99.14%
115
99.14%
93
80.17%
99
85.34%
106
91.38%
116 100.00%
71 61.21%
91 78.45%
80 68.97%
116 100.00%
80 68.97%
96 82.76%
83 71.55%
2012
116 100.00%
87 75.00%
100 86.21%
90 77.59%
Ta ble E MR16
Over 600 beds
Systems (CDSS)
Order Entry (CPOE)
Communication)
Patient Portal
Physician Portal
2010
2011
% of 151 Hospitals
151 100.00%
151 100.00%
2012
151 100.00%
148
98.01%
148
98.01%
150
99.34%
151 100.00%
139
92.05%
146
96.69%
151 100.00%
101 66.89%
123 81.46%
101 66.89%
151 100.00%
110 72.85%
135 89.40%
113 74.83%
151 100.00%
117 77.48%
140 92.72%
126 83.44%
69
Over three-quarters of all applications in the EMR segment were
contracted after 2000 (see Tables EMR17–EMR19). The majority of
contracts for patient portal and physician portal were signed in 2010
or later. The availability of ARRA incentives are expected to drive
higher adoption rates for CPOE, physician documentation, patient
portal and physician portal through 2016 as hospitals strive to meet
Meaningful Use criteria.
Ta ble E MR17
# for Contract
Range
Prior to 1990
17
1990 to 1994
89
1995 to 1999
386
2000 to 2004
838
2005 to 2009
795
2010 to 2012
529
Total
2,654
Clinical Decision Support System (CDSS)
Prior to 1990
15
1990 to 1994
85
1995 to 1999
332
2000 to 2004
694
2005 to 2009
760
2010 to 2012
523
Total
2,409
Prior to 1990
2
1990 to 1994
90
1995 to 1999
43
2000 to 2004
449
2005 to 2009
681
2010 to 2012
767
Total
2,032
Total
Responding
% of Total
Responding
2,654
2,654
2,654
2,654
2,654
2,654
2,654
0.64%
3.36%
14.56%
31.60%
29.98%
19.95%
100.00%
2,409
2,409
2,409
2,409
2,409
2,409
2,409
0.63%
3.56%
13.91%
29.07%
31.84%
21.91%
100.00%
2,032
2,032
2,032
2,032
2,032
2,032
2,023
0.10%
4.45%
2.13%
22.19%
33.66%
37.91%
100.00%
Total
Responding
% of Total
Responding
2,898
2,898
2,898
2,898
2,898
2,898
2,898
1.38%
6.80%
15.36%
31.54%
26.36%
18.56%
100.00%
181
181
181
181
181
181
181
0.00%
0.00%
0.55%
10.50%
14.36%
67.96%
100.00%
Ta ble E MR18
# for Contract
Range
Prior to 1990
40
1990 to 1994
197
1995 to 1999
445
2000 to 2004
914
2005 to 2009
764
2010 to 2012
538
Total
2,898
Patient Portal
Prior to 1990
0
1990 to 1994
0
1995 to 1999
1
2000 to 2004
19
2005 to 2009
38
2010 to 2012
123
Total
181
Ta ble E MR19
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
Physician Portal
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2009
2010 to 2012
Total
# for Contract
Range
Total
Responding
% of Total
Responding
3
92
48
457
563
677
1,840
1,840
1,840
1,840
1,840
1,840
1,840
1,840
0.16%
5.00%
2.61%
24.85%
30.61%
36.81%
100.00%
0
6
20
187
277
358
848
848
848
848
848
848
848
848
0.00%
0.71%
2.36%
22.08%
32.70%
42.27%
100.00%
The EMR environment market has been or will most likely be
• An increased focus on complying with ARRA Meaningful Use
Stage 1 and Stage 2 requirements and reporting criteria in order
to qualify for EMR adoption incentives and avoid Medicare
reimbursement penalties.
• While Stage 2 Meaningful Use has raised the bar on all the
Stage 1 measures for EMR use, clearly there is a strong intent to
increase “patient engagement” as a way to begin tackling the
chronic disease issues in the country. We see this as another
Meaningful Use driver for portal adoption.
• The increased need to acquire, manage and analyze clinical data for
business intelligence, outcomes improvement, pay for performance
incentive programs and government compliance reporting.
• Increased hiring of hospitalists who are expected to use CPOE and
physician documentation applications as a condition of employment.
• Increased purchasing of physician practices which are expected to
use CPOE and physician documentation applications as a
condition of purchase and employment.
• Increased pressures on hospitals by federal and state authorities
to participate in HIE and public health reporting activities, or the
desire of IDNs to actively participate in private HIEs.
• Tight capital markets which may impact the acquisition and
installation of EMR products through 2015, especially for small
community and critical access hospitals, in spite of the
availability of ARRA incentives.
• The continued resistance of attending physicians in a competitive
community hospital environment to the adoption and use of
CPOE and physician documentation applications.
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation
The acute care EMR Adoption ModelSM (EMRAM) was
developed by HIMSS Analytics to assess the status of clinical
system/EMR implementations in care delivery organizations
(CDOs), specifically hospitals. HIMSS Analytics collects data on
healthcare IT deployments and uses this data to measure the degree
of deployment of core technologies and processes that support an
electronic medical record environment. This model, which uses an
algorithm to score more than 5,300 U.S. acute care hospitals,
demonstrates consistent upward movement among U.S. hospitals
(see Figure EMRAM1). This same algorithm-based technique is
used to measure movement towards an EMR environment in
Canada, Europe, the Middle East and Asia.
EMR Adoption ModelSM: An EMR Market Transformation Assessment Tool
The stages of the model are as follows:
Stage 0: Some clinical automation may be present, but all three of
the major ancillary department systems for laboratory, pharmacy,
and radiology are not implemented.
Stage 1: All three of the major ancillary clinical systems (pharmacy,
laboratory and radiology) are installed.
Stage 2: Major ancillary clinical systems feed orders and results
data to a CDR that provides physician access for retrieving and
reviewing results. The CDR contains a controlled medical
vocabulary (CMV), and the clinical decision support/rules engine
(CDSS) for rudimentary conflict checking such as duplicate orders.
Information from document imaging systems may be linked to the
CDR at this stage.
Stage 3: Clinical documentation (e.g., vital signs, flow sheets,
nursing notes, and the eMAR) is required; care plan charting is
scored with extra points, and is implemented and integrated with
the CDR for at least one service or one unit in the hospital. Some
level of medical image access from radiology picture archive and
communication systems (R-PACS) is available to physicians via
the organization’s intranet or other secure networks outside of the
radiology department confines. If clinical documentation (e.g., vital
signs, flow sheets, nursing notes, and eMAR) is implemented for
one inpatient service area and completed the previous stages, then
this stage has been achieved.
Stage 4: CPOE for use by any clinician is added to the nursing
and CDR environment along with the second level of clinical
decision support capabilities related to evidence-based medicine
protocols and order sets. An organization is given credit for having
achieved this stage if one patient service area (excluding the
emergency department) has implemented CPOE and completed
the previous stages.
Stage 5: The closed-loop medication administration environment is
fully implemented in at least one patient care service area. The
eMAR and bar coding or other auto identification technology, such
as RFID, are implemented and integrated with CPOE and
pharmacy to support the five rights of medication administration
(right patient, right drug, right dose, right route and right time),
thereby maximizing point-of-care patient safety processes.
Stage 6: Full physician documentation/charting (using structured
templates) is implemented for at least one patient care service area
supported by clinical decision support. Level three of clinical
decision support is implemented, which provides guidance for all
clinician activities related to protocols and outcomes in the form of
variance and compliance alerts. A full complement of R-PACS
systems provides medical images to physicians via an intranet and
displaces all film-based images.
Stage 7: The hospital has a paperless EMR environment to support
patient care delivery. Patient data/information is easily exchanged
between the inpatient, out-patient, and emergency department
domains. All radiology images are digital and easily accessed by all
authorized clinicians. Clinical information can be readily analyzed
and reported on for quality and patient safety initiatives, and shared
via standardized electronic transactions with all entities within a
HIE (i.e., other hospitals, ambulatory clinics, sub-acute
environments, employers, payers and patients). This stage allows the
healthcare organization to support the true sharing and use of health
and wellness information by consumers and providers alike using
CCD, CCR, or state required transaction formats.
Scoring Format
An EMR score is represented by the following format—S.nnnn,
where “S” equals the current stage achieved for the model, and the
“.nnnn” represents the weighted score representing the
implementation of higher stage clinical applications that have been
implemented before the higher stage has been fully achieved. In this
model all applications in previous stages and the current stage must
be achieved before the current stage score is achieved. For example,
if a hospital has installed CPOE (Stage 4), but has not yet
implemented all of the components required for clinical
documentation used by nursing (Stage 3), then the hospital would be
scored as a Stage 2 hospital and the four digits after the stage
designation would identify the weighted points that had been
achieved for implementing CPOE (2.nnnn).
A comparison of the EMRAM scores for U.S. hospitals by
individual stage for the third quarter of 2012 as compared to year
end 2011 final numbers is shown in Figure EMRAM1. Continuing
trends from previous years, hospitals in Stages 4 through 6
increased from end of year 2011 to the Q3 of 2012, while the
percentage of hospitals in Stages 0 to 3 have decreased in the same
timeframe showing that hospitals are moving up the EMRAM
stages. The increase in the percentage of hospitals in Stages 4 to 6
can largely be attributed directly to the ARRA incentive and
meeting the Meaningful Use criteria. The number of U.S. Stage 7
hospitals increased slightly from 2011 to 2012, while the number of
U.S. hospitals in Stage 3 decreased by almost three percent. Stage 3
provides the foundation for advancing to more advanced stages of
clinical information system capabilities (e.g., CPOE, closed-loop
medication administration, and physician documentation).
71
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation con tinue d
Figure EMRAM1: US EMR Adoption Model
SM
Stage
Cumulative Capabilities
2011
Final
2012
Q3
Stage 7
Complete EMR; CCD transactions to share data; Data
warehousing; Data continuity with ED, ambulatory, OP
1.2%
1.8%
Stage 6
Physician documentation (structured templates),
full CDSS (variance & compliance), full R-PACS
5.2%
7.3%
Stage 5
Closed loop medication administration
8.4%
12.0%
Stage 4
CPOE, Clinical Decision Support (clinical protocols)
13.2%
14.2%
Stage 3
Nursing/clinical documentation (flow sheets), CDSS
(error checking), PACS available outside Radiology
44.9%
41.3%
Stage 2
CDR, Controlled Medical Vocabulary, CDS, may have
Document Imaging; HIE capable
12.4%
11.2%
Stage 1
Ancillaries - Lab, Rad, Pharmacy - All Installed
5.7%
4.8%
Stage 0
All Three Ancillaries Not Installed
9.0%
7.4%
N = 5,337
N = 5,319
Data from HIMSS AnalyticsTM Database ©2012
The EMRAM scores of U.S. hospitals have moved positively since
2008, as Stages 4 through 7 have increased while Stages 0 through
3 have decreased. The following is a representation of a five-year
trend (see Table EMRAM1):
Ta ble E MR A M1
Stage 7
Stage 6
Stage 5
Stage 4
Stage 3
Stage 2
Stage 1
Stage 0
N
2008 (Q4)
0.3%
0.5%
2.5%
2.5%
35.7%
31.4%
11.5%
15.6%
5,168
2009 (Q4)
0.7%
1.6%
3.8%
7.4%
50.9%
16.9%
7.2%
11.5%
5,235
2010 (Q4)
1.0%
3.2%
4.5%
10.5%
49.0%
14.6%
7.1%
11.5%
5,281
2011 (Q4)
1.2%
5.2%
8.4%
13.2%
44.9%
12.4%
5.7%
9.0%
5,337
2012 (Q3)
1.8%
7.3%
12.0%
14.2%
41.3%
11.2%
4.8%
7.4%
5,319
A more comprehensive evaluation of the U.S. hospital EMRAM
model is presented in the HIMSS Analytics’ Essentials of the U.S.
Hospital IT Market quarterly reports.
It is also worth noting that in 2012, seven critical access hospitals
(all with 25 and under bed size and all part of an integrated delivery
system) have attained Stage 7 status. Additionally, a free standing
hospital with 82 beds also achieved Stage 7. This clearly
demonstrates that achieving Stage 7 of the EMRAM model is
not exclusively the purview of large hospitals.
An evaluation of U.S. hospitals by type, bed size and region
(see Table EMRAM2) with 2012 data shows that:
• Among all hospital types, academic medical centers had the
highest mean and median EMRAM scores; this hospital segment
is also the only group that has both a median and mean score of
4.000. This is followed by general medical/surgical and urban
hospitals. This is unchanged from previous Annual Reports.
• A positive correlation continues between larger bed hospitals and
high EMRAM average and median scores. Hospitals in both the
501 to 600 bed segment and the over 600 bed segment categories
have achieved both a median and average score of at least four.
Hospitals with fewer than 100 beds have the lowest mean and
median scores.
• The New England region had the highest mean and median score
by region, as also reported in previous years. New England is also
the only region to have both a median and mean score of four.
The Mountain and West South Central regions have hospitals
with the lowest average and median scores. The East South
Central region is the only region that does not have a hospital that
has achieved Stage 7.
Ta ble E MR A M2
Segment
Hospital Type Segment
Academic/Teaching
Non-Academic
General Medical/Surgical
Others (Non-General Medical/Surgical)
Rural
Urban
IDS
Independent Hospital
Critical Access
Bed Segment
0–100 Beds
101–200 Beds
201–300 Beds
301–400 Beds
401–500 Beds
501–600 Beds
Over 600 beds
Regions (U.S. Census Defined)
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
All Hospitals
Total
Mean
Min
Max
Median
Number
4.5386
3.4372
3.7575
3.0686
2.8370
3.6660
3.5982
3.2731
2.8503
0.3870
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
7.0710
7.0710
7.0710
7.0710
7.0710
7.0710
7.0710
7.0710
7.0390
4.3270
3.3670
3.4300
3.2225
3.1990
3.4150
3.3900
3.3640
3.2100
207
5,112
3,177
2,142
1,193
4,126
3,387
1,932
1,333
3.0229
3.6841
4.0363
4.0817
4.1525
4.4725
4.5214
0.0000
0.0000
0.0000
0.0810
2.0540
2.1700
2.1020
7.0710
7.0710
7.0710
7.0710
7.0710
7.0710
7.0710
3.2220
3.4140
3.4620
3.4620
3.5340
4.3160
4.3000
2,779
970
613
400
222
144
191
3.7730
3.1427
3.6997
3.0790
4.3040
3.6038
3.6680
3.4461
3.0203
0.0000
0.0000
0.0050
0.0000
0.2400
0.0000
0.0000
0.0000
0.0000
7.0710
6.0710
7.0390
7.0630
7.0630
7.0710
7.0710
7.0710
7.0390
3.4380
3.3340
3.4150
3.2670
4.2310
3.3680
3.4225
3.4150
3.2310
843
447
481
421
199
583
790
713
839
3.4801
0.0000
7.0710
3.3830
5,319
Region Key for States:
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation con tinue d
An analysis of the EMRAM scores by individual U.S. state shows
that seven states (Rhode Island, Vermont, Maine, Minnesota,
Connecticut, Massachusetts and Iowa) have median scores above
4.0000. Montana and District of Columbia have median EMRAM
scores below 3, the lowest reported (see Table EMR3).
Ta ble E MR A M3
State
Rhode Island
Vermont
Maine
Minnesota
Connecticut
Massachusetts
Iowa
Delaware
Virginia
Maryland
Illinois
Wisconsin
Washington
New Jersey
Michigan
Indiana
Missouri
Alaska
Colorado
North Carolina
Alabama
Georgia
Florida
Pennsylvania
Oregon
South Carolina
Utah
South Dakota
Idaho
Tennessee
New York
Ohio
Hawaii
Kentucky
New Hampshire
West Virginia
California
Nebraska
Arizona
New Mexico
Texas
Louisiana
Oklahoma
Arkansas
Nevada
Mississippi
Wyoming
Kansas
North Dakota
District of Columbia
Montana
Mean
4.7805
4.9062
4.5703
4.1482
4.2186
4.3003
3.9563
4.3137
4.3354
4.1783
3.9257
3.9177
3.7755
3.7200
3.9086
3.6542
3.7895
3.7316
3.3341
3.5571
3.2861
3.4860
3.6388
3.7130
3.7692
3.5681
3.0502
3.3348
3.1915
3.2744
3.6785
3.5077
3.0211
3.2623
3.5188
3.2907
3.5652
3.0087
3.6851
3.0383
3.1401
2.8118
2.8168
2.9856
2.5724
2.6988
3.1957
2.5744
2.6142
2.6105
2.0988
Min
0.3870
3.4160
3.2070
0.0000
1.0790
0.2400
0.0050
2.6370
2.0390
0.0810
0.0450
0.0550
0.0000
0.1900
0.0050
0.0000
0.0250
0.0050
0.0150
0.0100
0.0000
0.0000
0.0640
0.0050
0.0420
0.2400
0.0000
0.0000
0.0000
0.0000
0.0850
0.0000
0.0050
0.0480
2.0860
0.0700
0.0000
0.0100
0.0610
0.0000
0.0000
0.0180
0.0000
0.0350
0.0000
0.0000
0.0200
0.0000
0.0250
1.0000
0.0000
Max
6.0710
6.0710
6.0710
7.0710
6.0710
7.0630
7.0710
7.0470
7.0710
6.0710
7.0710
7.0710
6.0710
6.0710
6.0710
7.0550
7.0550
6.0710
7.0470
6.0710
5.1640
6.0710
7.0710
7.0390
7.0230
6.0710
5.1180
6.0710
6.0560
6.0710
6.0710
7.0710
7.0470
6.0710
6.0470
6.0630
7.0710
7.0080
7.0630
6.0310
7.0390
6.0710
6.0710
6.0710
7.0160
6.0710
7.0390
6.0480
6.0710
4.2920
6.0310
Median
6.0320
5.1100
4.3140
4.2690
4.2300
4.2160
4.0230
3.6200
3.5400
3.5180
3.4700
3.4700
3.4540
3.4465
3.4395
3.4380
3.4310
3.4310
3.4300
3.4220
3.4220
3.4215
3.4175
3.4160
3.4150
3.4150
3.3830
3.3740
3.3580
3.3510
3.3500
3.3420
3.3420
3.3300
3.3260
3.3175
3.3085
3.2900
3.2820
3.2800
3.2570
3.2270
3.2150
3.2060
3.1700
3.1665
3.1620
3.1540
3.0900
2.6305
2.1670
Number
11
14
37
136
33
78
121
9
83
48
197
137
94
84
160
143
132
17
84
121
98
158
240
195
61
71
49
53
43
140
202
206
23
107
26
50
388
87
82
38
486
147
121
85
42
102
27
139
45
10
56
For additional information about EMRAM, go to the link
shown below:
http://www.himssanalytics.org/emram/index.aspx
The first incentive payments were issued in May 2011, for Meaningful
Use Stage 1 achievement measured in late 2010. Data that compares
the growth of EMR adoption over the five quarters that followed
showed an admirable growth in EMRAM Stages 5 and 6 of more
than 80 percent with more than 66 percent in Stage 7. Concomitantly,
there was a 16 percent to 27 percent decrease in Stages 0, 1 and 2, the
lower, elementary stages of the EMRAM. We believe this indicates
that the incentive program is clearly working to motivate hospitals to
invest in healthcare IT to improve quality and safety while earning
incentive payments. However, while the rate of progress is
commendable and vital to the long-term “health” of health care,
much more work remains to be accomplished if the government’s
goal of 70 percent of the U.S. healthcare providers is to achieve
meaningful criteria by the end of 2015 (see Figure EMRAM2).
Figure EMRAM2: US EMR Adoption Model
SM
Stage
2011
Q2
2012
Q3
Stage 7
Complete EMR; CCD transactions to share data; Data
warehousing; Data continuity with ED, ambulatory, OP
1.1%
1.8%
Stage 6
Physician documentation (structured templates),
full CDSS (variance & compliance), full R-PACS
4.0%
7.3%
Stage 5
Closed loop medication administration
6.1%
12.0%
Stage 4
CPOE, Clinical Decision Support (clinical protocols)
12.3%
14.2%
Stage 3
Nursing/clinical documentation (flow sheets), CDSS
(error checking), PACS available outside Radiology
46.3%
41.3%
Stage 2
CDR, Controlled Medical Vocabulary, CDS, may have
Document Imaging; HIE capable
13.7%
11.2%
Stage 1
Ancillaries - Lab, Rad, Pharmacy - All Installed
.6%
4.8%
Stage 0
All Three Ancillaries Not Installed
10.0%
7.4%
N = 5,310
N = 5,310
73
▶▶ Ambulatory (Hospital Owned/Managed) IT Environment
In 2012, HIMSS Analytics streamlined our data collection efforts in
the ambulatory market to focus on applications of greatest interest to
the IT vendor community. As a result, this report no longer includes
data on ambulatory laboratory, pharmacy and radiology systems, and
will instead just report on the following three applications: Ambulatory
EMR (A-EMR), Ambulatory PACS, and Practice Management.
Since the Meaningful Use definition will be introduced in three
stages through 2015, and providers can qualify for the full value of
the incentive if they are fully qualified before the end of 2012, it is
reasonable to assume that A-EMR first time purchases will continue
to increase over the next few years as the data in the following
tables demonstrates.
Of the applications tracked in the hospital-owned/managed ambulatory
IT market, the A-EMR software application market reflected the most
positive market penetration gains this past year (see Table AH1). It is
reasonable to assume that A-EMR growth can be traced to hospitals
and clinics having a better understanding of the ARRA Meaningful
Use metrics released in 2010. The ambulatory PACS market
penetration decreased by less than one percent this past year, while
practice management growth was negligible given this market
reflecting near market saturation levels (95 percent or better) in the
hospital owned/managed clinic environment.
However, if the demand continues to sustain, we remain concerned
about whether the industry has the number of implementation
professionals that will be required to meet the ARRA Meaningful
Use measurements for 2013 and beyond.
More than three-quarters of purchasing plans for practice
management applications are projected to be replacement purchases
(see Table AH2), whereas A-EMR and ambulatory PACS continue
to primarily reflect first time purchasers.
Ta ble A H1 | Ambulatory
N = 19,649
2010
2011
Ambulatory EMR
57.37%
62.71%
Ambulatory PACS*
62.32%
60.10%
Practice Management
96.62%
97.40%
*N = 3,461 only includes ambulatory facilities that offer on-site imaging
2012
70.04%
59.43%
97.43%
An evaluation of the urban vs. rural and multi- vs. single hospital
system ownership/management market segments of ambulatory
facilities provides the following insights:
• A-EMR: ambulatory facilities owned/managed by rural
hospitals demonstrated the highest growth year-over-year at
more than 11 percentage points (see Table AH3). Ambulatory
facilities owned/managed by a single hospital system segment
demonstrated growth of approximately ten percentage points.
Growth in the urban and multi-hospital owned/managed
segments was between five and seven percentage points.
• Ambulatory PACS: the rural market segment for ambulatory
facilities showed the highest growth rates, at just less than one
percentage point. Single hospital system owned/managed
ambulatory facilities had the largest market penetration decrease
of nearly three percentage points (see Table AH4).
Ta ble A H2 | 2012
# of Hospitals
% of Hospitals
with Installed
with Installed
Ambulatory EMR
85
23.04%
Ambulatory PACS
1
11.11%
Practice Management
119
78.81%
for the First Time
284
8
32
for the First Time
76.96%
88.89%
21.19%
N = Total Number of
Hospitals Planning
369
9
151
Ta ble A H3 | Ambulatory EMR
2010
Type
Rural
Urban
All
Segment
Count
1,093
10,180
7,562
3,711
11,273
Percent
50.70%
58.19%
59.54%
53.40%
57.37%
2011
Total
Count
2,156
17,493
12,700
6,949
19,649
Segment
Count
1,233
11,088
8,152
4,169
12,321
Total
Count
242
3,219
2,402
1,059
3,461
Segment
Count
99
1,981
1,462
618
2,080
Total
Count
2,156
17,493
12,700
6,949
19,649
Segment
Count
2,051
17,088
12,437
6,702
19,139
Percent
57.19%
63.39%
64.19%
59.99%
62.71%
2012
Total
Count
2,156
17,493
12,700
6,949
19,649
Segment
Count
1,483
12,279
8,885
4,877
13,762
Total
Count
242
3,219
2,402
1,059
3,461
Segment
Count
101
1,956
1,468
589
2,057
Total
Count
2,156
17,493
12,700
6,949
19,649
Segment
Count
2,052
17,093
12,403
6,742
19,145
Percent
68.78%
70.19%
69.96%
70.18%
70.04%
Total
Count
2,156
17,493
12,700
6,949
19,649
Ta ble A H4 | Ambulatory PACS*
2010
Segment
Type
Count
Rural
108
Urban
2,049
1,547
610
All
2,157
* Only includes ambulatory facilities doing imaging on site
Percent
44.63%
63.65%
64.40%
57.60%
62.32%
2011
Percent
40.91%
61.54%
60.87%
58.36%
60.10%
2012
Percent
41.74%
60.76%
61.12%
55.62%
59.43%
Total
Count
242
3,219
2,402
1,059
3,461
Ta ble A H5 | Practice Management
2010
Type
Rural
Urban
All
Segment
Count
2,033
16,951
12,337
6,647
18,984
Percent
94.29%
96.90%
97.14%
95.65%
96.62%
2011
Percent
95.13%
97.68%
97.93%
96.45%
97.40%
2012
Percent
95.18%
97.71%
97.66%
97.02%
97.43%
Total
Count
2,156
17,493
12,700
6,949
19,649
▶▶ Ambulatory (Hospital Owned/Managed) IT Environment con tinue d
• Practice management: market penetration for practice
management is over 95 percent in all segments. Growth for all
segments was less than one percentage point (see Table AH5).
More than three-quarters of the contracts for A-EMR were signed
between 2005 and 2012. Nearly 80 percent of ambulatory PACS
contracts were signed between 2000 and 2009 (see Table AH6).
More than half of the contract activity for practice management
solutions occurred in 2004 or prior. The applications contracted
before 2000 may be entering a stage when the hospitals begin to
evaluate them for replacement.
The impending deadline for conversion to ICD-10 diagnostic coding
will require a major upgrade to these legacy practice management
applications. The one year extension of the ICD-10 implementation
was welcomed by the physician community as this was the market
segment that needed more time to adapt to the new coding
requirement. In our view, the next two years will see an increase
in purchasing activity for updating practice management among
these facilities.
Ta ble A H9
# for Contract
Range
Ambulatory EMR
Prior to 1990
0
1990 to 1994
42
1995 to 1999
216
2000 to 2004
1,321
2005 to 2009
3,477
2010 to 2012
1,883
Total
6,939
Ambulatory PACS*
Prior to 1990
0
1990 to 1994
0
1995 to 1999
14
2000 to 2004
163
2005 to 2009
224
2010 to 2012
87
Total
488
Practice Management
Prior to 1990
129
1990 to 1994
455
1995 to 1999
1,521
2000 to 2004
3,253
2005 to 2009
2,972
2010 to 2012
1,741
Total
10,071
* Based on ambulatory facilities doing imaging on site
Total
Responding
% of Total
Responding
6,939
6,939
6,939
6,939
6,939
6,939
6,939
0.00%
0.61%
3.11%
19.04%
50.11%
27.14%
100.00%
488
488
488
488
488
488
488
0.00%
0.00%
2.87%
33.40%
45.90%
17.83%
100.00%
10,071
10,071
10,071
10,071
10,071
10,071
10,071
1.28%
4.52%
15.10%
32.30%
29.51%
17.29%
100.00%
The hospital owned/managed ambulatory IT application market
has been and will continue to be impacted through 2015 by:
• The need to comply with ARRA Meaningful Use criteria to
achieve funding for A-EMR implementations or recover A-EMR
investments already made.
• The need to facilitate the interoperable flow of information
between the acute care and ambulatory environments, as well as
with external HIE entities, which will be essential to receive
Meaningful Use incentive payments beyond Stage 1.
• The need to facilitate the interoperable flow of information
between the acute care and ambulatory environments for both
clinical and financial applications to support a shared savings /
bundled payment environment.
• The need to better track episodes of care for quality outcomes
and pay for performance reimbursement models, especially for
the ARRA Meaningful Use criteria, patient centered medical
home and ACOs.
• Completion of practice management system upgrades in time
for the ICD-10 implementation deadline.
• The likely increase use of hospital PACS systems by tethered
(ambulatory facilities owned, operated and/or managed by a
hospitals) ambulatory facilities and thus a decrease of free
standing PACS environments.
• Growing efforts of HIE projects, and the ability to create,
manage, and exchange patient summary data from all modalities
of patient care.
• Access to capital by hospitals to make application purchases for
their ambulatory environments (this will be easier for ambulatory
facilities owned by hospitals than for stand-alone/independent
clinics, which may drive further market consolidation of clinics
and ambulatory services and hospitals).
• Relaxation of the Stark Laws related to hospital subsidies for
ambulatory practice EMR purchases, which are set to expire
in 2013.
• Ongoing activity with respect to standards adoption and
government mandates to ensure interoperability will lead to
frequent version upgrades of installed products.
• Usability of HIT systems that will accommodate a variety of
clinical specialties in addition to primary care clinicians.
• Consumer demands for personal health information and patient
safety derived from the A-EMR and the provisions of Meaningful
Use Stage 2 to increase patient engagement.
• Increase in consumer demands to have emerging technologies
(i.e. mobile health or mHealth) available to communicate with
clinicians and manage their healthcare.
• Shortages of trained HIT professionals available to assist
ambulatory clinics in meeting the implementation and reporting
Meaningful Use Requirements.
75
The Ambulatory EMR Adoption ModelSM
HIMSS Analytics launched the Ambulatory EMR Adoption
ModelSM (A-EMRAM) in 2012 to monitor EMR adoption in
ambulatory settings. Since there is such wide variation in ambulatory
care settings, we strive to apply the A-EMRAM to the following
care delivery environment: where there is a patient and care giver
encounter where the care giver is licensed to asses, diagnose,
document findings and impressions, generate orders and prescribe
medications. This patient and care giver encounter does not
necessarily have to be face to face, but it must include a care giver
whose license and scope of practice includes the ability to asses,
diagnose, document findings and impressions, generate orders and
prescribe medications. Similar to the hospital EMRAM, this model
uses an algorithm to score ambulatory facilities owned, operated
and/or managed by a hospital (a.k.a. tethered facility). The
A-EMRAM creates a framework for dialogue among ambulatory
facilities by focusing on the systems which will provide higher levels
of access, quality, efficiency and safety.
Ambulatory EMR Adoption ModelSM
The stages of the model are as follows:
Scoring Format
An Ambulatory EMR score is represented by the following
format—S.nnnn, where “S” equals the current stage achieved for
the model, and the “.nnnn” represents the weighted score
representing the implementation of higher stage clinical applications
and functions that have been implemented before the higher stage
has been fully achieved. In this model all applications and functions
in previous stages and the current stage must be achieved before the
current stage score is achieved. For example, if an ambulatory
facility uses electronic messaging for intra-office communication
(Stage 3), but has not yet implemented all of the components
required for an Ambulatory EMR (Stage 2), then the ambulatory
facility would be scored as a Stage 2 ambulatory and the four digits
after the stage designation would identify the weighted points that
had been achieved for implementing intra-office electronic
messaging (2.nnnn). As with the hospital EMRAM, there is a
validation process for Stage 6 and Stage 7 ambulatories to confirm
the facility’s capabilities.
Fig. AEMRAM1: Ambulatory EMR Adoption Model
SM
2012
Q3
Stage 0: There is no EMR at all; paper charts are the only means
of storing and accessing clinical information (even if there is a
computerized billing system).
Stage
Stage 7
HIE capable, sharing of data between the EMR and
community based EHR, business and clinical intelligence
0.00%
Stage 1: Access to limited clinical information available through
computers for doctors and nurses; information is from multiple
data sources, no CDR functionality.
Stage 6
Advanced clinical decision support, proactive care
management, structured messaging
0.81%
Stage 5
Personal health record, online tethered patient portal
2.13%
Stage 2: Computers may be at point-of-care; orders and results
are beginning to feed a CDR; results from outside facilities made
available on-line.
Stage 4
CPOE, use of structured data for accessibility in EMR and
internal and external sharing of data
0.24%
Stage 3
Electronic messaging, computers have replaced the paper
chart, clinical documentation and clinical decision support
7.59%
Stage 3: Nursing/clinical documentation charting includes vitals,
nursing intake assessment, encounter procedures with clinical
decision support; electronic messaging utilized; computers have
replaced paper charts; Problem lists, e-prescribing utilized and all
medications tracked for medication reconciliation.
Stage 2
Beginning of a CDR with orders and results, computers may
be at point-of-care, access to results from outside facilities
Stage 2
Desktop access to clinical information, unstructured data
multiple data sources, intra-office/informal messaging
4.29%
Stage 0
Paper chart based
53.77%
Stage 4: CPOE and physician documentation; discrete structured
data used in EMR; electronic growth charts supported where
appropriate, data shared both internally and externally.
Stage 5: Online patient portal; personal health record created.
Stage 6: Advanced clinical decision support is implemented which
provides guidance for all clinician activities related to protocols and
outcomes in the form of variance and compliance alerts; structured
messaging in use for communication; proactive care management;
follow-up notices sent directly to patients are initiated by flags set
by provider.
Stage 7: Patient data/information is easily exchanged between the
inpatient, out-patient, and emergency department domains. Clinical
information can be readily analyzed and reported on for quality and
patient safety initiatives, and shared via standardized electronic
transactions with all entities within a HIE (i.e., hospitals, other
ambulatory clinics, sub-acute environments, employers, payers and
patients).
30.54%
N = 14,872
An overall profile of A-EMRAM scores by tethered U.S.
ambulatory facilities for the third quarter of 2012 is shown in Figure
AEMRAM1. The majority of ambulatory facilities (53.8 percent)
still rely on paper based charts. Thirty (30) percent of scored
ambulatories are Stage 3, showing increased use of computers for
documenting care. No ambulatory site has achieved Stage 7 and less
than one percent of all scored facilities have reached Stage 6. In
subsequent Annual Reports, comparison between years will be made.
An evaluation of U.S. ambulatories by healthcare system type and
region (see Table AEMRAM1) with 2012 data shows that:
• Ambulatory facilities that are part of an IDS had the highest
mean and median A-EMRAM scores compared to facilities that
are associated with single hospital organization. Nearly twothirds of all ambulatory facilities included in this sample are part
of a multi-hospital healthcare system.
• The West North Central region had the highest mean score by
region. New England had the highest median score and the
second highest mean score. The lowest average score is in the
East South Central region. The lowest median score was seen in
the East South Central and West South Central regions.
Ta ble A E MR A M1
Segment
Hospital Type Segment
IDS
Independent Hospital
Regions (U.S. Census Defined)
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
All Ambulatories
Total
Ta ble A E MR A M2
Mean
Min
Median
Number
1.20346 0.00000 6.21500 0.15500
0.98925 0.00000 6.17500 0.06600
9,427
5,445
1.24456
0.77785
1.01284
1.11020
1.28528
1.16493
1.04261
1.34047
0.78774
0.18700
0.03100
0.06400
1.03200
1.03500
0.25800
0.05400
1.03200
0.03100
3,154
713
1,947
893
995
1,477
2,344
2,183
1,166
1.12503 0.00000 6.21500 0.10800
14,872
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
Max
6.19500
5.14000
3.26900
3.26600
3.21200
6.17500
5.21500
6.19500
6.21500
Region Key for States:
An evaluation of the A-EMRAM scores by individual U.S. state
reveals that 16 states have median scores above 2.00000. Virginia,
Maine and New Hampshire have the highest median scores. The
District of Columba, Minnesota and Virginia each have average
scores above 2.00000, the three highest average A-EMRAM.
Rhode Island has the lowest mean and median scores and is ranked
50th of all the U.S. states and District of Columbia (see Table
AEMRAM2).
For additional information about A-EMRAM, go to the link
shown below:
http://www.himssanalytics.org/emram/AEMRAM.aspx
The year 2011 marked the beginning of the period of payout for
ARRA’s EMR adoption incentives and measures of activity during
the latter half of 2010 suggest that the rate of EMR acquisition and
implementation is escalating and we anticipate this trend will
further accelerate in 2013. However, while the rate of progress is
commendable and vital to the long-term “health” of health care,
much more work remains to be accomplished if the government’s
goal of 70 percent of the U.S. healthcare providers is to achieve
meaningful criteria by the end of 2015.
State
Virginia
Maine
New Hampshire
Wisconsin
Hawaii
New Mexico
Idaho
Minnesota
Utah
District of Columbia
Iowa
Pennsylvania
Oregon
Ohio
North Dakota
Washington
Massachusetts
Maryland
Nevada
Illinois
Connecticut
South Dakota
South Carolina
Oklahoma
California
Indiana
Arkansas
Montana
Missouri
New York
Wyoming
Michigan
Mississippi
Vermont
Arizona
Colorado
Nebraska
Florida
Georgia
Kentucky
North Carolina
Kansas
Tennessee
Louisiana
Texas
West Virginia
Alabama
Alaska
New Jersey
Delaware
Rhode Island
Mean
2.13581
1.68731
1.61433
1.58376
1.73169
1.29698
1.49682
2.30576
1.94325
2.60462
1.32649
1.23048
1.41315
1.22700
1.75407
1.29264
1.17901
1.49273
1.06246
1.60910
0.81581
1.00295
0.36012
0.71163
1.04695
0.99505
0.38573
0.38526
1.07922
0.92832
1.05947
0.60603
0.87734
0.80876
0.62123
0.92707
0.70725
0.53492
0.82164
0.79596
0.71442
0.68019
0.88289
1.50221
0.74376
0.80465
0.51024
0.52082
0.37095
0.14792
0.02520
Min
0.00000
0.00000
0.01100
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
Max
5.21500
3.11200
3.21200
6.19500
3.26600
2.25500
3.17600
6.19500
2.07100
5.14500
3.13000
3.23600
3.26600
5.14000
6.19500
4.12700
3.20600
5.14500
2.04900
6.16500
3.14700
3.18600
2.08300
2.21500
6.17500
2.17400
3.23100
2.12300
6.18500
3.26900
3.13000
5.12000
3.20900
3.18400
3.19500
3.26600
2.21300
3.22000
3.26600
5.14000
3.13000
6.18500
2.23300
6.21500
6.19500
2.24600
2.23300
2.06000
2.13500
2.13500
0.05900
Median
2.27100
2.12000
2.11700
2.06200
2.06000
2.05800
2.05600
2.05500
2.05400
2.03900
2.03900
2.03700
2.03200
2.01950
2.01000
2.00500
1.05600
1.04900
1.04500
1.03500
0.52650
0.12000
0.08900
0.08100
0.07600
0.07600
0.07600
0.06400
0.06300
0.04800
0.04300
0.04000
0.03900
0.03900
0.03900
0.03500
0.03450
0.03200
0.03100
0.03100
0.03100
0.03100
0.03050
0.03000
0.03000
0.02300
0.01800
0.01100
0.01100
0.01100
0.01100
Number
432
200
203
597
29
50
138
502
156
21
308
932
205
617
81
370
383
219
59
874
131
223
289
249
851
438
167
82
657
805
30
628
174
68
195
183
191
342
429
216
493
221
175
157
593
80
148
22
210
39
10
77
▶▶ Appendix
Applications
0–100 Beds
2011
2012
% of 2,165 hospitals % of 2,165 hospitals
101–200 Beds
2011
2012
% of 802 hospitals
% of 802 hospitals
201–300 Beds
2011
2012
% of 483 hospitals
% of 483 hospitals
Abstracting
2,031
93.81%
2,057
95.01%
798
99.50%
801
99.88%
483
100.00%
483
100.00%
Accounts Payable
2,160
99.77%
2,160
99.77%
802
100.00%
802
100.00%
483
100.00%
483
100.00%
ADT/Registration
2,152
99.40%
2,152
99.40%
801
99.88%
801
99.88%
483
100.00%
483
100.00%
734
33.90%
819
37.83%
607
75.69%
625
77.93%
437
90.48%
441
91.30%
Bed Management
510
23.56%
586
27.07%
323
40.27%
368
45.89%
263
54.45%
285
59.01%
1,769
81.71%
1,803
83.28%
779
97.13%
782
97.51%
475
98.34%
475
98.34%
Blood Bank
963
44.48%
963
44.48%
682
85.04%
690
86.03%
458
94.82%
460
95.24%
1,597
73.76%
1,647
76.07%
724
90.27%
725
90.40%
441
91.30%
441
91.30%
694
32.06%
789
36.44%
408
50.87%
443
55.24%
255
52.80%
278
57.56%
128
5.91%
143
6.61%
334
41.65%
357
44.51%
300
62.11%
316
65.42%
Budgeting
Cardiology–CT (Computerized Tomography)
124
5.73%
144
6.65%
234
29.18%
257
32.04%
189
39.13%
203
42.03%
232
10.72%
273
12.61%
340
42.39%
377
47.07%
273
56.52%
284
58.80%
109
5.03%
129
5.96%
202
25.19%
226
28.18%
185
38.30%
196
40.58%
134
6.19%
157
7.25%
207
25.81%
232
28.93%
174
36.02%
193
39.96%
Cardiology Information System
348
16.07%
384
17.74%
520
64.84%
527
65.71%
378
78.26%
382
79.09%
Case Mix Management
1,500
69.28%
1,547
71.45%
727
90.65%
731
91.15%
441
91.30%
443
91.72%
Chart Deficiency
1,857
85.77%
1,908
88.13%
791
98.63%
796
99.25%
481
99.59%
482
99.79%
1,824
84.25%
1,864
86.10%
789
98.38%
787
98.13%
476
98.55%
474
98.14%
1,828
84.43%
1,934
89.33%
771
96.13%
784
97.76%
476
98.55%
479
99.17%
Clinical Decision Support System (CDSS)
1,763
81.43%
1,859
85.87%
753
93.89%
764
95.26%
471
97.52%
472
97.72%
293
13.53%
199
9.19%
140
17.46%
99
12.34%
109
22.57%
85
17.60%
1,298
59.95%
1,578
72.89%
536
66.83%
623
77.68%
376
77.85%
414
85.71%
Contract Management
1,193
55.10%
1,258
58.11%
622
77.56%
638
79.55%
390
80.75%
397
82.19%
Cost Accounting
1,228
56.72%
1,265
58.43%
615
76.68%
627
78.18%
408
84.47%
407
84.27%
Credit/Collections
1,889
87.25%
1,937
89.47%
776
96.76%
780
97.26%
465
96.27%
469
97.10%
755
34.87%
859
39.68%
437
54.49%
467
58.23%
280
57.97%
297
61.49%
581
26.84%
682
31.50%
363
45.26%
399
49.75%
249
51.55%
271
56.11%
DBMS
1,149
53.07%
1,194
55.15%
615
76.68%
628
78.30%
381
78.88%
392
81.16%
Dictation
1,832
84.62%
1,880
86.84%
779
97.13%
784
97.76%
471
97.52%
474
98.14%
544
25.13%
640
29.56%
382
47.63%
419
52.24%
285
59.01%
310
64.18%
50.93%
Disaster Recovery
719
33.21%
787
36.35%
358
44.64%
410
51.12%
217
44.93%
246
Document Management
1,335
61.66%
1,429
66.00%
614
76.56%
646
80.55%
403
83.44%
413
85.51%
EDI-Cleaninghouse Vendor
1,770
81.76%
1,842
85.08%
699
87.16%
717
89.40%
422
87.37%
432
89.44%
1,031
47.62%
1,259
58.15%
485
60.47%
531
66.21%
315
65.22%
325
67.29%
1,544
71.32%
1,730
79.91%
651
81.17%
700
87.28%
428
88.61%
443
91.72%
1,355
62.59%
1,518
70.12%
709
88.40%
730
91.02%
459
95.03%
469
97.10%
Encoder
2,026
93.58%
2,048
94.60%
799
99.63%
801
99.88%
483
100.00%
483
100.00%
Encryption
997
46.05%
1,129
52.15%
524
65.34%
568
70.82%
330
68.32%
359
74.33%
Enterprise Master Person Index (EMPI)
900
41.57%
956
44.16%
482
60.10%
514
64.09%
297
61.49%
311
64.39%
335
15.47%
376
17.37%
204
25.44%
229
28.55%
152
31.47%
169
34.99%
1,228
56.72%
1,280
59.12%
567
70.70%
577
71.95%
344
71.22%
353
73.08%
577
26.65%
639
29.52%
323
40.27%
342
42.64%
217
44.93%
237
49.07%
Firewall
1,346
62.17%
1,455
67.21%
609
75.94%
635
79.18%
382
79.09%
397
82.19%
General Ledger
2,159
99.72%
2,159
99.72%
802
100.00%
802
100.00%
483
100.00%
483
100.00%
Financial Modeling
Infection Surveillance System
432
19.95%
571
26.37%
252
31.42%
317
39.53%
200
41.41%
241
49.90%
1,663
76.81%
1,636
75.57%
600
74.81%
592
73.82%
381
78.88%
372
77.02%
Intensive Care
746
34.46%
816
37.69%
538
67.08%
568
70.82%
360
74.53%
385
79.71%
Interface Engines
967
44.67%
1,053
48.64%
551
68.70%
580
72.32%
363
75.16%
374
77.43%
18.84%
119
5.50%
141
6.51%
118
14.71%
134
16.71%
83
17.18%
91
331
15.29%
406
18.75%
223
27.81%
263
32.79%
179
37.06%
202
41.82%
Laboratory Information System
2,094
96.72%
2,117
97.78%
802
100.00%
802
100.00%
483
100.00%
483
100.00%
2,060
95.15%
2,077
95.94%
799
99.63%
799
99.63%
483
100.00%
482
99.79%
1,072
49.52%
1,143
52.79%
540
67.33%
576
71.82%
328
67.91%
342
70.81%
910
42.03%
1,281
59.17%
402
50.12%
497
61.97%
294
60.87%
317
65.63%
1,356
62.63%
1,416
65.40%
757
94.39%
759
94.64%
472
97.72%
473
97.93%
826
38.15%
999
46.14%
426
53.12%
478
59.60%
285
59.01%
310
64.18%
Microbiology
Nurse Call System
993
45.87%
970
44.80%
614
76.56%
615
76.68%
417
86.34%
414
85.71%
1,622
74.92%
1,792
82.77%
695
86.66%
726
90.52%
441
91.30%
452
93.58%
627
28.96%
677
31.27%
541
67.46%
564
70.32%
348
72.05%
362
74.95%
301–400 Beds
2011
2012
% of 312 hospitals
% of 312 hospitals
401–500 Beds
2011
2012
% of 188 hospitals
% of 188 hospitals
501–600 Beds
2011
2012
% of 116 hospitals
% of 116 hospitals
Over 600 beds
2011
2012
% of 151 hospitals
% of 151 hospitals
309
99.04%
310
99.36%
188
100.00%
188
100.00%
116
100.00%
115
99.14%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
115
99.14%
115
99.14%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
286
91.67%
294
94.23%
173
92.02%
174
92.55%
113
97.41%
114
98.28%
148
98.01%
148
98.01%
196
62.82%
207
66.35%
125
66.49%
129
68.62%
77
66.38%
84
72.41%
126
83.44%
132
87.42%
308
98.72%
309
99.04%
186
98.94%
186
98.94%
114
98.28%
114
98.28%
147
97.35%
148
98.01%
300
96.15%
301
96.47%
182
96.81%
183
97.34%
114
98.28%
114
98.28%
145
96.03%
147
97.35%
292
93.59%
291
93.27%
180
95.74%
180
95.74%
111
95.69%
111
95.69%
142
94.04%
142
94.04%
183
58.65%
195
62.50%
110
58.51%
120
63.83%
75
64.66%
77
66.38%
96
63.58%
103
68.21%
218
69.87%
234
75.00%
154
81.91%
155
82.45%
100
86.21%
99
85.34%
128
84.77%
130
86.09%
130
41.67%
140
44.87%
104
55.32%
106
56.38%
63
54.31%
65
56.03%
90
59.60%
98
64.90%
210
67.31%
222
71.15%
143
76.06%
150
79.79%
92
79.31%
92
79.31%
125
82.78%
128
84.77%
139
44.55%
146
46.79%
104
55.32%
109
57.98%
65
56.03%
70
60.34%
91
60.26%
101
66.89%
60.93%
126
40.38%
133
42.63%
93
49.47%
100
53.19%
66
56.90%
68
58.62%
85
56.29%
92
255
81.73%
264
84.62%
166
88.30%
168
89.36%
101
87.07%
102
87.93%
144
95.36%
143
94.70%
280
89.74%
280
89.74%
174
92.55%
174
92.55%
101
87.07%
104
89.66%
145
96.03%
146
96.03%
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
115
99.14%
151
100.00%
151
309
99.04%
308
98.72%
183
97.34%
182
96.81%
115
99.14%
113
97.41%
147
97.35%
147
97.35%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
166
100.00%
151
100.00%
151
100.00%
302
96.79%
303
97.12%
185
98.40%
185
98.40%
115
99.14%
115
99.14%
148
98.01%
150
99.34%
67
21.47%
52
16.67%
47
25.00%
36
19.15%
25
21.55%
26
22.41%
43
28.48%
42
27.81%
253
81.09%
270
86.54%
157
83.51%
167
88.83%
99
85.34%
106
91.38%
139
92.05%
146
96.69%
255
81.73%
264
84.62%
164
87.23%
163
86.70%
95
81.90%
100
86.21%
130
86.09%
134
88.74%
273
87.50%
272
87.18%
170
90.43%
170
90.43%
109
93.97%
109
93.97%
141
93.38%
140
92.72%
296
94.87%
297
95.19%
183
97.34%
182
96.81%
111
95.69%
111
95.69%
146
96.69%
147
97.35%
201
64.42%
210
67.31%
124
65.96%
133
70.74%
67
57.76%
69
59.48%
114
75.50%
117
77.48%
170
54.49%
179
57.37%
99
52.66%
111
59.04%
58
50.00%
65
56.03%
112
74.17%
120
79.47%
255
81.73%
260
83.33%
158
84.04%
163
86.70%
98
84.48%
100
86.21%
133
88.08%
136
90.07%
306
98.08%
309
99.04%
181
96.28%
183
97.34%
113
97.41%
113
97.41%
142
94.04%
145
96.03%
196
62.82%
208
66.67%
118
62.77%
126
67.02%
78
67.24%
86
74.14%
99
65.56%
112
74.17%
135
43.27%
150
48.08%
84
44.68%
97
51.60%
54
46.55%
64
55.17%
87
57.62%
94
62.25%
263
84.29%
267
85.58%
168
89.36%
169
89.89%
97
83.62%
103
88.79%
139
92.05%
141
93.38%
281
90.06%
285
91.35%
162
86.17%
166
88.30%
104
89.66%
106
91.38%
139
92.05%
144
95.36%
212
67.95%
224
71.79%
134
71.28%
138
73.40%
80
68.97%
85
73.28%
105
69.54%
110
72.85%
280
89.74%
286
91.67%
181
96.28%
183
97.34%
111
95.69%
111
95.69%
140
92.72%
145
96.03%
292
93.59%
295
94.55%
183
97.34%
183
97.34%
107
92.24%
108
93.10%
151
100.00%
151
100.00%
310
99.36%
311
99.68%
188
100.00%
188
100.00%
116
100.00%
115
99.14%
151
100.00%
151
100.00%
209
66.99%
225
72.12%
131
69.68%
140
74.47%
75
64.66%
84
72.41%
108
71.52%
116
76.82%
202
64.74%
209
66.99%
121
64.36%
127
67.55%
74
63.79%
77
66.38%
121
80.13%
124
82.12%
120
38.46%
132
42.31%
78
41.49%
84
44.68%
55
47.41%
58
50.00%
76
50.33%
83
54.97%
230
73.72%
235
75.32%
139
73.94%
141
75.00%
86
74.14%
87
75.00%
119
78.81%
119
78.81%
160
51.28%
166
53.21%
107
56.91%
108
57.45%
71
61.21%
75
64.66%
81
53.64%
89
58.94%
237
75.96%
244
78.21%
152
80.85%
157
83.51%
84
72.41%
90
77.59%
122
80.79%
126
83.44%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
115
99.14%
115
99.14%
151
100.00%
151
100.00%
69.54%
128
41.03%
156
50.00%
91
48.40%
102
54.26%
53
45.69%
65
56.03%
89
58.94%
105
235
75.32%
233
74.68%
141
75.00%
137
72.87%
95
81.90%
92
79.31%
122
80.79%
117
77.48%
220
70.51%
227
72.76%
143
76.06%
150
79.79%
99
85.34%
101
87.07%
133
88.08%
138
91.39%
248
79.49%
248
79.49%
162
86.17%
163
86.70%
102
87.93%
104
89.66%
136
90.07%
142
94.04%
81
25.96%
86
27.56%
52
27.66%
53
28.19%
34
29.31%
35
30.17%
80
52.98%
82
54.30%
139
44.55%
148
47.44%
83
44.15%
98
52.13%
54
46.55%
61
52.59%
91
60.26%
100
66.23%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
211
67.63%
224
71.79%
134
71.28%
138
73.40%
75
64.66%
84
72.41%
104
68.87%
111
73.51%
186
59.62%
208
66.67%
135
71.81%
142
75.53%
77
66.38%
88
75.86%
107
70.86%
121
80.13%
307
98.40%
306
98.08%
187
99.47%
187
99.47%
113
97.41%
113
97.41%
149
98.68%
150
99.34%
168
53.85%
189
60.58%
105
55.85%
116
61.70%
66
56.90%
77
66.38%
94
62.25%
106
70.20%
288
92.31%
288
92.31%
169
89.89%
166
88.30%
108
93.10%
110
94.83%
142
94.04%
144
95.36%
287
91.99%
291
93.27%
177
94.15%
180
95.74%
112
96.55%
113
97.41%
145
96.03%
149
98.68%
241
77.24%
241
77.24%
150
79.79%
150
79.79%
96
82.76%
98
84.48%
130
86.09%
131
86.75%
79
▶▶ Appendix con tinued
0–100 Beds
2011
2012
Applications
Operating Room (Surgery)–Post-Operative
101–200 Beds
2011
2012
% of 802 hospitals
% of 802 hospitals
201–300 Beds
2011
2012
% of 483 hospitals
% of 483 hospitals
987
45.59%
1,109
51.22%
633
78.93%
656
81.80%
409
84.68%
420
Operating Room (Surgery)–Pre-Operative
1,037
47.90%
1,149
53.07%
660
82.29%
678
84.54%
434
89.86%
443
91.72%
OR Scheduling
1,078
49.79%
1,185
54.73%
696
86.78%
705
87.91%
452
93.58%
458
94.82%
Order Entry (includes Order Communications)
1,928
89.05%
1,990
91.92%
780
97.26%
784
97.76%
588
98.76%
480
99.38%
1,247
57.60%
1,330
61.43%
660
82.29%
677
84.41%
407
84.27%
417
86.34%
474
21.89%
548
25.31%
286
35.66%
290
36.16%
196
40.58%
203
42.03%
2,158
99.68%
2,159
99.72%
802
100.00%
802
100.00%
482
99.79%
483
100.00%
Patient Acuity (formerly Nurse Acuity)
Patient Billing
Patient Portal
86.96%
807
37.27%
896
41.39%
489
60.97%
515
64.21%
310
64.18%
334
69.15%
Patient Scheduling
2,043
94.36%
2,066
95.43%
794
99.00%
797
99.38%
480
99.38%
482
99.79%
Payroll
2,125
98.15%
2,134
98.57%
800
99.75%
800
99.75%
482
99.79%
482
99.79%
1,762
81.39%
1,795
82.91%
785
97.88%
785
97.88%
477
98.76%
478
98.96%
Pharmacy Management System
1,996
92.19%
2,043
94.36%
801
99.88%
802
100.00%
483
100.00%
483
100.00%
1,124
51.92%
1,336
61.71%
529
65.96%
566
70.57%
366
75.78%
384
79.50%
819
37.83%
951
43.93%
457
56.98%
488
60.85%
312
64.60%
340
70.39%
Physician Portal
Radiology–Angiography
926
42.77%
960
44.34%
649
80.92%
661
82.42%
442
91.51%
447
92.55%
Radiology–Computed Radiography (CR)
1,673
77.27%
1,751
80.88%
748
93.27%
753
93.89%
457
94.62%
460
95.24%
Radiology–Computerized Tomography (CT)
1,697
78.38%
1,760
81.29%
749
93.39%
755
94.14%
469
97.10%
472
97.72%
Radiology–Digital Fluoroscopy (DF)
1,240
57.27%
1,301
60.09%
705
87.91%
720
89.78%
447
92.55%
450
93.17%
75.16%
Radiology–Digital Mammography
956
44.16%
1,087
50.21%
558
69.58%
592
73.82%
343
71.01%
396
Radiology–Digital Radiography (DR)
1,355
62.59%
1,404
64.85%
713
88.90%
716
89.28%
444
91.93%
442
91.51%
Radiology–Magnetic Resonance Imaging (MRI)
1,492
68.91%
1,549
71.55%
734
91.52%
739
92.14%
461
95.45%
465
96.27%
Radiology–Nuclear Medicine
1,268
58.57%
1,318
60.88%
729
90.90%
733
91.40%
459
95.03%
462
95.65%
706
32.61%
770
35.57%
463
57.73%
482
60.10%
295
61.08%
306
63.35%
Radiology–Orthopedic
Radiology–Ultrasound (US)
1,667
77.00%
1,726
79.72%
742
92.52%
748
93.27%
468
96.89%
470
97.31%
Radiology Information System
1,960
90.53%
2,024
93.49%
793
57.73%
482
60.10%
482
99.79%
481
99.59%
Respiratory Care Information System
849
39.21%
999
46.14%
455
56.73%
500
62.34%
290
60.04%
316
65.42%
Single Sign-On
506
23.37%
604
27.90%
352
43.89%
389
48.50%
245
50.72%
261
54.04%
79.50%
Spam Filter/ Spyware
1,244
57.46%
1,317
60.83%
568
70.82%
596
74.31%
366
75.78%
384
Staff Scheduling
655
30.25%
735
33.95%
443
55.24%
460
57.36%
311
64.39%
327
67.70%
Telemedicine
574
26.51%
662
30.58%
204
25.44%
236
29.43%
128
26.50%
140
28.99%
1,953
90.21%
1,985
91.69%
785
97.88%
785
97.88%
474
98.14%
474
98.14%
671
30.99%
790
36.49%
348
43.39%
414
51.62%
239
49.48%
265
54.87%
Time and Attendance
Virtualization Software
0–100 Beds
2011
2012
Next Generation RCM
Biller’s Dash Board
101–200 Beds
2011
2012
% of 802 hospitals
% of 802 hospitals
201–300 Beds
2011
2012
% of 483 hospitals
% of 483 hospitals
271
12.52%
294
13.58%
212
26.43%
217
27.06%
130
26.92%
142
29.40%
68
3.14%
108
4.99%
70
8.73%
83
10.35%
60
12.42%
70
14.49%
542
25.03%
641
29.61%
338
42.14%
373
46.51%
182
37.68%
223
46.17%
Denial Rules
350
16.17%
378
17.46%
244
30.42%
273
34.04%
145
30.02%
150
31.06%
Direct Payer Claims
730
33.72%
748
34.55%
346
43.14%
365
45.51%
208
43.06%
215
44.51%
EFT Transaction
538
24.85%
606
27.99%
239
29.80%
268
33.42%
164
33.95%
185
38.30%
581
26.84%
650
30.02%
256
31.92%
288
35.91%
160
33.13%
183
37.89%
535
24.71%
583
26.93%
188
23.44%
206
25.69%
135
27.95%
153
31.68%
42
1.94%
39
1.80%
24
2.99%
21
2.62%
18
3.73%
19
3.93%
247
11.41%
252
11.64%
90
11.22%
100
12.47%
67
13.87%
71
14.70%
Web PreRegister
329
15.20%
349
16.12%
122
15.21%
132
16.46%
89
18.43%
95
19.67%
Web Schedule
366
16.91%
379
17.51%
122
15.21%
130
16.21%
82
16.98%
87
18.01%
Web Self-Pay
542
25.03%
565
26.10%
198
24.69%
221
27.56%
130
26.92%
145
30.02%
A mbulat ory
Ambulatory EMR
Practice Management
A mbulat ory
2011
% of 19,649 Ambulatory
Facilities
12,321
62.71%
19,139
97.40%
2012
% of 19,649 Ambulatory
Facilities
13,762
70.04%
19,145
97.43%
Ambulatory PACS*
2011
% of 3,461
Ambulatory Facilities
2,080
60.10%
*Only includes ambulatory facilities doing imaging on site
2012
% of 3,461
Ambulatory Facilities
2,057
59.43%
301–400 Beds
2011
2012
% of 312 hospitals
% of 312 hospitals
401–500 Beds
2011
2012
% of 188 hospitals
% of 188 hospitals
501–600 Beds
2011
2012
% of 116 hospitals
% of 116 hospitals
Over 600 beds
2011
2012
% of 151 hospitals
% of 151 hospitals
277
88.78%
282
90.38%
170
90.43%
175
93.09%
107
92.24%
108
93.10%
146
96.69%
148
98.01%
287
91.99%
290
92.95%
178
94.68%
181
96.28%
110
94.83%
111
95.69%
148
98.01%
149
98.68%
295
94.55%
294
29.23%
183
97.34%
186
98.94%
114
98.28%
114
98.28%
151
100.00%
151
100.00%
310
99.36%
309
99.04%
187
99.47%
187
99.47%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
259
83.01%
264
84.62%
160
85.11%
163
86.70%
95
81.90%
98
84.48%
137
90.73%
137
90.73%
124
39.74%
130
41.67%
91
48.40%
92
48.94%
51
43.97%
53
45.69%
73
48.34%
77
50.99%
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
202
64.74%
218
69.87%
125
66.49%
135
71.81%
80
68.97%
87
75.00%
110
72.85%
117
77.48%
311
99.68%
311
99.68%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
312
100.00%
312
100.00%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
220
70.51%
238
76.28%
136
72.34%
256
77.13%
96
82.76%
100
86.21%
135
89.40%
140
92.72%
213
68.27%
227
72.76%
143
76.06%
151
80.32%
83
71.55%
90
77.59%
113
74.83%
126
83.44%
289
92.63%
292
93.59%
182
96.81%
182
96.81%
113
97.41%
113
97.41%
151
100.00%
151
100.00%
301
69.47%
303
97.17%
182
97.34%
183
97.34%
115
99.14%
115
99.14%
150
99.34%
150
99.34%
304
97.44%
305
97.76%
186
98.94%
186
98.94%
115
99.14%
115
99.14%
151
100.00%
151
100.00%
295
94.55%
298
95.51%
180
95.74%
180
95.74%
114
98.28%
114
92.28%
147
97.35%
151
100.00%
236
75.64%
252
80.77%
147
78.19%
150
79.79%
95
81.90%
101
87.07%
128
84.77%
131
86.75%
295
94.55%
299
95.83%
182
96.81%
182
96.81%
114
98.28%
111
95.69%
149
98.68%
150
99.34%
302
96.79%
304
97.44%
184
97.87%
185
98.40%
115
99.14%
115
99.14%
150
99.34%
150
99.34%
299
95.83%
302
96.79%
183
97.34%
184
97.87%
113
97.41%
113
97.41%
147
97.35%
147
97.35%
193
61.86%
207
66.35%
139
73.94%
143
76.06%
79
68.10%
79
68.10%
121
80.13%
121
80.13%
302
96.79%
303
97.12%
186
98.94%
186
98.94%
115
99.14%
115
99.14%
151
100.00%
151
100.00%
311
99.68%
311
99.68%
188
100.00%
188
100.00%
116
100.00%
116
100.00%
151
100.00%
151
100.00%
187
59.94%
203
65.06%
130
69.15%
141
75.00%
74
63.79%
81
69.83%
114
75.50%
120
79.47%
150
48.08%
174
55.77%
86
45.74%
96
51.06%
59
50.86%
65
56.03%
92
60.93%
100
66.23%
233
74.68%
241
77.24%
145
77.13%
152
80.85%
82
70.69%
86
74.14%
122
80.79%
127
84.11%
222
71.15%
232
74.36%
129
68.62%
137
72.87%
80
68.97%
87
75.00%
118
78.15%
123
81.46%
91
29.17%
102
32.69%
59
31.38%
65
34.57%
43
37.07%
47
40.52%
68
45.03%
79
52.32%
306
98.08%
306
98.08%
186
98.94%
185
98.40%
113
97.41%
115
99.14%
150
99.34%
150
99.34%
160
51.28%
175
56.09%
103
54.79%
113
60.11%
58
50.00%
71
61.21%
91
60.26%
102
67.55%
301–400 Beds
2011
2012
% of 312 hospitals
% of 312 hospitals
401–500 Beds
2011
2012
% of 188 hospitals
% of 188 hospitals
501–600 Beds
2011
2012
% of 116 hospitals
% of 116 hospitals
Over 600 beds
2011
2012
% of 151 hospitals
% of 151 hospitals
81
25.96%
83
26.60%
45
23.94%
51
27.13%
34
29.31%
36
31.03%
39
25.83%
41
27.15%
44
14.10%
50
16.03%
16
8.51%
22
11.70%
12
10.34%
21
18.10%
22
14.57%
31
20.53%
124
39.74%
143
45.83%
77
40.96%
86
45.74%
53
45.69%
66
56.90%
55
36.42%
72
47.68%
95
30.45%
103
33.01%
64
34.04%
65
34.57%
30
25.86%
34
29.31%
48
31.79%
51
33.77%
44.37%
144
46.15%
153
49.04%
93
49.47%
88
46.81%
46
39.66%
52
44.83%
63
41.72%
67
100
32.05%
111
35.58%
73
38.83%
79
42.02%
42
36.21%
48
41.38%
55
36.42%
62
41.06%
101
32.37%
114
36.54%
75
39.89%
81
43.09%
42
36.21%
49
42.24%
63
41.72%
69
45.70%
85
27.24%
99
31.73%
66
35.11%
74
39.36%
35
30.17%
41
35.34%
46
30.46%
49
32.45%
16
5.13%
14
4.49%
9
4.79%
7
3.72%
5
4.31%
7
6.03%
11
7.28%
12
7.95%
52
16.67%
57
18.27%
38
20.21%
38
20.21%
21
18.10%
21
18.10%
29
19.21%
34
22.52%
58
18.59%
67
21.47%
48
25.53%
49
26.06%
25
21.55%
25
21.55%
37
24.50%
40
26.49%
46
14.74%
52
16.67%
43
22.87%
44
23.40%
24
20.69%
25
21.55%
31
20.53%
35
23.18%
86
27.56%
97
31.09%
66
35.11%
69
36.70%
28
24.14%
30
25.86%
50
33.11%
56
37.09%
Home He alt h
Home Health Administrative
Home Health Clinical
2011
% of 1,782
Home Health Facilities
1,723
96.69%
1,593
89.39%
2012
% of 1,782
Home Health Facilities
1,733
97.25%
1,629
91.41%
About HIMSS
HIMSS is a cause-based, not-for-profit organization exclusively focused on providing global leadership for the optimal use of
information technology (IT) and management systems for the betterment of health and healthcare. Founded 52 years ago, HIMSS
and its related organizations are headquartered in Chicago with additional offices in the United States, Europe and Asia. HIMSS
represents more than 52,000 individual members, of which more than two thirds work in healthcare provider, governmental and
not-for-profit organizations. HIMSS also includes over 600 corporate members and more than 225 not-for-profit partner
organizations that share our mission of transforming healthcare through the best use of information technology and management
systems. HIMSS frames and leads healthcare practices and public policy through its content expertise, professional development,
research initiatives, and media vehicles designed to promote information and management systems’ contributions to improving the
quality, safety, access, and cost-effectiveness of patient care. To learn more about HIMSS and to find out how to join us and our
members in advancing our cause, please visit our website at www.himss.org.
About HIMSS Analy tics
HIMSS Analytics supports improved decision-making for healthcare organizations, healthcare IT companies and consulting firms by
delivering high quality data and analytical expertise. The company collects and analyzes healthcare organization data relating to IT
processes and environments, products, IS department composition and costs, IS department management metrics, healthcare
delivery trends and purchasing-related decisions. HIMSS Analytics is a wholly-owned, not for profit subsidiary of HIMSS.
HIMSS Analytics
Chicago, IL 60603-5616
www.himssanalytics.org
HIMSS
Chicago, IL 60603-5616
312-915-9295
www.himss.org
ISBN: 978-1-938904-26-4
ISSN: 1949-0526
Order Code: 617

Annual Report of the US Hospital IT Market

Transcription

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