Editor’s Note:

Transcription

Editor’s Note:

Editor’s Note: This online data supplement contains supplemental material that was not included with the published article by
Caroline Lubick Goldzweig and colleagues, “Costs and Benefits of Health Information Technology: New Trends from the Literature,”
Health Affairs 28, no. 2 (2009): w282-w293 (published online 27 January 2009; 10.1377/hlthaff.28.2.w282)
Figure 1. Article Flow
4,683 Titles Ide ntifie d for Titl e R eview
4.035 R ejected on Title R eview
648 Titles C onsi der ed R elevant
400 R ejected on A bstract R eview
248 A r ticles R equested
5 R ejected:
5 N ot Found
243 A r ticles S cr eened
64
15
4
15
5
23
2
R ejected:
Topic (N ot H IT)
D esign – O ther P urpose
D escriptive Q ualitative
N on-systematic review
D escriptive D esign/N o B arriers or Facilitators
R obotics article
179 A r ticles Q uality R eview ed and i nclude d in t he H IT int er active data base
182 studies foun d
References
Asaro PV, Sheldahl AL, Char DM. “Embedded guideline
information without patient specificity in a
commercial emergency department computerized orderentry system.” Academic Emergency Medicine 2006; 13:
452-8.
Boissy P, Jacobs K, Roy SH. “Usability of a barcode
scanning system as a means of data entry on a PDA for
self-report health outcome questionnaires: a pilot
study in individuals over 60 years of age.” BioMed
Central Medical Informatics and Decision Making 2006;
6: 42.
Boldrick JC, Layton CJ, Nguyen J, Swetter SM. “Evaluation
of digital dermoscopy in a pigmented lesion clinic:
clinician versus computer assessment of malignancy
risk.” Journal of the American Academy of Dermatology
2007; 56: 417-21.
Butler J, Speroff T, Arbogast PG, Newton M, Waitman LR,
Stiles R, Miller RA, Ray W, Griffin MR. “Improved
compliance with quality measures at hospital discharge
with a computerized physician order entry system.”
American Heart Journal 2006; 151: 643-53.
Cavanagh K, Shapiro DA, Van Den Berg S, Swain S, Barkham M,
Proudfoot J. “The effectiveness of computerized
cognitive behavioural therapy in routine care.”
British Journal of Clinical Psychology 2006; 45: 499514.
Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E,
Morton SC, Shekelle PG. “Systematic review: impact of
health information technology on quality, efficiency,
and costs of medical care.” Annals of Internal
Medicine 2006; 144: 742-52.
Cintron A, Phillips R, Hamel MB. “The effect of a webbased, patient-directed intervention on knowledge,
discussion, and completion of a health care proxy.”
Journal of Palliative Medicine 2006; 9: 1320-8.
Cunningham JA, Humphreys K, Kypri K, van Mierlo T.
“Formative evaluation and three-month follow-up of an
online personalized assessment feedback intervention
for problem drinkers.” Journal of Medical Internet
Research 2006; 8: e5.
Cutler DM, Feldman NE, Horwitz JR. “U.S. adoption of
computerized physician order entry systems.” Health
Affairs (Millwood) 2005; 24: 1654-63.
Del Beccaro MA, Jeffries HE, Eisenberg MA, Harry ED.
“Computerized provider order entry implementation: no
association with increased mortality rates in an
intensive care unit.” Pediatrics 2006; 118: 290-5.
Dexter PR, Perkins SM, Maharry KS, Jones K, McDonald CJ.
“Inpatient computer-based standing orders vs physician
reminders to increase influenza and pneumococcal
vaccination rates: a randomized trial.” Journal of the
American Medical Association 2004; 292: 2366-71.
Downer SR, Meara JG, DaCosta AC. Use of SMS text messaging
to improve outpatient attendance. Med J Aust
2005;183(7):366-8
Downer SR, Meara JG, Da Costa AC, Sethuraman K. “SMS text
messaging improves outpatient attendance.” Australian
Health Review 2006; 30: 389-96.
Feldstein A, Elmer PJ, Smith DH, Herson M, Orwoll E, Chen
C, Aickin M, Swain MC. “Electronic medical record
reminder improves osteoporosis management after a
fracture: a randomized, controlled trial.” Journal of
the American Geriatrics Society 2006; 54: 450-7.
Fung V, Ortiz E, Huang J, Fireman B, Miller R, Selby JV,
Hsu J. “Early experiences with e-health services
(1999-2002): promise, reality, and implications.”
Medical Care 2006; 44: 491-6.
Galanter WL, Polikaitis A, DiDomenico RJ. A trial of
automated safety alerts for inpatient digoxin use with
computerized physician order entry. Journal of the
American Medical Informatics Association 2004; 11:
270-7.
Garrido T, Jamieson L, Zhou Y, Wiesenthal A, Liang L.
“Effect of electronic health records in ambulatory
care: retrospective, serial, cross sectional study.”
British Medical Journal 2005; 330: 581.
Glanz K, Murphy S, Moylan J, Evensen D, Curb JD. “Improving
dietary self-monitoring and adherence with hand-held
computers: a pilot study.” American Journal of Health
Promotion 2006; 20: 165-70.
Glasgow RE, Nutting PA, King DK, Nelson CC, Cutter G,
Gaglio B, Rahm AK, Whitesides H. “Randomized
effectiveness trial of a computer-assisted
intervention to improve diabetes care.” Diabetes Care
2005; 28: 33-9.
Glasgow RE, Strycker LA, King DK, Toobert DJ, Rahm AK, Jex
M, Nutting PA. “Robustness of a computer-assisted
diabetes self-management intervention across patient
characteristics, healthcare settings, and intervention
staff.” American Journal of Managed Care 2006; 12:
137-45.
Green MJ, Peterson SK, Baker MW, Harper GR, Friedman LC,
Rubinstein WS, Mauger DT. “Effect of a computer-based
decision aid on knowledge, perceptions, and intentions
about genetic testing for breast cancer
susceptibility: a randomized controlled trial.”
Journal of the American Medical Association 2004; 292:
442-52.
Grime PR. “Computerized cognitive behavioural therapy at
work: a randomized controlled trial in employees with
recent stress-related absenteeism.” Occupational
Medicine 2004; 54: 353-9.
Gustafson DH, McTavish FM, Stengle W, Ballard D, Hawkins R,
Shaw BR, Jones E, Julesberg K, McDowell H, Chen WC,
Volrathongchai K, Landucci G. “Use and Impact of
eHealth System by Low-income Women With Breast
Cancer.” Journal of Health Communication 2005; 10
Suppl 1: 195-218.
Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS,
Nguyen TC, Bayir H, Orr RA. “Unexpected increased
mortality after implementation of a commercially sold
computerized physician order entry system.” Pediatrics
2005; 116: 1506-12.
Harno K, Kauppinen-Makelin R, Syrjalainen J. “Managing
diabetes care using an integrated regional e-health
approach.” Journal of Telemedicine and Telecare 2006;
12 Suppl 1: 13-5.
Holden MK, Dyar TA, Dayan-Cimadoro L. “Telerehabilitation
using a virtual environment improves upper extremity
function in patients with stroke.” IEEE Transactions
on Neural Systems and Rehabilitation Engineering 2007;
15: 36-42.
Jacobi C, Morris L, Beckers C, Bronisch-Holtze
Winzelberg AJ, Taylor CB. “Maintenance of
based prevention: a randomized controlled
International Journal of Eating Disorders
114-9.
J, Winter J,
internettrial.”
2007; 40:
Jha AK, Ferris TG, Donelan K, DesRoches C, Shields A,
Rosenbaum S, Blumenthal D. “How common are electronic
health records in the United States? A summary of the
evidence.” Health Affairs (Millwood) 2006; 25: w496507.
Kaner E, Heaven B, Rapley T, Murtagh M, Graham R, Thomson
R, May C. “Medical communication and technology: a
video-based process study of the use of decision aids
in primary care consultations.” BioMed Central Medical
Informatics and Decision Making 2007; 7: 2.
Kemper AR, Uren RL, Clark SJ. “Adoption of electronic
health records in primary care pediatric practices.”
Pediatrics 2006; 118: e20-4.
Lester WT, Grant RW, Barnett GO, Chueh HC. “Randomized
controlled trial of an informatics-based intervention
to increase statin prescription for secondary
prevention of coronary disease.” Journal of General
Internal Medicine 2006; 21: 22-9.
Lindenauer PK, Ling D, Pekow PS, Crawford A, NaglieriPrescod D, Hoople N, Fitzgerald J, Benjamin EM.
“Physician characteristics, attitudes, and use of
computerized order entry.” Journal of Hospital
Medicine 2006; 1: 221-30.
Lium JT, Laerum H, Schulz T, Faxvaag A. “From the front
line, report from a near paperless hospital: mixed
reception among health care professionals.” Journal of
the American Medical Informatics Association 2006; 13:
668-75.
Mattocks K, Lalime K, Tate JP, Giannotti TE, Carr K,
Carrabba A, Blum T, Meehan TP. “The state of physician
office-based health information technology in
Connecticut: current use, barriers and future plans.”
Connecticut Medicine 2007; 71: 27-31.
McInnes DK, Saltman DC, Kidd MR. “General practitioners'
use of computers for prescribing and electronic health
records: results from a national survey.” The Medical
Journal of Australia 2006; 185: 88-91.
McMahon GT, Gomes HE, Hickson Hohne S, Hu TM, Levine BA,
Conlin PR. “Web-based care management in patients with
poorly controlled diabetes.” Diabetes Care 2005; 28:
1624-9.
Menachemi N. “Barriers to ambulatory EHR: who are 'imminent
adopters' and how do they differ from other
physicians?” Informatics in Primary Care 2006; 14:
101-8.
Murray MD, Harris LE, Overhage JM, Zhou XH, Eckert GJ,
Smith FE, Buchanan NN, Wolinsky FD, McDonald CJ,
Tierney WM. “Failure of computerized treatment
suggestions to improve health outcomes of outpatients
with uncomplicated hypertension: results of a
randomized controlled trial.” Pharmacotherapy 2004;
24: 324-37.
O'Neill L, Klepack W. “Electronic medical records for a
rural family practice: a case study in systems
development.” Journal of Medical Systems 2007; 31: 2533.
Ovretveit J, Scott T, Rundall TG, Shortell SM, Brommels M.
“Improving quality through effective implementation of
information technology in healthcare.” International
Journal for Quality in Health Care 2007; 19: 259-66.
Ozanne EM, Annis C, Adduci K, Showstack J, Esserman L.
“Pilot trial of a computerized decision aid for breast
cancer prevention.” Breast Journal 2007; 13: 147-54.
Ozdas A, Speroff T, Waitman LR, Ozbolt J, Butler J, Miller
RA. “Integrating ‘best of care’ protocols into
clinicians' workflow via care provider order entry:
impact on quality-of-care indicators for acute
myocardial infarction.” Journal of the American
Medical Informatics Association 2006; 13: 188-96.
Palen TE, Raebel M, Lyons E, Magid DM. “Evaluation of
laboratory monitoring alerts within a computerized
physician order entry system for medication orders.”
American Journal of Managed Care 2006; 12: 389-95.
Pizzi LT, Suh DC, Barone J, Nash DB. “Factors related to
physicians' adoption of electronic prescribing:
results from a national survey.” American Journal of
Medical Quality 2005; 20: 22-32.
Potts AL, Barr FE, Gregory DF, Wright L, Patel NR.
“Computerized physician order entry and medication
errors in a pediatric critical care unit.” Pediatrics
2004; 113: 59-63.
Pretty IA, Ellwood RP. “Comparison of paired visual
assessment and software analyses of changes in caries
status over 6 months from fluorescence images.” Caries
Research 2007; 41: 115-20.
Proudfoot J, Ryden C, Everitt B, Shapiro DA, Goldberg D,
Mann A, Tylee A, Marks I, Gray JA. “Clinical efficacy
of computerised cognitive-behavioural therapy for
anxiety and depression in primary care: randomised
controlled trial.” The British Journal of Psychiatry
2004; 185: 46-54.
Robertson L, Smith M, Castle D, Tannenbaum D. “Using the
Internet to enhance the treatment of depression.”
Australasian Psychiatry 2006; 14: 413-7.
Rothschild JM, McGurk S, Honour M, Lu L, McClendon AA,
Srivastava P, Churchill WH, Kaufman RM, Avorn J, Cook
EF, Bates DW. “Assessment of education and
computerized decision support interventions for
improving transfusion practice.” Transfusion 2007; 47:
228-39.
Roumie CL, Elasy TA, Greevy R, Griffin MR, Liu X, Stone WJ,
Wallston KA, Dittus RS, Alvarez V, Cobb J, Speroff T.
“Improving blood pressure control through provider
education, provider alerts, and patient education: a
cluster randomized trial.” Annals of Internal Medicine
2006; 145: 165-75.
Schinke S, Di Noia J, Schwinn T, Cole K. “Drug abuse risk
and protective factors among black urban adolescent
girls: a group-randomized trial of computer-delivered
mother-daughter intervention.” Psychology of Addictive
Behaviors 2006; 20: 496-500.
Schmittdiel J, Bodenheimer T, Solomon NA, Gillies RR,
Shortell SM. “Brief report: The prevalence and use of
chronic disease registries in physician organizations.
A national survey.” Journal of General Internal
Medicine 2005; 20: 855-8.
Sequist TD, Gandhi TK, Karson AS, Fiskio JM, Bugbee D,
Sperling M, Cook EF, Orav EJ, Fairchild DG, Bates DW.
“A randomized trial of electronic clinical reminders
to improve quality of care for diabetes and coronary
artery disease.” Journal of the American Medical
Informatics Association 2005; 12: 431-7.
Sheridan SL, Shadle J, Simpson RJ Jr, Pignone MP. “The
impact of a decision aid about heart disease
prevention on patients' discussions with their doctor
and their plans for prevention: a pilot randomized
trial.” BioMed Central Health Services Research 2006;
6: 121.
Smith DH, Perrin N, Feldstein A, Yang X, Kuang D, Simon SR,
Sittig DF, Platt R, Soumerai SB. “The impact of
prescribing safety alerts for elderly persons in an
electronic medical record: an interrupted time series
evaluation.” Archives of Internal Medicine 2006; 166:
1098-104.
Steele AW, Eisert S, Witter J, Lyons P, Jones MA, Gabow P,
Ortiz E. “The effect of automated alerts on provider
ordering behavior in an outpatient setting.” PLoS
Medicine 2005; 2: e255.
Stevenson KB, Barbera J, Moore JW, Samore MH, Houck P.
“Understanding keys to successful implementation of
electronic decision support in rural hospitals:
analysis of a pilot study for antimicrobial
prescribing.” American Journal of Medical Quality
2005; 20: 313-8.
Tideman RL, Chen MY, Pitts MK, Ginige S, Slaney M, Fairley
CK. “A randomised controlled trial comparing computerassisted with face-to-face sexual history taking in a
clinical setting.” Sexually Transmitted Infections
2007; 83: 52-6.
Tierney WM, Overhage JM, Murray MD, Harris LE, Zhou XH,
Eckert GJ, Smith FE, Nienaber N, McDonald CJ, Wolinsky
FD. “Can computer-generated evidence-based care
suggestions enhance evidence-based management of
asthma and chronic obstructive pulmonary disease? A
randomized, controlled trial.” Health Services
Research 2005; 40: 477-97.
Toth-Pal E, Nilsson GH, Furhoff AK. “Clinical effect of
computer generated physician reminders in health
screening in primary health care--a controlled
clinical trial of preventive services among the
elderly.” International Journal of Medical Informatics
2004; 73: 695-703.
Vilella A, Bayas JM, Diaz MT, Guinovart C, Diez C, Simo D,
Munoz A, Cerezo J. “The role of mobile phones in
improving vaccination rates in travelers.” Preventive
Medicine 2004; 38: 503-9.
Wagner B, Knaevelsrud C, Maercker A. “Internet-based
cognitive-behavioral therapy for complicated grief: a
randomized controlled trial.” Death Studies 2006; 30:
429-53.
Walshe K. “Understanding what works – and why – in quality
improvement: the need for theory-driven evaluation.”
International Journal for Quality in Health Care 2007;
19: 57-59.
Table 1. Evidence Table for studies from the HIT leaders
HIT Element(s)
Healthcare Setting
Butler J, Speroff
TArbogast PG, Newton M,
Waitman LR, Stiles R,
Miller RA, Ray W, Griffin
MR. “Improved compliance
with quality measures at
hospital discharge with a
computerized physician
order entry system.”
American Heart Journal
2006; 151: 643-53.
Study
Purpose
To assess the
effect of CPOE
discharge tools
on quality
measures for
acute
myocardial
infarction (AMI)
and congestive
heart failure
(CHF)
CPOE, clinical
reminders during
patient
encounter,
electronic
prescribing
Vanderbilt University
Medical Center,
Nashville, TN
Dexter PR, Perkins SM,
Maharry KS, Jones K,
McDonald CJ. “Inpatient
computer-based standing
orders vs physician
reminders to increase
influenza and
pneumococcal vaccination
rates: a randomized trial.”
Journal of the American
Medical Association 2004;
292: 2366-71.
To evaluate the
effect of
computerized
standing nurse
orders for
influenza and
pneumococcal
vaccines as
compared to
physician
computerized
reminders
CPOE, EHR,
clinical reminders
during patient
encounter
University hospital in
Indianapolis,
including all patients
discharged from
general medicine
wards during the
study periods who
were eligible for the
vaccines
Author
Implementation
Factors Evaluated
CPOE associated
reminders were
revised up to weekly
based on provider
feedback
(Implementation
strategy)
Potential barriers to
adoption included
confusion between
providers and coders
on criteria used to
assign primary
discharge diagnoses
and a lack of .
regular feedback on
results of
intervention
Program sustained
indefinitely at study
institution for all
inpatient wards other
than intensive care
Source: Authors’ analysis of results from 2007 Systematic Review of the HIT Literature
Findings/Outcomes
Smoking cessation
counseling increased
from 1% to 43% of
smokers with CHF
and from 21% to 62%
of smokers with AMI.
Discharge
instructions
increased from 3% to
56% of CHF patients.
The proportion of
patients who
received discharge
prescriptions did not
change.
Nurse electronic
standing orders
resulted in greater
rates of vaccination
compared to
electronic physician
reminders (for
influenza 42% vs.
30%; for
pneumococcal
vaccination 51% vs.
31%)
1
Author
HIT Element(s)
Healthcare Setting
Lester WT, Grant RW,
Barnett GO, Chueh HC.
“Randomized controlled
trial of an informaticsbased intervention to
increase statin prescription
for secondary prevention
of coronary disease.”
Journal of General Internal
Medicine 2006; 21: 22-9.
Study
Purpose
To evaluate
whether a
disease
management
system outside
a clinical
encounter
would reduce
delays in
appropriate
medication
adjustment
EHR, electronic
prescribing
Academic primary
care adult practices
that relied on an
electronic health
record for the
majority of care
Murray MD Harris LE,
Overhage JM, Zhou XH,
Eckert GJ, Smith FE,
Buchanan NN, Wolinsky
FD, McDonald CJ, Tierney
WM. “Failure of
computerized treatment
suggestions to improve
health outcomes of
outpatients with
uncomplicated
hypertension: results of a
randomized controlled
trial.” Pharmacotherapy
2004; 24: 324-37.
To assess
physician and
pharmacist
compliance
with electronic
hypertension
treatment
suggestions
and the effect
on patient
health-related
quality of life,
and clinical and
utilization
measures.
CPOE, medical
prescribing
support
Large, inner-city
academic internal
medicine practice
affiliated with the
Indiana University
School of Medicine
Implementation
Factors Evaluated
Initial differences in
statin prescription
changes were not
sustained at one
year
Findings/Outcomes
Implementation
strategy included
dissemination of
locally approved
guidelines for
managing
hypertension;
presentations at
medical grand
rounds; and one-onone meeting with
each intervention
pharmacist and
physician regarding
the intervention
Compliance with
treatment
suggestions did NOT
differ significantly
among groups nor
were there
differences in quality
of life, blood pressure
measurements or
emergency room or
hospital visits.
Compared with
controls, more
intervention patients
had statin
prescription changes
at 1 month
postrandomization
(15.3% vs 2%,
p=0.001).
Providers could
bypass suggestions
by using the
“escape” key
(barrier)
2
Author
Ozdas A, Speroff T,
Waitman LR, Ozbolt J,
Butler J, Miller RA.
“Integrating ‘best of care’
protocols into clinicians'
workflow via care provider
order entry: impact on
quality-of-care indicators
for acute myocardial
infarction.” Journal of the
American Medical
Informatics Association
2006; 13: 188-96.
Potts AL, Barr FE,
Gregory DF, Wright L,
Patel NR. “Computerized
physician order entry and
medication errors in a
pediatric critical care unit.”
Pediatrics 2004; 113: 5963.
Study
Purpose
To evaluate the
impact of a
decision
support tool on
a) the
integration of
cardiology
order sets and
b) resulting
medication
orders
HIT Element(s)
Healthcare Setting
CPOE, clinical
reminders during
patient
encounter,
clinical
guidelines/protoc
ols
Vanderbilt University
Hospital, a 630-bed
academic tertiary
care hospital
To evaluate the
impact of
CPOE on the
frequency of
errors in the
medication
ordering
process in a
pediatric critical
care unit
CPOE
All patients admitted
to a 20-bed
multidisciplinary
pediatric ICU at an
academic institution
in a large city
Implementation
Factors Evaluated
Relevant order sets
were reviewed and
revised by cardiology
(implementation
strategy)
System penetration
was complete for
non-ER sites but
system could not be
used in the ER,
where many cardiac
patients first present,
because CPOE was
not in use (barrier)
None reported
Findings/Outcomes
ACS order set use
increased from 60%
in the preintervention period to
70% after the
program was
installed (p=0.009).
For all suspected
acute myocardial
infarction (ACI)
admissions, CS order
set use led to a
significant increase in
early aspirin ordering
(p=0.001) and a
trend toward increase
in beta-blocker
ordering (p=0.07).
Rates of potential
adverse drug events
(ADEs), medication
prescribing errors
(MPs) and rule
violations (RVs) all
decreased
significantly after
implementation of the
CPOE system
(40.9% reduction in
potential ADEs,
99.4% reduction in
MPEs and 97.9%
reduction in RVs, p<
0.001 for all
comparisons)
3
Author
Rothschild JM, McGurk S,
Honour M, Lu L,
McClendon AA, Srivastava
P, Churchill WH, Kaufman
RM, Avorn J, Cook EF,
Bates DW. “Assessment of
education and
computerized decision
support interventions for
improving transfusion
practice.” Transfusion
2007; 47: 228-39.
Roumie CL, Elasy TA,
Greevy R, Griffin MR, Liu
X, Stone WJ, Wallston KA,
Dittus RS, Alvarez V, Cobb
J, Speroff T. “Improving
blood pressure control
through provider
education, provider alerts,
and patient education: a
cluster randomized trial.”
Annals of Internal
Medicine 2006; 145: 16575
Study
Purpose
RCT of
decision
support
intervention
with
computerized
physician order
entry (CPOE)
for red blood
cell, platelet,
and freshfrozen plasma
orders.
HIT Element(s)
Healthcare Setting
Decision support
system
Academic medical
center with an
established CPOE
system.
To compare the
effect of
different
elements of a
multifactorial
intervention on
quality of care
for
hypertensive
patients
EHR, clinical
reminders during
patient
encounter,
clinical
guidelines/protoc
ols
Implementation
Factors Evaluated
System penetration
limited to areas with
established CPOE
Facilitated by
guideline training
Potential barrier
related to physician
concerns that the
goal of the guidelines
was cost and usage
reduction
Patients with
hypertension and
their providers
associated with the
VA Tennessee
Valley Healthcare
System
None reported
Findings/Outcomes
Rates of
inappropriate
transfusion orders for
all staff decreased
after the initial
education (from
72.6% to 63.3%,
p<0.0001) and
continued to
decrease in the
decision support
group (59.6%
p<0.0001) while
slipping back to
baseline in the
control group
(67.4%).
The proportion of
patients achieving a
systolic blood
pressure goal of
<140 was greatest
when patients
received an
educational letter in
addition to their
providers receiving
education and
electronic alerts.
4
Author
Sequist Sequist TD,
Gandhi TK, Karson AS,
Fiskio JM, Bugbee D,
Sperling M, Cook EF, Orav
EJ, Fairchild DG, Bates
DW. “A randomized trial of
electronic clinical
reminders to improve
quality of care for diabetes
and coronary artery
disease.” Journal of the
American Medical
Informatics Association
2005; 12: 431-7.
Tierney WM, Overhage
JM, Murray MD, Harris LE,
Zhou XH, Eckert GJ, Smith
FE, Nienaber N, McDonald
CJ, Wolinsky FD. “Can
computer-generated
evidence-based care
suggestions enhance
evidence-based
management of asthma
and chronic obstructive
pulmonary disease? A
randomized, controlled
trial.” Health Services
Research 2005; 40: 47797.
Study
Purpose
To assess the
effect of
computerized
clinical
reminders on
processes of
care for
diabetes and
coronary artery
disease
HIT Element(s)
Healthcare Setting
Clinical
reminders during
patient encounter
Partners HealthCare
System, 20
outpatient clinics
affiliated with
Brigham and
Women’s Hospital or
Massachusetts
General Hospital
To determine
whether
guidelinebased
suggestions
presented to
physicians and
pharmacists
improves the
care of asthma
and COPD
CPOE, EHR,
medication
prescribing
support, clinical
reminders during
patient
encounter,
clinical
guidelines/protoc
ols
4 hospital-based
primary care
practices (Indiana
University Medical
Group-Primary Care)
with associated
outpatient
pharmacies.
Patients were >18
with diagnosis of
asthma or COPD
based on diagnosis,
medication or xray
result
Implementation
Factors Evaluated
System penetration
was universal for all
sites
Barriers most
commonly identified
were lack of time,
patient
noncompliance and
lack of knowledge
Findings/Outcomes
Intervention
physicians required
to view all care
suggestions and
both intervention and
control physicians
required to enter all
orders electronically
(facilitators)
There were no
differences between
intervention and
control groups in
adherence to care
suggestions, impact
on quality of life,
medication
adherence or patient
satisfaction
Reminders increased
the use of
recommended
processes for
diabetes by an
average of 5% (from
14% to 19%)
compared to control,
; and for coronary
artery disease by 5%
(from 17% to 22%)
Physicians were
skeptical of benefits
and intentions of
guidelines (barrier)
5
Table 2. Evidence Table of Commercial HIT Applications
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Asaro PV, Sheldahl
AL, Char DM.
“Embedded
guideline information
without patient
specificity in a
commercial
emergency
department
computerized orderentry system.”
Academic
Emergency Medicine
2006; 13: 452-8
To compare
acute coronary
syndrome (ACS)
guideline
compliance
before and after
both paper and
then electronic
implementation
CPOE
Emergency medicine
division at
Washington
University hospital
Del Beccaro MA,
Jeffries HE,
Eisenberg MA, Harry
ED. “Computerized
provider order entry
implementation: no
association with
increased mortality
rates in an intensive
care unit.” Pediatrics
2006; 118: 290-5.
To determine
whether there
were changes in
risk-adjusted
mortality in a
pediatric ICU
after
implementation of
a CPOE system
CPOE, results
reporting /
viewing systems
Pediatric ICU of a
tertiary referral
center in the
Northwest US
Implementation Factors
Evaluated
A paper-based guideline
with order sets for ED
patients with ACS was
developed by a
multidisciplinary team over
a six-month period. The
guideline was initially
introduced as a set of four
preprinted paper forms
which were later adapted
for inclusion as CPOE
order sets.
(implementation
strategy)
Clinical leader identified
from each clinical division
to design order sets; all
clinical staff required to
attend role-specific
training; and, each
discipline had
"superusers"(implementati
on strategy)
Findings/Outcomes
In the last phase of
the study, betablocker use was
significantly
associated with use of
the guidelines. There
was no association
between aspirin or
heparin use and use
of the guidelines.
Despite electronic
implementation of
guidelines, there was
no improvement in
compliance with any
of the guideline
recommendations.
There was a nonsignificant reduction in
the risk of mortality in
the 13 months before
and after
implementation
(4.22% v 3.36%; RR
0.82, 95% CI 0.55 –
1.21)
Go-live support provided
24/7 for 2 weeks, after
which providers could not
“opt out” (facilitators).
6
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Feldstein A, Elmer
PJ, Smith DH,
Herson M, Orwoll E,
Chen C, Aickin M,
Swain MC.
“Electronic medical
record reminder
improves
osteoporosis
management after a
fracture: a
randomized,
controlled trial.”
Journal of the
American Geriatrics
Society 2006; 54:
450-7.
To evaluate
whether an EHR
reminder to the
primary care
provider, with or
without a patient
reminder,
increases the
proportion of
women who
received bone
mineral density
(BMD)
measurement or
a medication for
osteoporosis
after a fracture.
EHR, clinical
guidelines/proto
cols
Nonprofit group
model HMO in he
Pacific Northwest
Evaluated
Reminder was signed by
(the chair of the
osteoporosis quality
improvement committee
and patient-specific advice,
as opposed to general
advice, was provided.
(facilitators)
Findings/Outcomes
6 months after
initiation of provider
and patient reminders,
rates of BMD
measurement or
receipt of
osteoporosis
medications were
51.5% in the provider
reminder group,
43.1% in the patient
reminder group, and
5.9% in the usual care
group
Total calcium intake
increased significantly
in both intervention
groups, compared to
usual care.
7
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Galanter WL,
Polikaitis A,
DiDomenico RJ. A
trial of automated
safety alerts for
inpatient digoxin use
with computerized
physician order
entry. Journal of the
American Medical
Informatics
Association 2004;
11: 270-7.
To compare the
time for physician
action regarding
digoxin use
before and after
implementation of
synchronous
alerts (occurring
at the time of
ordering) and
asynchronous
alerts (presented
as print-outs for
responsible
providers)
CPOE, Clinical
reminders
during patient
encounter
University of Illinois
Hospital and Medical
Center
Evaluated
None reported
Findings/Outcomes
There was a
significant
improvement in time
to ordering
appropriate lab tests
after implementation
of the DSS.
Compliance with
supplementation of
untreated
hypokalemia and
hypomagnesemia was
improved with the
asynchronous alerts
but not with the
synchronous alerts.
8
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Garrido T, Jamieson
L, Zhou Y,
Wiesenthal A, Liang
L. “Effect of
electronic health
records in
ambulatory care:
retrospective, serial,
cross sectional
study.” British
Medical Journal
2005; 330: 581.
To assess the
effect of the
introduction of a
multifunctional
EHR on health
care utilization
and processes of
care
CPOE, EHR,
results
reporting/viewin
g systems
Kaiser Permanente
Northwest and
Colorado
Evaluated
Qualitative interviews
indicated that strong
leadership support, an
organizational structure
supporting free flow of
information, and efficiency
gains were key to
successful implementation.
Findings/Outcomes
Four years after
implementation in
both the Northwest
and Colorado,
ambulatory care
service use declined
and laboratory use
decreased by
18%,radiology
services decreased by
14% in the Northwest.
Measures of advice
on smoking cessation,
cervical cancer
screening, or retinal
examination in
diabetics either were
unchanged or
improved slightly over
time.
9
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Han YY, Carcillo JA,
Venkataraman ST,
Clark RS, Watson
RS, Nguyen TC,
Bayir H, Orr RA.
“Unexpected
increased mortality
after implementation
of a commercially
sold computerized
physician order entry
system.” Pediatrics
2005; 116:150612.
To assess the
effect of CPOE
on outcomes in a
pediatric hospital
CPOE
University-affiliated
235 bed regional
pediatric referral
center with 12,000
annual admissions
Evaluated
Implementation strategy
included a mandatory 3
hour computer tutorial and
practice session 3 months
prior to CPOE
implementation for all
hospital health care
personnel, a.hospital-wide
implementation over a 6day period with experts
initially available to provide
hand-on consultations
followed by telephone
support
Findings/Outcomes
Risk-adjusted
mortality increased
form 2.8% (average)
in the 4 quarters prior
to CPOE
implementation to
6.6% (average) in the
2 quarters after
implementation.
10
Author
Study Purpose
HIT Element(s)
Healthcare Setting
O'Neill L, Klepack
W. “Electronic
medical records for a
rural family practice:
a case study in
systems
development.”
Journal of Medical
Systems 2007; 31:
25-33.
Describe the
implementation
and impact of an
EHR system.
EHR
Rural family practice.
Evaluated
There were 3 phases over
2+ years: a) building EHRs
and learning the system, b)
connecting with clinical
partners, and c) quality
management / disease
management
(implementation
strategy)
Findings/Outcomes
Case mix increased
10% in 2 years
Patient volume per
physician did not
change, so time spent
with each patient did
not decrease.
All staff in this small clinic
(4 MDs) used system for
ALL visits (system
penetration)
Office manager took lead
in educating the other staff.
Used vendor who had
previously supplied billing
and scheduling
systems.(facilitators)
Older physicians were less
familiar with computers.
(barriers)
11
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Palen TE, Raebel M,
Lyons E, Magid DM.
“Evaluation of
laboratory
monitoring alerts
within a
computerized
system for
medication orders.”
American Journal of
Managed Care
2006; 12: 389-95.
To evaluate
whether
reminders during
CPOE for
medications
would increase
compliance with
guidelines for
laboratory mo
nitoring at
initiation of
therapy
CPOE, EHR,
medication
prescribing
support
Physicians from 16
ambulatory practice
sites of a groupmodel managed
care organization
Smith DH, Perrin N,
Feldstein A, Yang X,
Kuang D, Simon SR,
Sittig DF, Platt R,
Soumerai SB. “The
impact of prescribing
safety alerts for
elderly persons in an
electronic medical
record: an
interrupted time
series evaluation.”
Archives of Internal
Medicine 2006; 166:
1098-104.
To examine the
effects of CPOE
with decision
support on
reducing the use
of potentially
contraindicated
agents in elderly
patients
CPOE,
medication
prescribing
support
Primary care
providers in a group
model HMO in the
Pacific Northwest
Evaluated
Implementation strategy
included one-on-one
detailing of each
intervention clinician to
train in where to find the
alerts and how to use the
information to alter dosing
or order labs at the time of
medication ordering
Clinicians were prompted
for the preferred
medication and choosing
this medication resulted in
an automatically populated
order ready for signature
(facilitator)
Decreases in use of nonpreferred agents was
sustained over the 2-year
post-alert period
Findings/Outcomes
No significant
difference found
between control and
intervention
physicians in their
overall rate of
compliance with
ordering
recommended
laboratory monitoring.
A sudden decrease in
rates of initial
dispensing of
nonpreferred agents
among elderly
patients was observed
when the alerts were
initiated, from 21.9 to
16.8 per 10,000
(p<0.01)
12
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Steele AW, Eisert S,
Witter J, Lyons P,
Jones MA, Gabow
P, Ortiz E. “The
effect of automated
alerts on provider
ordering behavior in
an outpatient
setting.” PLoS
Medicine 2005; 2:
e255.
To determine the
impact of using
computerized
alerts to improve
the prescribing of
medications
medication
prescribing
support
Large public
outpatient clinic in
Denver, Colorado
Evaluated
No specific provider
education was given to
staff (implementation
strategy)
82% of clinic clients are
Hispanic, 42% had
Medicaid, 41% were
uninsured, 17% had
Medicare, or private
insurance. (financial
context)
The content and layout of
the specific alert screens
were design by IT staff with
input from the clinic
providers.(facilitators)
Findings/Outcomes
When the alert was
for an abnormal lab
value, the % of times
the medication order
was discontinued
increased from 5.6%
at baseline to 10.9%
during the intervention
(p=.03). When an
alert was triggered for
a missing lab test, the
% of times the
provider ordered the
test increased from
43.0% at baseline to
62.0% (p<.001).
13
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Toth-Pal E, Nilsson
GH, Furhoff AK.
“Clinical effect of
computer generated
physician reminders
in health screening
in primary health
care--a controlled
clinical trial of
preventive services
among the elderly.”
International Journal
of Medical
Informatics 2004; 73:
695-703.
To evaluate the
effects of a
program for
computer
generated
physician
reminders,
integrated with an
EHR system, for
health screening
in elderly
patients.
Clinical
reminders
during patient
encounter
Four primary health
care centers in
suburban Sweden
Evaluated
None reported
Findings/Outcomes
There was a
statistically significant
moderate or marked
increase in the
number of patients
who were tested in all
five intervention
areas. A significant
increase in
pathological test
results (1-8%) was
found for hypertension
and cobalamin
deficiency.
14
Table 3. Evidence Table of Stand-Alone HIT Applications
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Cavanagh K,
Shapiro DA, Van Den
Berg S, Swain S,
Barkham M,
Proudfoot J. “The
effectiveness of
computerized
cognitive behavioural
therapy in routine
care.” British Journal
of Clinical
Psychology 2006; 45:
499-514.
To study
effectiveness of
"Beating the
Blues", a
computerized
cognitive
behavioral
therapy (CCBT)
program, when
implemented in
primary and
secondary
settings with
minimal research
support
To test whether
patient-directed
electronic
messages
improve
completion of a
health care proxy
(HCP) in the
medical record
and knowledge
regarding HCP
patient decision
support/consumer
health informatics
8 general practices,
2 community mental
health teams and 1
primary care clinical
psychology service
in England. Patients
had anxiety and/or
depression and had
been identified by a
health professional
as likely to benefit
from CCBT
administrative
electronic
communication
Patients of Beth
Israel Deaconess
Medical Center who
subscribed to
PatientSite, an
online electronic
communication
system
Cintron A, Phillips R,
Hamel MB. “The
effect of a webbased, patientdirected intervention
on knowledge,
discussion, and
completion of a
health care proxy.”
Journal of Palliative
Medicine 2006; 9:
1320-8
Implementation
Factors Evaluated
Implementation
strategy included
orientation for
patients to the
computer program at
initial visit and
support as needed
at each subsequent
visit
None reported
Findings/Outcomes
Compared to pretreatment ratings,
patients
demonstrated
statistically significant
improvements in the
Clinical Outcomes in
Routine EvaluationOutcome Measure
(CORE-OM), Work
and Social
Adjustment Scale
(WSA) and selfreported anxiety and
depression.
There were no
differences in
completion of an
HCP for intervention
vs control subjects
though intervention
patients were more
likely to report
knowledge of HCPs
15
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Cunningham JA,
Humphreys K, Kypri
K, van Mierlo T.
“Formative evaluation
and three-month
follow-up of an online
personalized
assessment feedback
intervention for
problem drinkers.”
Journal of Medical
Internet Research
2006; 8: e5.
To assess the
effect of a new
module assessing
problem drinking,
when added to an
existing webbased online selfhelp service for
problem drinking
patient decision
support / consumer
health informatics
348 registered
participants of
another online selfhelp center, the Stop
Smoking Center with
138 accessing the 3month follow-up
survey and 81
providing complete
data to test
effectiveness.
Grime PR.
“Computerized
cognitive behavioural
therapy at work: a
randomized
controlled trial in
employees with
recent stress-related
absenteeism.”
Occupational
Medicine 2004; 54:
353-9.
To evaluate the
effect of an 8
week CCBT
program "Beating
the Blues" on
emotional distress
in employees with
recent stressrelated
absenteeism and
to explore
reasons for nonparticipation
Patient decision
support / consumer
health informatics
NHS and local
authority employees
recruited by a
London NHS
occupational health
department who
were eligible if they
had ten or more
days of sickness
absence due to
stress, anxiety or
depression in the
past 6 months and
scored 4 or more on
the GHQ-12
(General Health
Questionnaire)
Implementation
Factors Evaluated
None reported
Differences were
not statistically
significant at 3 and 6
months posttreatment
(sustainability)
Findings/Outcomes
Of the participants
who provided
complete follow-up
data (81 out of the
original 388),
reductions in drinking
were reported.
At the end of
treatment, adjusted
mean depression
scores were 3.07
lower and adjusted
mean negative
attributional style
scores were 2.32
lower in the
intervention group.
At one month posttreatment, adjusted
mean anxiety,
depression and
negative attributional
style scores were
lower in the
intervention group.
16
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Jacobi C, Morris L,
Beckers C, BronischHoltze J, Winter J,
Winzelberg AJ,
Taylor CB.
“Maintenance of
internet-based
prevention: a
randomized
International Journal
of Eating Disorders
2007; 40: 114-9.
To evaluate 3
month effects of
an internet eating
disorder
prevention
program
patient decision
support/consumer
health informatics
Internet-based
prevention program
for eating disorders
in young German
females
McMahon GT,
Gomes HE, Hickson
Hohne S, Hu TM,
Levine BA, Conlin
PR. “Web-based care
management in
patients with poorly
controlled diabetes.”
Diabetes Care 2005;
28: 1624-9.
To assess the
effects of webbased care
management on
glucose and blood
pressure control
over 12 months in
patients with
poorly controlled
diabetes
patient decision
support/consumer
health informatics
Veteran patients
with poorly
controlled diabetes
who had a VA
Boston Healthcare
System primary care
provider and access
to a telephone
Implementation
Factors Evaluated
Overall usability was
rated as “good”
(mean 2.00 with 1.00
being best
(facilitator).
Study provided
computers and
internet access to
participants
(facilitators)
Findings/Outcomes
Intervention
produced significant
and sustained effects
in knowledge test,
shape concerns, and
eating restraint. Web
site use compliance
was 72%.
Greater decline in
A1c over time for the
web-based group (1.6 +/- 1.4%)
compared to usual
care (-1.2 +/- 1.4%).
Persistent users had
greater declines (-1.9
+/- 1.2%) compared
to intermittent users
(-1.2 +/- 1.4%) or
usual care.
Hypertensive
patients in the webbased group had
greater decline in
systolic BP (-10 +/17 mmHg) than usual
care (-7 +/- 21
mmHg).
17
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Proudfoot J, Ryden
C, Everitt B, Shapiro
DA, Goldberg D,
Mann A, Tylee A,
Marks I, Gray JA.
“Clinical efficacy of
computerised
cognitive-behavioural
therapy for anxiety
and depression in
primary care:
randomised
controlled trial.” The
British Journal of
Psychiatry 2004; 185:
46-54.
To determine the
impact of clinical
and demographic
variables on the
efficacy of
“Beating the
Blues”, a CCBT
program for
anxiety and
depression
Patient decision
support / consumer
health informatics
Patients aged 18-75
with depression,
mixed anxiety and
depression or
anxiety disorder not
currently receiving
psychological
treatment recruited
from general
practices in London
and southeast
England
Implementation
Factors Evaluated
A nurse checked
that the patient had
logged on
successfully at the
beginning of each
session and ensured
that the patient had
the necessary printouts at the end of
the session
(facilitator)
Findings/Outcomes
The computerized
CBT program
improved depression,
negative attributional
style, and work and
social adjustment
and was not affected
by whether patients
were prescribed
drugs or by length or
severity of illness.
Anxiety and positive
attributional style
also improved with
CBT and improved
more for more
disturbed patients.
18
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Wagner B,
Knaevelsrud C,
Maercker A.
“Internet-based
cognitive-behavioral
therapy for
complicated grief: a
randomized
Death Studies 2006;
30: 429-53.
To evaluate an
Internet-based
cognitive
behavioral
therapy program
for complicated
grief
electronic
communication
German-speaking
participants from
around the world.
Implementation
Factors Evaluated
None reported
Findings/Outcomes
The decrease in
intrusion and
avoidance symptoms
in the treatment
group was
significantly larger
than in the control
group. 85% of
patients rated the
email contact with
therapist pleasant
(versus unpleasant
or don’t know). 82%
described the
therapeutic contact
as personal; 85%
had positive attitudes
towards internet
treatment. 20%
missed face-to-face
contact with a
therapist.
19
Table 4. Evidence Table of Implementation Factor/Barriers Studies
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Cutler DM, Feldman
NE, Horwitz JR.
“U.S. adoption of
computerized
systems.” Health
Affairs (Millwood)
2005; 24: 1654-63.
To evaluate the
types of hospitals
that have
implemented
CPOE and
potential reasons
for low rates of
implementation
CPOE
Leapfrog Group's
Hospital Patient Safety
Survey, Version 1,
which surveyed
hospitals in 22
geographic regions.
More than 60% were
from California, New
York, and New Jersey
Jha AK, Ferris TG,
Donelan K,
DesRoches C,
Shields A,
Rosenbaum S,
Blumenthal D. “How
common are
electronic health
records in the United
States? A summary
of the evidence.”
Health Affairs
(Millwood) 2006; 25:
w496-507
To estimate EHR
adoption in the
US by
systematically
reviewing existing
surveys of EHR
adoption and use
EHR,
hospital/inpatient,
outpatient/ambulatory
pediatrics;
included only those
surveys in which the
underlying population of
interest consisted of
physicians, physician
group practices or
hospitals
Implementation
Factors Evaluated
Government
hospitals more
likely to report full
implementation of
CPOE than private
nonprofit or forprofit hospitals;
teaching hospitals
and large hospitals
are more likely to
invest in CPOE;
hospital profitability
is not associated
with CPOE
investment
About 24% of
physicians use an
EHR; about 5%
have CPOE
(system
penetration)
Findings/Outcomes
None reported
None reported
Large physician
offices were much
more likely to have
an EHR than solo
or small physician
practices (39% v.
16%) (barriers)
20
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Kemper AR, Uren
RL, Clark SJ.
“Adoption of
electronic health
records in primary
care pediatric
practices.” Pediatrics
2006; 118: e20-4.
To assess
adoption of EHR
EHR
outpatient / ambulatory
pediatrics - random
sample of primary care
pediatricians
Lindenauer PK, Ling
D, Pekow PS,
Crawford A, NaglieriPrescod D, Hoople
N, Fitzgerald J,
Benjamin EM.
“Physician
characteristics,
attitudes, and use of
computerized order
entry.” Journal of
Hospital Medicine
2006; 1: 221-30.
To assess the
adoption of CPOE
and the predictors
of use of CPOE
by attending
physicians at 2
community
hospitals where
the use of CPOE
is voluntary
CPOE
one 600-bed teaching
hospital (where
residents but not
attendings are required
to use CPOE) and one
125-bed community
hospital (where use of
CPOE is voluntary) in
Massachusetts
Implementation
Factors Evaluated
Cost was the main
barrier identified to
adoption of an EHR
by pediatric
practices that did
not have an EHR
(n=415), named in
94% of practices,
followed by inability
to find an EHR that
met the practice
needs (80%) and
physician
resistance (77%)
Belief that CPOE
may lead to fewer
errors (facilitator)
Belief that CPOE
may not support
workflow, may be
slower than written
orders and may not
result in faster
implementation
(barriers)
Findings/Outcomes
None reported
Medium and high
utilizers of the CPOE
system were more likely
to believe that CPOE
led to fewer medication
and non-medication
errors, and helps to
ensure that important
aspects of care do not
slip through the cracks.
21
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Lium JT, Laerum H,
Schulz T, Faxvaag A.
“From the front line,
report from a near
paperless hospital:
mixed reception
among health care
professionals.”
Journal of the
American Medical
Informatics
Association 2006; 13:
668-75.
To assess effects
on use and
efficiency of
continued use of
an EHR
EHR
community hospital
serving a population of
about 100,000 people
in southern Norway
McInnes DK,
Saltman DC, Kidd
MR. “General
practitioners' use of
computers for
prescribing and
electronic health
records: results from
a national survey.”
The Medical Journal
of Australia 2006;
185: 88-91.
To describe how
general
practitioners use
computers for
clinical functions
CPOE, EHR,
electronic
prescribing
stratified random
sample of Australian
general practitioners
Implementation
Factors Evaluated
None reported
About 90% of
Australian general
practitioners were
using a clinical
software packages,
the most common
use being
prescribing &
checking for drugdrug interactions.
(system
penetration)
Findings/Outcomes
Compared with 2002,
there was a significant
increase in the use of
the EHR for 11 of 19
tasks relevant to
physicians, such as
check and sign
discharge summaries
(which was at 100% in
2005), obtain results of
new tests, ordering
tests, etc. Nurses also
reported increased use
in 13 of 19 tasks
relevant to them,
including obtaining of
results of investigations,
reviewing the patient's
problem, and collecting
data for the nurses'
summarizing report.
None reported
22
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Menachemi N.
“Barriers to
ambulatory EHR:
who are 'imminent
adopters' and how do
they differ from other
physicians?”
Informatics in
Primary Care 2006;
14: 101-8.
To determine the
characteristics of
imminent
adopters
EHR
probability sample of
Florida primary care
and specialist
physicians, with a 28%
response rate
Implementation
Factors Evaluated
"Upfront" costs of
hardware and
software were the
most commonly
named barrier to
adoption by both
"imminent
adopters" and
physicians not
considering EHR
adoption, being
cited by 69% and
70%, respectively.
Ongoing
maintenance costs,
inadequate return
on investment,
perceived
difficulties in data
entry and lack of
uniform standards
were also
commonly named
as barriers
Findings/Outcomes
NR
23
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Pizzi LT, Suh DC,
Barone J, Nash DB.
“Factors related to
physicians' adoption
of electronic
prescribing: results
from a national
survey.” American
Journal of Medical
Quality 2005; 20: 2232.
To identify factors
related to
physicians'
adoption of
electronic
prescribing for
outpatients
electronic
prescribing
any outpatient setting
Implementation
Factors Evaluated
Only 19% of
responding MDs
used electronic
prescribing.
(system
penetration)
Findings/Outcomes
None reported
Electronic
prescribers were
significantly more
likely to be general
practitioners versus
specialists and
working at
academic or
publicly-funded
centers. Electronic
prescribers were
younger.
(facilitators)
The most
commonly reported
barriers included:
system costs; time
required to install
the system, train,
and change
prescribing
behavior; and
uncertainty about
which local
pharmacies accept
electronic
prescriptions.
52% of traditional
(paper) prescribers
either
Source: Authors’ analysis of results from 2007 Systematic Review of the HITwere
Literature
considering or
ready to implement
electronic
24
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Schmittdiel J,
Bodenheimer T,
Solomon NA, Gillies
RR, Shortell SM.
“Brief report: The
prevalence and use
of chronic disease
registries in physician
organizations. A
national survey.”
Journal of General
Internal Medicine
2005; 20: 855-8.
To determine the
prevalence of
disease registries
in physician
organizations and
the extent to
which they are
used to improve
care
data
collection/data
summary
systems
Medical groups and
independent practice
associations (IPAs) in
the United States
Implementation
Factors Evaluated
47% of physician
groups had at least
one chronic
disease registry.
Diabetes registries
were the most
common. (system
penetration)
Findings/Outcomes
Organizations with
registries were more
likely to provide
feedback to MDs on
patients’ use of
medications and visits,
as well as reminders to
patients for retinopathy
exams.
Physician
organizations that
had better IT and
greater incentives
for quality were far
more likely to have
registries. Larger
organizations (200
or more MDs) were
more likely to have
registries.
(facilitators)
25
Author
Study Purpose
HIT Element(s)
Healthcare Setting
Stevenson KB,
Barbera J, Moore
JW, Samore MH,
Houck P.
“Understanding keys
to successful
implementation of
electronic decision
support in rural
hospitals: analysis of
a pilot study for
antimicrobial
prescribing.”
American Journal of
Medical Quality
2005; 20: 313-8.
To evaluate the
impact of an
internet-based
clinical DSS on
empiric
antimicrobial
prescribing for
community
acquired
pneumonia in
rural hospitals in
Idaho
Medication
prescribing
support
Patients with
community-acquired
pneumonia admitted to
five rural hospitals in
Idaho that were
involved in a local rural
health network
Implementation
Factors Evaluated
Providers were
unwilling to enter
data directly in the
Antibiotic Assistant
because of
perceived time
requirements so
each hospital was
asked to organize
an AMT to enter
data (barrier)
Findings/Outcomes
There was a significant
improvement in
agreement with all
treatment
recommendations and
agreement with
recommended dose or
antimicrobial agent
subsequent to the
intervention, but this
improvement was
primarily accounted for
by the performance of
one hospital
26

Editor’s Note:

Transcription

Similar documents

- Bob the Builder

love... - Devonshire Mall

Matthew`s game - Parkfield Primary School

Closing Pandora`s Box on Free-Text CPOE Orders

smart healthcare consumer

Volume 12 Version F

Using the Hauppauge WinTV DVB-T Electronic

Hits of the Sixties 2

Electchester Housing Companies - AFL

Rebelmix One Sheet v20080317