An overview of the methods and data used in the CCORT Canadian

KENNEDY.qxd
4/20/2006
3:14 PM
Page 6
CCORT ATLAS PAPER
Chapter 2: An overview of the methods and data used in
the CCORT Canadian Cardiovascular Atlas project
Courtney C Kennedy MSc1, Susan E Brien PhD1, Jack V Tu MD PhD1,2,
for the Canadian Cardiovascular Outcomes Research Team
CC Kennedy, SE Brien, JV Tu for the Canadian Cardiovascular
Outcomes Research Team. An overview of the methods and data
used in the CCORT Canadian Cardiovascular Atlas project.
Originally published in Can J Cardiol 2003;19(6):655-663.
The Canadian Cardiovascular Atlas project, an initiative of the
Canadian Cardiovascular Outcomes Research Team (CCORT), will
be published as a series of 24 articles in future issues of The Canadian
Journal of Cardiology. Through a wide range of data sources and analyses from a number of collaborators across Canada, the CCORT Atlas
will provide a comprehensive overview of the current state of cardiac
care and disease in Canada. Administrative data, clinical registries
and community survey data will be analyzed at the provincial and
health region levels. The purposes of this article are to 1) provide an
overview of the data types and sources used in the Atlas project,
2) give a general description of the methods and analyses used to
report Atlas data and 3) describe how Atlas maps were created and
how they can be interpreted.
Aperçu des méthodes et des données utilisées
dans l’Atlas cardiovasculaire canadien
L’Atlas cardiovasculaire canadien, initiative de l’Équipe canadienne de
recherche en services cardiovasculaire, sera publié en une série de
24 articles dans les prochains numéros du Journal canadien de
cardiologie. S’appuyant sur un large éventail de sources de données et sur
des analyses faites par un certain nombre de collaborateurs partout au
Canada, l’Atlas dressera un tableau complet de la situation actuelle en ce
qui concerne les soins et les maladies cardiovasculaires au Canada. Les
données administratives, les registres cliniques et les données d’enquêtes
communautaires seront analysés aux niveaux des provinces et des régions
sanitaires. Le présent article vise trois objectifs : donner un aperçu des
types et des sources de données utilisés dans l’Atlas; décrire globalement
les méthodes et les analyses utilisées pour consigner les données de
l’Atlas; expliquer la façon dont les cartes de l’Atlas ont été dressées et la
façon de les interpréter.
Key Words: Administrative data; Atlas; Canada; Cardiovascular
disease; Small area variation
he Canadian Cardiovascular Atlas project, an initiative of
the Canadian Cardiovascular Outcomes Research Team
(CCORT), is a comprehensive national report on the state
of cardiovascular health and health services across Canada.
The Atlas material will be published as a series of 24 articles
in future issues of The Canadian Journal of Cardiology. An
earlier paper in this Journal provided an overview of upcoming topics and described the rationale and objectives of the
Atlas project (1).
The Atlas project was produced through the combined
effort of over 30 CCORT investigators, programmers, research
coordinators and other collaborators from across Canada. The
extensive clinical and research expertise of team members,
combined with a willingness to share multiple data sources,
enabled the Atlas team to conduct a more detailed and wider
range of analyses than has ever been done before in cardiovascular outcomes research in Canada. While each article will
T
describe methods specific to that particular study, the purpose
of this article is to
1) Describe the data sources used in the Atlas project;
2) Summarize the major types of analyses conducted;
3) Explain how health regions were defined and how maps for
cardiovascular disease in Canada were created;
4) Outline data privacy and confidentiality procedures used
throughout the Atlas project.
DATA SOURCES
The Atlas used three major types of data sources: administrative databases, clinical registries and population-based surveys.
Table 1 provides a list of the major databases used in the Atlas
project.
A complete list of CCORT investigators is published at www.ccort.ca
for Clinical Evaluative Sciences, Toronto; 2Division of General Internal Medicine and the Clinical Epidemiology and Health Care
Research Program, Department of Medicine, Sunnybrook and Women’s College Health Sciences Centre, University of Toronto, Toronto,
Ontario
Correspondence and reprints: Dr Jack V Tu, Institute for Clinical Evaluative Sciences, G106-2075 Bayview Avenue, Toronto, Ontario
M4N 3M5. Telephone 416-480-4700, fax 416-480-6048, e-mail [email protected]
Received for publication March 11, 2003. Accepted March 25, 2003
1Institute
6
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
KENNEDY.qxd
4/20/2006
3:14 PM
Page 7
CCORT Atlas methods
TABLE 1
Major databases used in the Canadian Cardiovascular Atlas project
Database
Type of data
Years
Description
APPROACH
Clinical registry or
1995/96 to
Clinical data capturing cardiac catheterization patients in Alberta (since 1995),
surveillance
1999/2000
BC Cardiac Registries
Clinical registry
1995/96 to
BC PharmaCare Plan
Administrative
1996/97 to
BC (since 1999) and Saskatchewan (since 2000)
BC provincial registry for cardiac surgery, pacemaker and angioplasty procedures
1999/2000
and, as of May 1999, diagnostic catheterization procedures
Data from the provincial drug insurance program for BC; eligible people are
1998/99
seniors (aged 65 and over), long-term care residents, social assistance recipients
and families with costs exceeding a set deductible
Canadian Community
Survey
September 2000 to
Administrative
1995 to 1997
The national registry of deaths in Canada, consolidated from provincial vital
Administrative
1994/95 to
Data collected for all provinces except Quebec and parts of Manitoba from hospital
Health Survey
Canadian Mortality
Population survey data capturing health determinants, health status and health
October 2001
system use variables for all 136 Canadian health regions
Database
CIHI DAD
statistics data
1999/2000
discharge summaries containing demographic information and diagnostic,
procedural and comorbidity codes
CIHI Hospital Morbidity
Administrative
Database
1994/95 to
Data downloaded from the CIHI DAD (most provinces) or submitted by the provincial
1999/2000
ministry of health for all provinces in Canada; patient separations from a hospital,
listed by primary diagnoses, for all provinces and territories
ECHO
Clinical or chart review
1997 to 1998
Clinical data (chart review) of a sample of first CHF admissions from 14 hospitals in
EFFECT
Clinical or chart review
1999 to 2001
Clinical data (chart review) of a sample of acute myocardial infarction and CHF
FASTRAK II
Clinical registry
January 2000 to
Clinical data (patients with acute myocardial infarction) from participating Canadian
ICONS
Clinical registry
October 1997 to
IMS Health Canada
Administrative
February 1996 to
Ontario
patients from 104 hospitals in Ontario
2001/02
coronary care units or cardiac wards
Clinical data (primary chart audit) on all Nova Scotia residents hospitalized with
April 2002
Compuscript Audit
acute coronary syndrome, CHF and atrial fibrillation
Data on the number of prescriptions dispensed by over 4400 Canadian pharmacies
January 2002
(nearly two-thirds of all retail pharmacies in Canada)
Database
Maritime Heart Centre
Clinical registry
Cardiac Surgery Database
March 1995 to
Detailed prehospital, in-hospital and postoperative information on all patients under-
1999/2000
Med-Echo
Administrative
1997/98 to
ODB
Administrative
1997/98 to
going cardiac surgery at a Halifax, Nova Scotia, hospital
Clinical and demographic data for acute care Quebec CVD inpatients
1999/2000
Data from the provincial drug insurance program for Ontario; eligible people are
1999/2000
seniors (aged 65 and over), long-term care residents, and home care and social
assistance recipients
RAMQ
Administrative
1997/98 to
Data from the provincial drug insurance program for Quebec; eligible people are
1999/2000
seniors (aged 65 and over), recipients of employment assistance or those without
access to group insurance
Statistics Canada Census
Census
1991
Information about Canada’s demographic, social and economic characteristics
APPROACH Alberta Provincial Project on Outcome Assessment in Coronary Heart Disease; BC British Columbia; CHF Congestive heart failure; CIHI Canadian
Institute for Health Information; CVD Cardiovascular disease; DAD Discharge Abstract Database; ECHO Evaulation of Congestive Heart Failure Outcomes;
EFFECT Enhanced Feedback for Effective Cardiac Treatment; ICONS Improving Cardiovascular Outcomes in Nova Scotia; IMS Intercontinental Medical Statistics;
ODB Ontario Drug Benefits; RAMQ La Régie de l’assurance maladie du Québec
Administrative data
Government agencies collect administrative health data for
monitoring and financial purposes, such as auditing, remuneration of physicians, resource allocation, total quality management and comparative analysis. Data elements generally
include demographic data, admission and discharge information, and codes for patient diagnoses, treatments and medical
procedures performed. One of the major shortcomings of
administrative databases is the lack of detailed information on
clinical risk variables. Furthermore, data are not collected primarily for the purpose of research and can include coding
errors and missing or ambiguous information. In contrast,
potential benefits of administrative data are relatively low cost
compared with primary data collection, availability of populationbased information in many jurisdictions, large sample sizes,
long-term follow-up, ability to link to other databases and ready
availability because they are necessarily collected for administrative purposes (2,3). Furthermore, several previous studies
suggest that administrative data, in general, are a reliable way
for health services researchers to study the Canadian health
care system (4).
Since the late 1980s, several studies have specifically
evaluated the accuracy of cardiac coding in Canadian
administrative databases either through chart reabstraction
or by comparison with another data source (eg, clinical registry). Table 2 summarizes this literature, including the study
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
7
KENNEDY.qxd
4/20/2006
3:14 PM
Page 8
Kennedy et al
TABLE 2
Summary of Canadian studies that have validated the accuracy of cardiac diagnoses or procedures in administrative data
First author,
year (reference)
province
Comparison
Construct
data
ICD-8/9
codes
Diagnosis
Specificity/
Agreement sensitivity
(%)
(%)
Design of validation component
Hospital discharge data compared with data from other sources
Austin, 2002 (5)
MRD
Ontario
Clinical
410
AMI
registry
427
Arrhythmia
–
97.8/60.7
92.8/88.8
Most responsible CIHI discharge diagnosis was compared
with the FASTRAK II CCU discharge diagnosis
428
CHF
96.8/58.5
(n=58,816) for AMI (primary goal) and arrhythmia, CHF,
786.5
Chest pain
94.2/44.4
unstable angina and chest pain NYD (secondary goal)
411/413
Unstable
93.9/57.9
angina
Jha, 1996 (7)
Ontario
Death
Clinical
rates
trials
410
AMI
–
93.6/100
Administrative data (Hospital Medical Records Institute)
on admissions and mortality from AMI were linked to
GUSTO I (n=1414) and LATE trial data (n=249);
comparability of death rates was examined
Rawson, 1995 (10) Discharge
Saskatchewan
Roos, 1989 (11)
Manitoba
Roos, 1991 (3)
Manitoba
diagnosis
Physician
claims
410
AMI
69.3
–
IHD patients were identified in the administrative data file
411
Acute IHD
14.6
and compared with matching physician claims (n=4402)
413
Angina
70.0
and abstracted medical charts (n=200) (see below)
414
Chronic IHD
55.6
Discharge
Physician
414, 411,
CABG
82.1
diagnoses
claims
413
61.4
424, 394,
Heart valve
stays
414
replacement
CVD
Clinical
Not
bidities
database
defined
Validity of physician claims for a particular surgery were
compared with hospital discharge abstracts for the stay
for surgical
Comor-
–
in which the surgery took place
–
92.0/43.0
The validity of comorbidity data was examined for several
diseases including CVD; Manitoba claims data (hospital
discharge abstracts) were compared with a clinical database at a large Winnipeg hospital
Reabstraction of hospital discharge data
Rawson, 1995 (10) Discharge
Saskatchewan
–
410
AMI
96.9
–
diagnosis
IHD patients were identified in the administrative data file
and compared with matching physician claims (n=4402)
(see above) and abstracted medical charts (n=224)
Cox, 1997 (6)
MRD
–
410
AMI
88.4
–
Ontario
475 charts (randomly selected from 16 hospitals) related
to AMI were abstracted twice using a checklist with
simplified MONICA criteria and compared with CIHI
diagnosis of AMI
Humphries,
Comor-
2000 (12)
bidities
–
410, 412
Prior MI
428
CHF
–
94.8/66.1
88.3/82.9
British Columbia
Levy, 1999 (8)
Quebec
Primary
–
410
AMI
96
–
discharge
Primary
1990 (13)
discharge
Ontario
diagnosis
Nova Scotia
Saskatchewan
were compared with chart review data collected in PCI
patients (n=817)
Discharge
diagnosis
A random sample of records with a primary discharge
diagnosis of MI (n=234) was compared with medical
diagnosis
van Walraven,
Comorbidity data derived from an administrative database
charts in six Montreal hospitals (patients 65 and older)
–
410
AMI
79.4
–
209 consecutive charts with a primary diagnosis of 410
(on the fact sheet) were reviewed in a Toronto hospital
–
410
AMI
(ICD 8/9)
CVD Epidemiology
≥86.7
Approximately 250 charts in each province (random
sample) were reviewed to estimate the false-positive
negative
rate for an AMI discharge diagnosis; 500 charts with
≤8.4)
Group, 1992 (9)
–
(false
411 to 414 diagnoses were reviewed to determine the
AMI false-negative rate
AMI Acute myocardial infarction; CABG Coronary artery bypass graft surgery; CCU Coronary care unit; CHF Congestive heart failure; CIHI Canadian Institute for
Health Information; CVD Cardiovascular disease; GUSTO I Global Utilization of Streptokinase and t-PA for Occluded Coronary Arteries 1; ICD International
Classification of Diseases; IHD Ischemic heart disease; LATE Late Assessment of Thrombolytic Efficacy; MI Myocardial infarction; MONICA Monitoring trends and
determinants in Cardiovascular disease; MRD Most responsible diagnosis; NYD Not yet diagnosed; PCI Percutaneous coronary intervention
design and the reported level of diagnostic agreement or
specificity and sensitivity of the administrative data evaluated. In general, acute myocardial infarction was the most
well studied and accurately coded diagnosis, producing diagnostic agreement or specificity and sensitivity estimates of
90% or more (5-13).
8
Hospital discharge data
Hospital discharge data were the most common administrative
data sources used in the Atlas project and were obtained from
two sources: 1) the Canadian Institute for Health Information
(CIHI) Discharge Abstract Database (DAD) and 2) the CIHI
Hospital Morbidity Database (HMDB).
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
KENNEDY.qxd
4/20/2006
3:14 PM
Page 9
CCORT Atlas methods
TABLE 3
Standard ICD-9-CM codes used to identify cardiovascular
hospitalizations in the CCORT Canadian Cardiovascular
Atlas
TABLE 5
Canadian population in 1991* by age and sex
Age group
(years)
Males
Females
Combined
% of total
population
ICD-9-CM codes
(at least one of those below)
0 to 04
1,002,469
955,983
1,958,452
7.0
Disease category
05 to 09
991,363
942,483
1,933,846
6.9
Cardiovascular disease
390 to 459
10 to 14
973,036
924,828
1,897,864
6.8
Ischemic heart disease
410 to 414
15 to 19
991,216
936,776
1,927,992
6.9
Congestive heart failure
428.x (428.0 to 428.9)
20 to 24
1,062,179
1,025,803
2,087,982
7.4
Hypertensive disease
401 to 405
25 to 29
1,269,802
1,237,171
2,506,973
8.9
Cerebrovascular disease
430 to 438
30 to 34
1,298,896
1,283,628
2,582,524
9.2
Stroke
430 to 432, 434, 436
35 to 39
1,172,240
1,173,175
2,345,415
8.4
Valvular disease
394 to 397, 424.0 to 424.3
40 to 44
1,068,117
1,060,889
2,129,006
7.6
Acute myocardial infarction
410.x (410.0 to 410.9)
45 to 49
843,971
829,574
1,673,545
6.0
Angina
411, 413
50 to 54
674,865
667,664
1,342,529
4.8
Chest pain
786.5
55 to 59
616,524
618,932
1,235,456
4.4
60 to 64
580,049
612,026
1,192,075
4.3
65 to 69
498,715
588,125
1,086,840
3.9
70 to 74
364,884
470,852
835,736
3.0
75 to 79
255,989
367,465
623,454
2.2
80 to 84
142,435
240,600
383,035
1.4
85 to 89
62,274
130,485
192,759
0.07
0.03
CCORT Canadian Cardiovascular Outcomes Research Team; ICD-9-CM
International Classification of Diseases, ninth revision, Clinical Modification
(23)
TABLE 4
Standard CCP codes used to identify cardiac procedures
in the CCORT Canadian Cardiovascular Atlas
Procedure
CCP codes (at least one
of those below)
Percutaneous coronary intervention
48.02, 48.03, 48.09
CABG
48.11 to 48.19
Isolated valve surgery
47.12, 47.22 to 47.25,
Combined valve or CABG
one of 47.12, 47.22 to 47.25,
≥90
25,468
69,913
95,381
Total
13,894,492
14,136,372
28,030,864
*This standard population was used for age and sex adjustments in many
Atlas analyses. Source: Statistics Canada
47.31 to 47.33
47.31 to 47.33
and one of 48.11 to 48.19
CABG Coronary artery bypass graft surgery; CCORT Canadian
Cardiovascular Outcomes Research Team; CCP Canadian Classification of
Diagnostic, Therapeutic, and Surgical Procedures (24)
The DAD contains information about inpatient hospital
discharges and same-day surgeries from all hospitals across
Canada (except in Quebec and parts of Manitoba) (14,15).
Approximately 75% of all hospital inpatient discharges in
Canada (about 4.3 million records annually) are represented in
this database (15). The HMDB has a smaller subset of the
information contained in the DAD, but includes information
from all 10 Canadian provinces. The HMDB provides a count
of patient separations (through discharge or death) from each
hospital, categorized by the primary disease diagnosis (15).
Clinical registries
Clinical registries or databases contain precise and detailed
information about diagnoses and clinical risk variables; however, their major drawback is the expense of development and
maintenance (16). Although clinical registries vary in the
scope of their data collection, most prospectively or retrospectively collect detailed information on patients, including preexisting medical conditions, current diagnoses and
demographic information. By definition, a clinical database
contains well defined, discrete and continuous data elements
that are routinely recorded and coupled with outcome descriptors (17). Some registries are population-based (eg, all patients
in a province undergoing catheterization), while others are voluntary at either the patient level or the hospital level (ie, the
decision to participate in data collection is made by the individual or, in the case of provincial or national registries, by a
hospital). Clinical databases used by the Atlas project include
the Alberta Provincial Project on Outcome Assessment in
Coronary Heart Disease database (18), the Improving
Cardiovascular Outcomes in Nova Scotia database (19) and
the Enhanced Feedback for Effective Cardiac Treatment database. Clinical databases were not available for every province;
thus, in several cases, Atlas studies compared the characteristics of patients in only a few provinces.
Population health surveys
Population-based health surveys ask specific questions of
health system users and are useful in health services research to
establish the health needs and practices of a population at a
given point in time (ie, they provide a ‘snapshot’ of a population’s health experience) (20). Population-based surveys are
subject to bias because they rely on self or proxy report and the
voluntary participation of randomly selected participants.
The Canadian Community Health Survey (CCHS) Cycle
1.1 (21) was used in the population health section of the
CCORT Atlas. Conducted by Statistics Canada, the CCHS
aims to provide ongoing estimates of health determinants,
health status and health system use across the country.
Covering approximately 98% of the Canadian population aged
12 years or older, the CCHS randomly selected one, and in
some cases two, respondents per household. The total sample
size for Cycle 1.1 was 131,535 household respondents, representing a response rate of 84.7% (22). The CCHS data used in
the Atlas were from the first collection cycle, September 2000
to November 2001. The complete survey instrument is available on the Statistics Canada Web site (www.statcan.ca) (21).
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
9
KENNEDY.qxd
4/20/2006
3:14 PM
Page 10
Kennedy et al
TABLE 6
Definition of health regions for Atlas time period (28,30)
Based on provincial
administrative boundary?
Number
of health
regions
Health region changes
since March 2000*
Province or territory
How health region was defined
Newfoundland/Labrador
Health and community services regions
Yes (implemented 1994)
6
None
Prince Edward Island
Urban and rural division
No†
2
None
Nova Scotia
Health zones
Yes†‡
6
None
New Brunswick
Regional health corporations
Yes (1992 to April 1, 2002)
7
Same boundaries, one additional
Quebec
Regional health authorities/Régies
Yes (implemented 1989)
Ontario
Public health units
No§
37
None
Manitoba
Regional health authorities
Yes (1997 to June 30, 2002)
12
Amalgamation of Marquette and South
Saskatchewan
Service areas (groupings of
No†
11
April 1, 2002: 12 regional health
regional health authority board
18
None
régionales de la santé et des services sociaux
Westman to Assiniboine
the health districts)
authorities replace 32 health district
boards
Alberta
Regional health authorities
Yes (established 1994)
17
May 2002: announced regional health
authorities will be reduced to 5 to 7
by 2004
British Columbia
Regional health boards
Yes (established 1993)
20
Yukon Territory
Not regionalized
–
1
Northwest Territories
Not regionalized
–
1
Nunavut
Not regionalized
–
1
In 2002, boundaries changed to
16 health service delivery areas
*Most data used in the Canadian Cardiovascular Outcomes Research Team Atlas project did not go beyond March 31, 2000; †Statistics Canada created their own
health regions for Prince Edward Island, Nova Scotia and Saskatchewan because legislated health regions in these provinces were relatively small and may not
have been comparable with other Canadian health regions. New health regions were related, but not identical, to existing provincial administrative regions; ‡In Nova
Scotia, three district health authorities were amalgamated with a neighbouring authority; §Health care in Ontario is administered and delivered by the province
(ie, not by regional health authorities)
METHODOLOGICAL OVERVIEW
AND TECHNICAL TERMS
Atlas cohorts were generated using a subset of selected
International Classification of Diseases, ninth revision, Clinical
Modification (ICD-9-CM) codes (23) and Canadian
Classification of Diagnostic, Therapeutic and Surgical Procedures
(CCP) codes (24). Tables 3 and 4 show the standardized
CCORT ICD-9-CM and CCP codes used to identify cardiovascular hospitalizations and procedures. All data in the Atlas
were analyzed according to the fiscal year. For example, the fiscal year for 1998/99 is from April 1, 1998, to March 31, 1999.
Most analyses were conducted using data from 1997/98 to
1999/2000, but databases were queried back to 1992 when
required data elements were available.
Standardized analyses
Utilization analyses (ie, hospitalization rates, procedure rates)
counted all relevant procedures or hospitalizations during a
study period, even if there were two or more events per patient.
Outcome analyses (eg, mortality rates, readmission rates)
counted patients only once in the numerator and once in the
denominator. The majority of Atlas articles report regional
rates based on patient province of residence, not province of
treatment (eg, a British Columbia resident treated in Alberta
was counted in the British Columbia rate). The exception to
this rule was for cardiac procedures: outcomes for patients
treated out of province were attributed to the province of
treatment, not residence.
Hospitalizations were regarded as ‘episodes of care’, ie, if an
admission took place less than 24 h after the previous discharge,
10
the two hospital stays were considered to be the same episode
of care. This was done to ensure an accurate reflection of the
follow-up period and to prevent the counting of transfers as
readmissions.
TYPES OF ANALYSES
Observed or crude rates
An observed or crude rate represents the ‘actual’ experience of
a population and is not adjusted for any factors that may affect
the outcome, such as age, sex and disease comorbidities. Crude
rates are summary measures and are useful for health planning
and resource allocation purposes.
Age-sex-standardized versus risk-adjusted rates
To make comparisons across regions in Canada, most rates
were also adjusted for potentially confounding factors. Some
Atlas analyses used only age-sex adjustment, while others
adjusted for several potential confounders, such as comorbid
conditions (termed risk-adjusted). In general, there was a
very high correlation between age-sex-standardized and riskadjusted rates at the health region level. Use of age-sex
adjustment alone allowed for inclusion of Quebec and
Manitoba data in many Atlas studies even though their
administrative data did not distinguish comorbidities from
complications.
One method used for adjustment of rates was direct standardization. The purpose of direct standardization is to compare rates between regions as if they had similar population
compositions. Rates calculated by direct standardization do
not necessarily reflect the actual or crude rate in a population.
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
KENNEDY.qxd
4/20/2006
3:14 PM
Page 11
CCORT Atlas methods
1001
1002
1003
1004
1005
1006
*
Newfoundland and Labrador (10)
Health and Community Services St. John’s Region
Health and Community Services Eastern Region
Health and Community Services Central Region
Health and Community Services Western Region
Grenfell Regional Health Services Board
Health Labrador Corporation
1101
1102
Prince Edward Island (11)*
Urban Health Region
Rural Health Region
1201
1202
1203
1204
1205
1206
Nova Scotia (12)*
Zone 1
Zone 2
Zone 3
Zone 4
Zone 5
Zone 6
1301
1302
1303
1304
1305
1306
1307
New Brunswick (13)*
Region 1
Region 2
Region 3
Region 4
Region 5
Region 6
Region 7
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
2413
2414
2415
2416
2417
2418
Quebec (24)*
Région du Bas-Saint-Laurent
Région du Saguenay - Lac-Saint-Jean
Région de Québec
Région de la Mauricie et Centre-du-Québec
Région de l’Estrie
Région de Montréal-Centre
Région de l’Outaouais
Région de l’Abitibi-Témiscamingue
Région de la Côte-Nord
Région du Nord-du-Québec
Région de la Gaspésie-Îles-de-la-Madeleine
Région de la Chaudière-Appalaches
Région de Laval
Région de Lanaudière
Région des Laurentides
Région de la Montérégie
Région du Nunavik
Région des Terres-Cries-de-la-Baie-James
3526
3527
3530
3531
Ontario (35)*
Algoma Public Health Unit
Brant Public Health Unit
Durham Public Health Unit
Elgin-St Thomas Public Health Unit
3533
3534
3535
3536
3537
3538
3539
3540
3541
3542
3543
3544
3545
3546
3547
3549
3551
3552
3553
3554
3555
3556
3557
3558
3560
3561
3562
3563
3565
3566
3568
3570
3595
Bruce-Grey-Owen Sound Public Health Unit
Haldimand-Norfolk Public Health Unit
Haliburton-Kawartha-Pine Ridge Public Health Unit
Halton Public Health Unit
Hamilton-Wentworth Public Health Unit
Hastings and Prince Edward Public Health Unit
Huron Public Health Unit
Kent-Chatham Public Health Unit
Kingston-Frontenac-Lennox and Addington Public Health Unit
Lambton Public Health Unit
Leeds-Grenville-Lanark Public Health Unit
Middlesex-London Public Health Unit
Muskoka-Parry Sound Public Health Unit
Niagara Public Health Unit
North Bay Public Health Unit
Northwestern Public Health Unit
Ottawa Carleton Public Health Unit
Oxford Public Health Unit
Peel Public Health Unit
Perth Public Health Unit
Peterborough Public Health Unit
Porcupine Public Health Unit
Renfrew Public Health Unit
Eastern Ontario Public Health Unit
Simcoe Public Health Unit
Sudbury Public Health Unit
Thunder Bay Public Health Unit
Timiskaming Public Health Unit
Waterloo Public Health Unit
Wellington-Dufferin-Guelph Public Health Unit
Windsor-Essex Public Health Unit
York Public Health Unit
City of Toronto Public Health Unit
4610
4615
4620
4625
4630
4640
4650
4655
4660
4670
4680
4690
Manitoba (46)*
Winnipeg
Brandon
North Eastman
South Eastman
Interlake
Central
Marquette
South Westman
Parkland
Norman
Burntwood
Churchill
4701
4702
4703
4704
Saskatchewan (47)*
Weyburn (A) Service Area
Moose Jaw (B) Service Area
Swift Current (C) Service Area
Regina (D) Service Area
4705
4706
4707
4708
4709
4710
4711
Yorkton (E) Service Area
Saskatoon (F) Service Area
Rosetown (G) Service Area
Melfort (H) Service Area
Prince Albert (I) Service Area
North Battleford (J) Service Area
Northern Health Services Branch (K) Service Area
4801
4802
4803
4804
4805
4806
4807
4808
4809
4810
4811
4812
4813
4814
4815
4816
4817
Alberta (48)*
Chinook Regional Health Authority
Palliser Health Authority
Headwaters Health Authority
Calgary Regional Health Authority
Health Authority #5
David Thompson Regional Health Authority
East Central Health Authority
WestView Regional Health Authority
Crossroads Regional Health Authority
Capital Health Authority
Aspen Regional Health Authority
Lakeland Regional Health Authority
Mistahia Regional Health Authority
Peace Regional Health Authority
Keeweetinok Lakes Regional Health Authority
Northern Lights Regional Health Authority
Northwestern Regional Health Authority
5901
5902
5903
5904
5905
5906
5907
5908
5909
5910
5911
5912
5913
5914
5915
5916
5917
5918
5919
5920
British Columbia (59)*
East Kootenay
West Kootenay-Boundary
North Okanagan
South Okanagan Similkameen
Thompson
Fraser Valley
South Fraser Valley
Simon Fraser
Coast Garibaldi
Central Vancouver Island
Upper Island/Central Coast
Cariboo
North West
Peace Liard
Northern Interior
Vancouver
Burnaby
North Shore
Richmond
Capital
6001
Yukon Territory
6101
Northwest Territories
6201
Nunavut
*This is the province prefix, in some geographically small health regions just the last 2 digits of the health region number appear (e.g. In Quebec, health region 2416 is labeled 16).
Figure 1) Health regions (corresponding to numbers above) used in the Canadian Cardiovascular Outcomes Research Team Canadian
Cardiovascular Atlas by population size, 1996
Most direct standardized rates in the Atlas were calculated
using the 1991 Canadian population as the standard population (see Table 5 for the 1991 population breakdown by age
and sex group). This is consistent with publications by other
organizations (25) and is the standard currently used by Health
Canada (26). For certain outcome analyses, the age-sex distribution in the overall study cohort was used as the standard
population.
Another method used for rate adjustment was model-based
indirect standardization, using a regression model. First,
expected rates for regions were calculated using a model that
best predicted the outcome of interest. Then for each region,
the crude rates were divided by expected rates and multiplied
by the overall Canadian average. Resulting rates are considered ‘risk-adjusted’ and can be interpreted as the rates that
would occur if all the time periods or regions of interest had
similar case mixes.
Hospitalization rates
A hospitalization rate is a measure of the number of patient
admissions into hospital for a designated condition, such as a
myocardial infarction. Hospitalization rates are useful for comparing regional use of resources and as a proxy measure of disease burden in a region.
In-hospital mortality rates
In-hospital mortality is a measure of the number of in-hospital
deaths that occurred within 30 days of admission to hospital
for the condition of interest (index admission). In-hospital
mortality is often used as a quality of care marker for the acute
treatment of myocardial infarction or other condition.
Readmission rates
Readmissions rates relate to patients who survived their initial
hospitalization but returned to hospital at least once within
30 days, 90 days or one year of their index admission. To calculate Atlas readmission rates, only patients who survived their
initial hospitalization were included in the denominator. A
readmission rate is a good indicator of whether the efforts to
prevent secondary complications or another event, such as
myocardial infarction, ongoing chest pain and heart failure,
were successful.
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
11
KENNEDY.qxd
4/20/2006
3:14 PM
Page 12
Kennedy et al
12
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
KENNEDY.qxd
4/20/2006
3:14 PM
Page 13
CCORT Atlas methods
Cardiac procedure rates
Cardiac procedure (ie, utilization) rates represent the total number of people in a health region or province undergoing a procedure (cardiac catheterization, coronary artery bypass graft surgery,
percutaneous coronary intervention, valve surgery) per 100,000
population. The purpose of calculating procedure rates is to
understand a region’s rate of use of a particular procedure and
determine variations in clinical practice or available resources.
Median wait time
The median wait time was the time required for half the
patients to receive a procedure (coronary artery bypass graft
surgery or percutaneous coronary intervention). Median wait
times (in days) were calculated for acute myocardial infarction
patients from the point of their initial hospitalization for acute
myocardial infarction to the point of the procedure. Median
wait times are good indicators of the availability of resources
and patient access to care in a region.
Drug utilization rates
Drug utilization rates were reported for both in-hospital and
outpatient treatment phases. These rates provide feedback to
practitioners on whether treatment benchmarks are being met
and reflect the extent of regional variation in Canada.
GEOGRAPHY OF CARDIAC CARE IN CANADA
The Canadian health care system provides comprehensive coverage for medically necessary hospital inpatient and outpatient
physician services (27). With financial assistance from the federal government, each of the 10 provinces and three territories
runs its own health care system and is responsible for managing
and delivering health services in its respective region. However,
in the 1990s, with the objective of streamlining the delivery
system, most provinces partially devolved their responsibilities
to subprovincial regional health authorities (RHAs) (28).
RHAs typically have appointed or elected boards of governance
and are responsible for funding and delivering community and
institutional health services within their defined geographical
region. Depending on the province, RHAs have varied scopes
of responsibilities and differ in terms of geographical and population size (28).
Regional level analyses in the CCORT Canadian
Cardiovascular Atlas (including maps) used the 139 Statistics
Canada-defined ‘health regions’ from December 2001, which,
for most provinces, are based on the geographical boundaries of
RHAs (29). Health regions for British Columbia were the 20
health service delivery areas in existence in January 2002
(before the health service redesign later in 2002). Health
regions in Ontario were defined as public health units (PHUs),
not district health councils, in order to provide as much detail
as possible (district health councils have greater geographical
areas than PHUs). Recent consultations with Ontario stakeholders have indicated a preference for the lowest unit of
aggregation in constructing maps for Institute for Clinical
Evaluative Sciences atlases (30). PHUs and counties have similar geographical boundaries in Ontario. Table 6 provides an
overview of all provincial health regions in existence during
the Atlas study period and changes made since that time. A
master legend of all health region names and boundaries is provided in Figure 1. This map is also shaded according to the
approximate population size of each particular region.
Atlas maps
CCORT Atlas maps were created using MapInfo software
(MapInfo Corp, USA). Maps were subdivided by health region
and, where possible, rate information was displayed for every
health region in Canada. This was not possible in all cases
because of necessary exclusion of regions with known errors in
coding (eg, acute myocardial infarction cases in Newfoundland)
and regions with small sample sizes (eg, the territories). For all
provinces except Quebec and Ontario, patients were assigned to
health regions by converting their enumeration area (EA) code
(assigned by CIHI) to a health region code, using the Statistics
Canada Postal Code Conversion file. For people who were missing an EA code, and for all patients of Ontario, the first three
digits of their postal code were converted to an EA code by
using a postal code conversion program. Health region codes
were directly provided for Quebec patients.
Health regions were colour coded on the maps according to
how their regional rate compared with the Canadian average.
First, the regional rate was divided by the overall Canadian
rate to obtain a rate ratio. Then each health region was
assigned a colour based on which of the following fixed ratio
groups it fell into: minimum to less than 0.75, 0.75 to less than
0.90, 0.90 to less than 1.10, 1.10 to less than 1.30, or 1.30 or
greater. For example, a region that had a rate that was at least
30% higher than the Canadian average fell within the highest
ratio category (at least 1.30) and appeared on the map as dark
red. A region that had a rate at least 25% less than the
Canadian average fell into the lowest ratio category (less than
0.75) and appeared on the map as yellow. Regions with rates
that fell into the middle categories (0.75 to less than 0.90, 0.90
to less than 1.10, 1.10 to less than 1.30) were coloured in
sequential shades of orange. Regions shaded in grey indicated
that data were not available or were suppressed because of confidentiality issues. In the map legend, the actual rates per 100
patients or 100,000 population were presented instead of the
fixed ratio categories (ie, the range of rates that corresponded
to the cutpoints in the ratio category) to provide readers with
more usable information. However, it should be noted that,
although the actual rates were different for each map, the
underlying fixed ratio categories were identical in every map.
Fixed ratio categories used in the CCORT Atlas were first
used by the Dartmouth Atlas of Cardiovascular Health Care (31) in
the United States. Instead of using quintiles, the Dartmouth
group chose cutpoints based on clinical significance and symmetry about 1.0. Rates that vary less than 10% of expected are not
clinically meaningful variations, and those that are higher than
30% of expected values are of potential concern. The chosen
corresponding lower bounds (ie, 0.75, 0.90) are approximate
reciprocals of the upper bounds. Because the variability in the
colours on a map should reflect the variability of the data, a
major benefit of the Dartmouth approach is that if the data are
tightly clustered around the mean, the two extreme colours will
not appear on the map.
PRIVACY AND CONFIDENTIALITY
CCORT investigators are firmly committed to protecting the
privacy of all patients whose health information was used in
the production of the Atlas project. To prevent any possibility
that patients could be identified, the Atlas does not report on
1) cell sizes less than five, 2) health regions with fewer than 50
cases, 3) health regions with fewer than two hospitals serving a
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology
13
KENNEDY.qxd
4/20/2006
3:14 PM
Page 14
Kennedy et al
region, and 4) health regions with fewer than two physicians
serving patients in that region. Research ethics approval for
the CCORT Atlas project was received from the Sunnybrook
and Women’s College Health Sciences Research Ethics Board
and the University of Toronto. All participating investigators
signed a data privacy and confidentiality agreement as part of
the Atlas project.
CONCLUSION
The CCORT Canadian Cardiovascular Atlas used data from
the CIHI DAD, clinical registries and the CCHS.
Standardized ICD-9-CM and CCP codes were used to identify
cardiovascular hospitalizations and procedures. Major types of
analyses in the Atlas included crude and age-sex or risk-adjusted
rates for in-hospital mortality, readmission, hospitalization,
cardiac procedures and drug use. Where possible, rates were
calculated for every health region in Canada and were represented geographically in colour-coded national maps. We
hope that the methods used in the Atlas will serve as a template for future research endeavours of this nature in
Canada.
ACKNOWLEDGEMENTS: The authors would like to acknowledge Woganee A Filate for her assistance with preparing the manuscript. The CCORT Canadian Cardiovascular Atlas project was
supported by operating grants to the Canadian Cardiovascular
Outcomes Research Team from the Canadian Institutes for Health
Research Interdisciplinary Health Research Team program and
the Heart and Stroke Foundation. Dr Tu is supported by a Canada
Research Chair in Health Services Research.
REFERENCES
1. Tu JV, Brien SE, Kennedy CC, Pilote L, Ghali WA An introduction
to the Canadian Cardiovascular Outcomes Research Team’s
(CCORT) Canadian Cardiovascular Atlas project. Can J Cardiol
2003;19:225-9.
2. Iezzoni LI. Assessing quality using administrative data. Ann Intern
Med 1997;127(Suppl 8):666-74.
3. Roos LL, Sharp SM, Cohen MM. Comparing clinical information
with claims data: Some similarities and differences. J Clin Epidemiol
1991;44:881-8.
4. Williams JI, Young W. Inventory of Studies on the Accuracy of
Canadian Health Administrative Databases. Working Paper.
Toronto: Institute for Clinical Evaluative Sciences, 1996.
5. Austin PC, Daly PA, Tu JV. Multicenter study of the coding accuracy
of hospital discharge administrative data for patients admitted to
cardiac care units in Ontario. Am Heart J 2002;144:290-6.
6. Cox JL, Melady MP, Chen E, Naylor CD. Towards improved coding
of acute myocardial infarction in hospital discharge abstracts: A pilot
project. Can J Cardiol 1997;13:351-8.
7. Jha P, Deboer D, Sykora K, Naylor CD. Characteristics and mortality
outcomes of thrombolysis trial participants and nonparticipants:
A population-based comparison. J Am Coll Cardiol 1996;27:1335-42.
8. Levy AR, Tamblyn RM, Fitchett D, McLeod PJ, Hanley JA. Coding
accuracy of hospital discharge data for elderly survivors of myocardial
infarction. Can J Cardiol 1999;15:1277-82.
9. The Nova Scotia-Saskatchewan Cardiovascular Disease
Epidemiology Group. Trends in incidence and mortality from acute
myocardial infarction in Nova Scotia and Saskatchewan 1974 to
1985. Can J Cardiol 1992;8:253-8.
10. Rawson SB, Malcolm E. Validity of the recording of ischaemic heart
disease and chronic obstructive pulmonary disease in the
saskatchewan health care datafiles. Stat Med 1995;14:2627-43.
11. Roos LL, Sharp SM, Wajda A. Assessing data quality:
A computerized approach. Soc Sci Med 1989;28:175-82.
12. Humphries KH, Rankin JM, Carere RG, Buller CE, Kiely FM,
Spinelli JJ. Co-morbidity data in outcomes research: Are clinical data
derived from administrative databases a reliable alternative to chart
review? J Clin Epidemiol 2000;53:343-9.
13. van Walraven C, Wang B, Ugnat AM, Naylor CD. False-positive
coding for acute myocardial infarction on hospital discharge records:
Chart audit results from a tertiary centre. Can J Cardiol 1990;6:383-6.
14. Richards J, Brown A, Homan C. The data quality study of the Canadian
Discharge Abstract Database. In: Proceedings of Statistics Canada
Symposium 2001 – Achieving Data Quality in a Statistical Agency:
A methodological perspective. Quebec: Statistics Canada, 2001.
14
15. Canadian Institute for Health Information. Health Services
Databases. http://www.cihi.ca (August 2002).
16. Hannan EL, Kilburn H, Lindsey ML, Lewis R. Clinical versus
administrative databases for CABG surgery: Does it matter? Med
Care 1992;30:892-907.
17. Pryor DB, Califf RM, Harrell FE, et al. Clinical data bases:
Accomplishments and unrealized potential. Med Care 1985;23:623-47.
18. Ghali WA, Knudtson ML for the APPROACH Investigators.
Overview of ‘APPROACH’ theAlberta provincial project for
outcome assessment in coronary heart disease. Can J Cardiol
2000;16:1225-30.
19. Optimizing disease management at a health care system level:
The rationale and methods of the improving cardiovascular outcomes
in Nova Scotia (ICONS) study. Can J Cardiol 1999;15:787-96.
20. Hennekens CH, Buring JE, eds. Epidemiology in Medicine. Toronto:
Little, Brown and Company, 1987.
21. Statistics Canada. The Canadian Community Health Survey (CCHS)
– Cycle 1.1. http://www.statcan.ca (January 8, 2003).
22. Béland Y, Bailie L, Catlin G, Singh MP. CCHS and NPHS:
An improved health survey program at Statistics Canada.
Proceedings of the section on survey research methods. Indianapolis:
American Statistical Association, 2000.
23. International Classification of Disease, 9th rev (Clinical
Modification). Washington: Public Health Service, USA
Department of Health and Human Services, 1988.
24. Canadian Classification of Diagnostic, Therapeutic, and Surgical
Procedures. Cat no 82-562E. Ottawa: Statistics Canada, 1986.
25. Changing Face of Heart Disease and Stroke in Canada 2000.
Ottawa: Heart and Stroke Foundation of Canada, 1999.
26. Health Canada. Cardiovascular Disease Surveillance On-Line,
Glossary. http://www.hc-sc.gc.ca (August 26, 2002).
27. Health Canada. Health Care. http://www.hc-sc.gc.ca (September 25,
2002).
28. Canadian Centre for Analysis of Regionalization and Health
(CCARH). What is regionalization?
http://www.regionalization.org/Index.html (December 14, 2002).
29. Statistics Canada. About Health Indicators. http://www.statcan.ca
(January 8, 2003).
30. Naylor CD, Slaughter PM, eds. Cardiovascular Health and Services
in Ontario. Toronto: Institute for Clinical Evaluative Sciences, 1999.
31. Dartmouth Medical School. Center for the Evaluative Clinical
Sciences. The Dartmouth Atlas of Cardiovascular Health Care.
Hanover: The Center for the Evaluative Clinical Science,
Dartmouth Medical College, 1999.
A Collection of Original Research Papers Published in The Canadian Journal of Cardiology