Table 1 : Summary of previous research on methods to identify coronary heart disease cases from administrative data
Author |
Data Source
|
Diagnosis/Treatment Codes and Algorithms |
Study Cohort |
Validation Methodology |
Comments |
Rawson et al. (1995) |
Country: Canada
Source: Hospital discharge abstracts
Year: 1986
|
Codes: ICD-9 410 – 414
Algorithms: Hospital discharge data with a relevant diagnosis code in the primary or secondary discharge diagnosis field. |
Age of cohort was not specified.
|
Validation was performed with medical chart review for AMI only. Physician billing claims were used to validate AMI, angina, and chronic IHD.
Concordance between hospital discharge abstracts and medical chart review for AMI was 96.9%.
Concordance between hospital discharge abstracts and physician claims was 69.3% for AMI, 70.0% for angina, and 55.6% for chronic IHD when the primary diagnosis was used.
|
“When diagnostic agreement was broadened to include any physician diagnosis in the same ICD sub-chapter, the concordances all increased ranging from 79% to 94% in the IHD groups…” p.2639 |
Mahonen (1997) |
Country: Finland
Source: Finnish national hospital discharge register
Year: 1983-1990 |
Codes: ICD-9 410 – 414
Algorithm: Diagnosis of CHD in hospital discharge abstract |
Ages 25-65 years |
FINMONICA acute myocardial infarction register
Max. Sensitivity: 87.1% Max. PPV: 95.7% |
“There are no medical record abstractors in Finland ; clinicians taking care of the patients assign both the diagnoses and ICD codes for hospitalizations.” p.405 |
O’Connor (1998) |
Country: USA
Source: Clinic (i.e., physician) data
Year: 1992-1994
|
Codes: ICD-9 428.0 (congestive heart failure), 412 (history of myocardial infarction), 429.2 (arteriosclerotic cardiovascular disease), 413.9 (angina)
Algorithm: At least one visit with at least on of the codes in a defined 1-year period |
HMO members. Age is not specified |
Survey data. The question was: “Have you ever been told by a doctor that you had a heart attack?” When survey data and database data conflicted, a chart review was done.
Max. Sensitivity: 89% Max. Specificity: 99% Max. PPV: 85% |
|
Shah et al. (2000) |
Country: Canada
Source: CIHI hospital discharge abstracts for Ontario
Years: 1981-1997
|
ICD-9 410, 411, 413, 414. CCP codes for angioplasty and bypass: 48.0, 48.1
Algorithm: An event of heart disease was defined as a hospital discharge that has a selected ICD-9 code as one of the first two discharge diagnoses, or a selected CCP code as one of the first 2 procedures listed. |
Residents of Ontario communities that had regular census participation and at least 95% of their population claiming Native origins (N=16875 in 1991) |
No validation was conducted.
|
|
Pajunen et al. (2005) |
Country: Finland
Source: Finnish national hospital discharge register
Years: 1988 – 2002 |
ICD-9 410 (AMI) ICD-10 I21-I22 (AMI)
ICD-9 411.0 (unstable angina) ICD-10 I20.0 (unstable angina) – these were investigated in a secondary component of the analysis
Non-fatal events were identified where one of the selected codes was either the main diagnosis or an additional diagnosis. |
35 years of age and older. |
Validation was conducted using the myocardial infarction (MI) register.
For both fatal and non-fatal events: Max Sens = 85% Max PPV = 90%
For non-fatal events: Max Sens = 94% However, there were wide geographic variations in sensitivity, from 52% to 94%. |
|