BACKGROUND: Case definitions are essential to epidemiological research. OBJECTIVES: To evaluate ICD-9 codes 410 and 411 to identify cases of acute coronary syndromes (ACS), and the clinical information availability in the administrative and hospital discharge records of Saskatchewan, Canada. METHODS: In the context of a safety cohort study, we identified hospitalisations with primary discharge codes 410 (2260) and 411 (799). We selected all records with code 411, and a random sample (200) with code 410. Based on information obtained by trained abstractors from hospital records, events were classified by two cardiologists as definite or possible according to adapted AHA/ESC criteria. The validity of 410 and 411 codes was assessed by calculating the positive predictive value (PPV). Completeness of the recorded information on risk factors and use of aspirin was explored. RESULTS: The PPVs of the codes 410 and 411 for ACS were 0.96 (95%CI: 0. 92-0.98) and 0.86 (95%CI: 0.83-0.88), respectively. The PPV of 410 for acute myocardial infarction (AMI) was 0.95 (95%CI: 0.91-0.98). The PPV of 411 was 0.73 (95%CI: 0.70-0.77) for primary unstable angina (UA) and 0.09 (95%CI: 0.07-0.11) for AMI. Hospital charts review revealed key information for clinical variables, smoking, obesity and use of aspirin at admission. CONCLUSIONS: ICD-9 410 code has high PPV for AMI cases, likewise 411 for UA cases. Case validation remains important in epidemiological studies with administrative health databases. Given the pathophysiology of ACS, both AMI and UA might be used as study end points. In addition to code 410, we recommend the use of 411 plus validation
Positive predictive value of ICD-9 codes 410 and 411 in the identification of cases of acute coronary syndromes in the Saskatchewan Hospital automated database
Varas-Lorenzo, C., Castellsague, J., Stang, MR., Tomas, L., Aguado, J., & Perez-Gutthann, S. (2008). Positive predictive value of ICD-9 codes 410 and 411 in the identification of cases of acute coronary syndromes in the Saskatchewan Hospital automated database. Pharmacoepidemiology and Drug Safety, 17(8), 842-852.