Validating Acute Myocardial Infarction Diagnoses in National Health Registers for Use as Endpoint in Research: The Tromsø Study

Clin Epidemiol. 2021 Aug 3:13:675-682. doi: 10.2147/CLEP.S321293. eCollection 2021.

Abstract

Purpose: To assess whether acute myocardial infarction (MI) diagnoses in national health registers are sufficiently correct and complete to replace manual collection of endpoint data for a population-based, epidemiological study.

Patients and methods: Using the Tromsø Study Cardiovascular Disease Register for 2013-2014 as gold standard, we calculated correctness (defined as positive predictive value (PPV)) and completeness (defined as sensitivity) of MI cases in the Norwegian Myocardial Infarction Register and the Norwegian Patient Register separately and in combination. We calculated the sensitivity and PPV with 95% confidence intervals using the Clopper-Pearson Exact test.

Results: We identified 153 MI cases in the gold standard. In the Norwegian Myocardial Infarction Register, we found a PPV of 97.1% (95% confidence interval (CI) 92.8-99.2) and a sensitivity of 88.2% (95% CI 82.0-92.9). In the Norwegian Patient Register, the PPV was 96.3% (95% CI 91.6-98.8) and the sensitivity was 85.6% (95% CI 79.0-90.8). The combined dataset of the Norwegian Myocardial Infarction Register and the Norwegian Patient Register had a PPV of 96.6% (95% CI 92.1-98.9) and a sensitivity of 91.5% (95% CI 85.9-95.4).

Conclusion: MI diagnoses in both the Norwegian Myocardial Infarction Register and the Norwegian Patient Register were highly correct and complete, and each of the registers could be considered as endpoint sources for the Tromsø Study. A combination of the two national registers seemed, however, to represent the most comprehensive data source overall. The benefits of using data from national registers as endpoints in epidemiological studies include faster, less resource-intensive access to nationwide data and considerably lower loss to follow-up, compared to manual data collection in a limited geographical area.

Keywords: cardiovascular diseases; data collection; data quality; quality control; registers.