The performance of marginal structural models for estimating risk differences and relative risks using weighted univariate generalized linear models
Austin PC. Stat Methods Med Res. 2024; Apr 24 [Epub ahead of print].
Background — Reporting of ischemic heart disease (IHD) prevalence in Canada has been based on self-report or patients presenting to hospital. However, IHD often presents and can be managed in the outpatient setting.
Objectives — To determine whether the combination of hospital data and physician billings could accurately identify patients with IHD.
Methods — A random sample of 969 adult patients from the Electronic Medical Record Administrative data Linked Database (EMRALD) – an electronic medical record database of primary care physicians in Ontario linked to administrative data for the province of Ontario – was used. A number of combinations of physician billing and hospital discharge abstracts were tested to determine the accuracy of using administrative data to identify IHD patients.
Results — Two physician billings within a one-year period (with one of the billings by a specialist or a family physician in a hospital or emergency room setting) or a hospital discharge abstract gave a sensitivity of 77.0% (95% CI 68.2% to 85.9%), a specificity of 98.0% (95% CI 97.0% to 98.9%), a positive predictive value of 78.8% (95% CI 70.1% to 87.5%), a negative predictive value of 97.7% (95% CI 96.8% to 98.7%) and a kappa of 0.76 (95% CI 0.68 to 0.83).
Conclusions — A combination of physician billing and hospital discharge abstracts can be used to identify patients with IHD. Population prevalence of IHD can be measured using administrative data.
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