Comparison of estimation methods for creating small area rates of acute myocardial infarction among Medicare beneficiaries in California. (September 2015)

• Record Type: Journal Article
• Authors: Yasaitis, Laura C.; Arcaya, Mariana C.; Subramanian, S.V.
• Is Part Of: Health & place. Volume 35(2015:Sep.)
• Page Start: 95
• Page End: 104
• Publication Date: 2015-09
• Subjects: Medicare -- Myocardial Infarction -- Spatial Analysis -- Local Disease Rates -- Markov Chains; Health -- Social aspects -- Periodicals; Health services accessibility -- Periodicals; Public health -- Periodicals; Political planning -- Periodicals; Social medicine -- Periodicals; Epidemiology -- Periodicals; Health Policy -- Periodicals; Health Services Accessibility -- Periodicals; Public Health -- Periodicals; Public Policy -- Periodicals; Sociology, Medical -- Periodicals; Épidémiologie -- Périodiques; Politique sanitaire -- Périodiques; Santé, Services de -- Accessibilité -- Périodiques; Health services accessibility; Health -- Social aspects; Political planning; Public health; Social medicine; Periodicals; 613
• DOI: 10.1016/j.healthplace.2015.08.003
• Languages: English
• ISSNs: 1353-8292

Abstract

Abstract: Creating local population health measures from administrative data would be useful for health policy and public health monitoring purposes. While a wide range of options – from simple spatial smoothers to model-based methods – for estimating such rates exists, there are relatively few side-by-side comparisons, especially not with real-world data. In this paper, we compare methods for creating local estimates of acute myocardial infarction rates from Medicare claims data. A Bayesian Monte Carlo Markov Chain estimator that incorporated spatial and local random effects performed best, followed by a method-of-moments spatial Empirical Bayes estimator. As the former is more complicated and time-consuming, spatial linear Empirical Bayes methods may represent a good alternative for non-specialist investigators. Highlights: We compared methods to estimate local rates of Acute Myocardial Infarction (AMI). ZCTA-level rates were examined among Medicare beneficiaries in California. Single-year estimates were compared to those created from five years' pooled data. Bayesian analyses accounting for spatial relationships performed best. Linear methods performed nearly as well as those implemented using MCMC estimation.