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

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 i

SUBMITTER: Yasaitis LC 

PROVIDER: S-EPMC5072888 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature