Unknown

Dataset Information

0

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 investigators.

SUBMITTER: Yasaitis LC 

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

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Yasaitis Laura C LC   Arcaya Mariana C MC   Subramanian S V SV  

Health & place 20150915


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 Mar  ...[more]

Similar Datasets

| S-EPMC6990949 | biostudies-literature
| S-EPMC5815081 | biostudies-other
| S-EPMC5922453 | biostudies-literature
| S-EPMC4415510 | biostudies-literature
| S-EPMC3142883 | biostudies-literature
| S-EPMC6015328 | biostudies-literature
| S-EPMC5097252 | biostudies-literature
| S-EPMC5867101 | biostudies-literature
| S-EPMC7327397 | biostudies-literature
| S-EPMC4836735 | biostudies-literature