Literature DB >> 26443420

Optimal use of available claims to identify a Medicare population free of coronary heart disease.

Shia T Kent, Monika M Safford, Hong Zhao, Emily B Levitan, Jeffrey R Curtis, Ryan D Kilpatrick, Meredith L Kilgore, Paul Muntner.   

Abstract

We examined claims-based approaches for identifying a study population free of coronary heart disease (CHD) using data from 8,937 US blacks and whites enrolled during 2003-2007 in a prospective cohort study linked to Medicare claims. Our goal was to minimize the percentage of persons at study entry with self-reported CHD (previous myocardial infarction or coronary revascularization). We assembled 6 cohorts without CHD claims by requiring 6 months, 1 year, or 2 years of continuous Medicare fee-for-service insurance coverage prior to study entry and using either a fixed-window or all-available look-back period. We examined adding CHD-related claims to our "base algorithm," which included claims for myocardial infarction and coronary revascularization. Using a 6-month fixed-window look-back period, 17.8% of participants without claims in the base algorithm reported having CHD. This was reduced to 3.6% using an all-available look-back period and adding other CHD claims to the base algorithm. Among cohorts using all-available look-back periods, increasing the length of continuous coverage from 6 months to 1 or 2 years reduced the sample size available without lowering the percentage of persons with self-reported CHD. This analysis demonstrates approaches for developing a CHD-free cohort using Medicare claims.
© The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Medicare; algorithms; bias (epidemiology); coronary disease; epidemiologic methods

Mesh:

Year:  2015        PMID: 26443420      PMCID: PMC4617296          DOI: 10.1093/aje/kwv116

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


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