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Use of the Medicare database in epidemiologic and health services research: a valuable source of real-world evidence on the older and disabled populations in the US.

Authors :
Mues, Katherine E.
Liede, Alexander
Jiannong Liu
Wetmore, James B.
Zaha, Rebecca
Bradbury, Brian D.
Collins, Allan J.
Gilbertson, David T.
Source :
Clinical Epidemiology; May2017, Vol. 9, p267-277, 11p
Publication Year :
2017

Abstract

Medicare is the federal health insurance program for individuals in the US who are aged ≥65 years, select individuals with disabilities aged <65 years, and individuals with endstage renal disease. The Centers for Medicare and Medicaid Services grants researchers access to Medicare administrative claims databases for epidemiologic and health outcomes research. The data cover beneficiaries' encounters with the health care system and receipt of therapeutic interventions, including medications, procedures, and services. Medicare data have been used to describe patterns of morbidity and mortality, describe burden of disease, compare effectiveness of pharmacologic therapies, examine cost of care, evaluate the effects of provider practices on the delivery of care and patient outcomes, and explore the health impacts of important Medicare policy changes. Considering that the vast majority of US citizens ≥65 years of age have Medicare insurance, analyses of Medicare data are now essential for understanding the provision of health care among older individuals in the US and are critical for providing realworld evidence to guide decision makers. This review is designed to provide researchers with a summary of Medicare data, including the types of data that are captured, and how they may be used in epidemiologic and health outcomes research. We highlight strengths, limitations, and key considerations when designing a study using Medicare data. Additionally, we illustrate the potential impact that Centers for Medicare and Medicaid Services policy changes may have on data collection, coding, and ultimately on findings derived from the data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11791349
Volume :
9
Database :
Complementary Index
Journal :
Clinical Epidemiology
Publication Type :
Academic Journal
Accession number :
123494425
Full Text :
https://doi.org/10.2147/CLEP.S105613