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Using Medicare claims for outcomes research

J B Mitchell1, T Bubolz, J E Paul

  • 1Health Economics Research, Inc., Waltham, MA 02154.

Medical Care
|July 1, 1994
PubMed
Summary
This summary is machine-generated.

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Medicare claims databases offer advantages for outcomes research, but require careful handling. This study details methods for using these large datasets to define patient cohorts, episode lengths, and measure outcomes effectively.

Area of Science:

  • Health Services Research
  • Biostatistics
  • Epidemiology

Background:

  • Medicare claims databases are valuable for outcomes research due to their population-based nature, cost-effectiveness, large case numbers, and long-term follow-up capabilities.
  • The administrative, rather than clinical, focus and large size of these databases necessitate specialized approaches for accurate research.
  • Ten Programs of Research on the Treatment of Stroke (PORTs) utilized Medicare claims data for outcomes research.

Purpose of the Study:

  • To report the experiences and knowledge gained by ten PORTs in utilizing Medicare claims data for constructing and analyzing episodes of care.
  • To address key methodological challenges in using Medicare claims for outcomes research.

Main Methods:

  • Identifying index cases or patient cohorts for study within Medicare claims data.

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  • Defining the temporal boundaries (length) of an episode of care.
  • Selecting and measuring appropriate outcomes using claims data.

    • Main Results:

    • The paper details the specific strategies and considerations employed by the PORTs for each of the key issues: case identification, episode definition, and outcome measurement.
    • Insights into the practical application and challenges of using Medicare claims for episode-of-care analysis are provided.

    Conclusions:

    • Careful methodological approaches are crucial for effectively leveraging Medicare claims databases in outcomes research.
    • The experiences shared by the PORTs offer valuable guidance for researchers working with large administrative healthcare datasets to construct and analyze episodes of care.