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Geographic variation in the delivery of high-value inpatient care

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  • John Romley
  • Erin Trish
  • Dana Goldman
  • Melinda Beeuwkes Buntin
  • Yulei He
  • Paul Ginsburg

Abstract

Objectives: To measure value in the delivery of inpatient care and to quantify its variation across U.S. regions. Data sources / Study setting: A random (20%) sample of 33,713 elderly fee-for-service Medicare beneficiaries treated in 2,232 hospitals for a heart attack in 2013. Study design: We estimate a production function for inpatient care, defining output as stays with favorable patient outcomes in terms of survival and readmission. The regression model includes hospital inputs measured by treatment costs, as well as patient characteristics. Region-level effects in the production function are used to estimate the productivity and value of the care delivered by hospitals within regions. Data collection / Extraction methods: Medicare claims and enrollment files, linked to the Dartmouth Atlas of Health Care and Inpatient Prospective Payment System Impact Files. Principal findings: Hospitals in the hospital referral region at the 90th percentile of the value distribution delivered 54% more high-quality stays than hospitals at the 10th percentile could have delivered, after adjusting for treatment costs and patient severity. Conclusions: Variation in the delivery of high-value inpatient care points to opportunities for better quality and lower costs.

Suggested Citation

  • John Romley & Erin Trish & Dana Goldman & Melinda Beeuwkes Buntin & Yulei He & Paul Ginsburg, 2019. "Geographic variation in the delivery of high-value inpatient care," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-11, March.
  • Handle: RePEc:plo:pone00:0213647
    DOI: 10.1371/journal.pone.0213647
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    References listed on IDEAS

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    Cited by:

    1. John A. Romley & Dana Goldman & Neeraj Sood & Abe C. Dunn, 2019. "Quantifying Productivity Growth in the Delivery of Important Episodes of Care Within the Medicare Program Using Insurance Claims and Administrative Data," BEA Papers 0111, Bureau of Economic Analysis.

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