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Impact of early primary care follow-up after discharge on hospital readmissions

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Listed:
  • Damien Bricard

    () (Institut de Recherche et de Documentation en Economie de la Santé (IRDES))

  • Zeynep Or

    () (Institut de Recherche et de Documentation en Economie de la Santé (IRDES))

Abstract

Reducing repeated hospitalizations of patients with chronic conditions is a policy objective for improving system efficiency. We test the hypothesis that the risk of readmission is associated with the timing and intensity of primary care follow-up after discharge, focusing on patients hospitalized for heart failure in France. We propose a discrete-time model which takes into account that primary care treatments have a lagged and cumulative effect on readmission risk, and an instrumental variable approach, exploiting geographical differences in availability of generalists. We show that the early consultations with a GP after discharge can reduce the 28-day readmission risk by almost 50%, and that patients with higher ambulatory care utilization have smaller odds of readmission. Furthermore, geographical disparities in primary care affect indirectly the readmission risk. These results suggest that interventions which strengthen communication between hospitals and generalists are elemental for reducing readmissions and for developing effective strategies at the hospital level, it is also necessary to consider primary care resources that are available to patients.

Suggested Citation

  • Damien Bricard & Zeynep Or, 2019. "Impact of early primary care follow-up after discharge on hospital readmissions," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(4), pages 611-623, June.
  • Handle: RePEc:spr:eujhec:v:20:y:2019:i:4:d:10.1007_s10198-018-1022-y
    DOI: 10.1007/s10198-018-1022-y
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    References listed on IDEAS

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    More about this item

    Keywords

    Readmissions; Primary care; Hospital; Instrumental variable; Discrete-time model;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures

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