Literature DB >> 15154689

An optimal contract approach to hospital financing.

Robin Boadway1, Maurice Marchand, Motohiro Sato.   

Abstract

Existing models of hospital financing advocate mixed schemes which include both lump-sum and cost-based payments. The doctor is generally the unique decision maker, which is unrealistic in a hospital setting where both managers and doctors are involved. This paper develops a model in which managers and doctors are responsible for different decisions within the hospital. In this model, public authorities who provide the financing, hospital managers who allocate resources within the hospital, and doctors who assign patients to either a low-tech or a high-tech therapy have information of increasing quality on the casemix of patients. The public authorities sign with hospital managers contracts specifying some lump-sum financing and some size of a high-tech equipment. In turn, managers, who know the broad mix of patients in the hospital, sign with hospital doctors contracts that specify the non-medical resources allocated to this facility as well as some remuneration. Doctors, who know each patient's illness severity, select the patients to be treated by the high-tech facility, and receive from public authorities some fee-for-service payment that is differentiated according to the low- or high-tech treatment used for curing their patients. What emerges is a two-stage agency problem in which contracts are designed to elicit information in the most efficient way.

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Year:  2004        PMID: 15154689     DOI: 10.1016/j.jhealeco.2003.08.001

Source DB:  PubMed          Journal:  J Health Econ        ISSN: 0167-6296            Impact factor:   3.883


  6 in total

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4.  Modeling and designing health care payment innovations for medical imaging.

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5.  Provider accountability as a driving force towards physician-hospital integration: a systematic review.

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6.  Buying efficiency: optimal hospital payment in the presence of double upcoding.

Authors:  Simon B Spika; Peter Zweifel
Journal:  Health Econ Rev       Date:  2019-12-28
  6 in total

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