Literature DB >> 14686628

Random output and hospital performance.

Pedro Pita Barros1.   

Abstract

Many countries are under pressure to reform health care financing and delivery. Hospital care is one part of the health system that is under scrutiny. Private management initiatives are a possible way to increase efficiency in health care delivery. This motivates the interest in developing methodologies to assess hospital performance, recognizing hospitals as a different sort of firm. We present a simple way to describe hospital production: hospital output as a change in the distribution of survival probabilities. This output definition allows us to separate hospital production from patients' characteristics. The notion of "better performance" has a precise meaning: (first-order) stochastic dominance of a distribution of survival probabilities over another distribution. As an illustration, we compare, for an important DRG, private and public management and find that private management performs better, mainly in the range of high-survival probabilities. The measured performance difference cannot be attributed to input prices or to economies of scale and/or scope. It reflects pure technological and organisational differences.

Entities:  

Mesh:

Year:  2003        PMID: 14686628     DOI: 10.1023/a:1026277507298

Source DB:  PubMed          Journal:  Health Care Manag Sci        ISSN: 1386-9620


  10 in total

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Authors:  D M Cutler; M McClellan; J P Newhouse
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4.  Measuring hospital efficiency with frontier cost functions.

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Journal:  J Health Econ       Date:  1994-10       Impact factor: 3.883

5.  Measuring hospital performance. A non-parametric approach.

Authors:  S Grosskopf; V Valdmanis
Journal:  J Health Econ       Date:  1987-06       Impact factor: 3.883

6.  Measuring hospital cost efficiency with panel data models.

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7.  Adjusting cesarean delivery rates for case mix.

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Journal:  Health Serv Res       Date:  1997-10       Impact factor: 3.402

8.  Managing care, incentives, and information: an exploratory look inside the "black box" of hospital efficiency.

Authors:  D Conrad; T Wickizer; C Maynard; T Klastorin; D Lessler; A Ross; N Soderstrom; S Sullivan; J Alexander; K Travis
Journal:  Health Serv Res       Date:  1996-08       Impact factor: 3.402

9.  Sex-based differences in early mortality after myocardial infarction. National Registry of Myocardial Infarction 2 Participants.

Authors:  V Vaccarino; L Parsons; N R Every; H V Barron; H M Krumholz
Journal:  N Engl J Med       Date:  1999-07-22       Impact factor: 91.245

10.  Does more intensive treatment of acute myocardial infarction in the elderly reduce mortality? Analysis using instrumental variables.

Authors:  M McClellan; B J McNeil; J P Newhouse
Journal:  JAMA       Date:  1994-09-21       Impact factor: 56.272

  10 in total
  2 in total

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2.  Performance evaluation of inpatient service in Beijing: a horizontal comparison with risk adjustment based on Diagnosis Related Groups.

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  2 in total

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