Literature DB >> 8344821

Measuring differences and similarities in hospital caseloads: a conceptual and empirical analysis.

D A Dayhoff1, J Cromwell.   

Abstract

OBJECTIVE: This article conceptually and empirically evaluates alternative index measures that have been used to distinguish among hospital caseloads. It introduces two new measures. DATA SOURCES/STUDY
SETTING: The study relies on 1987 Medpar data, which provide a 100 percent sample of Medicare Part A claims for the calendar year. STUDY
DESIGN: Descriptive statistics indicate the sensitivity of alternative caseload measures to hospital bed size, region, and urban/rural location. Multiple regression analysis then examines the ability of the caseload measures to distinguish among hospitals based on hospital- and area-specific characteristics. DATA COLLECTION/EXTRACTION
METHODS: A provider level file containing the number of cases treated by each provider in each DRG was constructed from the Medpar data and merged with data from the American Hospital Association and the Area Resource File. PRINCIPAL
FINDINGS: Different indexes purporting to measure hospital specialization are often evaluating very different aspects of the hospitals' caseloads. Prior work has indicated a specialization among hospitals during the period from 1980 to 1985. Replication of this work using other indexes could verify the increase in specialization and might provide a clearer picture of market or hospital characteristics associated with changing caseloads.

Mesh:

Year:  1993        PMID: 8344821      PMCID: PMC1069937     

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  8 in total

1.  Case-mix specialization in the market for hospital services.

Authors:  D E Farley; C Hogan
Journal:  Health Serv Res       Date:  1990-12       Impact factor: 3.402

2.  Measuring casemix specialization and the concentration of diagnoses in hospitals using information theory.

Authors:  D E Farley
Journal:  J Health Econ       Date:  1989-06       Impact factor: 3.883

3.  Synthesis of albumin via a precursor protein in cell suspensions from rat liver.

Authors:  K Edwards; G Schreiber; H Dryburgh; J Urban; A S Inglis
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4.  The learning curve and the cost of heart transplantation.

Authors:  J R Woods; R M Saywell; A W Nyhuis; S J Jay; R G Lohrman; H G Halbrook
Journal:  Health Serv Res       Date:  1992-06       Impact factor: 3.402

5.  Does quality influence choice of hospital?

Authors:  H S Luft; D W Garnick; D H Mark; D J Peltzman; C S Phibbs; E Lichtenberg; S J McPhee
Journal:  JAMA       Date:  1990-06-06       Impact factor: 56.272

6.  The role of specialized clinical services in competition among hospitals.

Authors:  H S Luft; J C Robinson; D W Garnick; S C Maerki; S J McPhee
Journal:  Inquiry       Date:  1986       Impact factor: 1.730

7.  On grouping hospitals for economic analysis.

Authors:  R E Berry
Journal:  Inquiry       Date:  1973-12       Impact factor: 1.730

8.  Classification of community hospitals by scope of service: four indexes.

Authors:  M Edwards; J D Miller; R Schumacher
Journal:  Health Serv Res       Date:  1972       Impact factor: 3.402

  8 in total
  7 in total

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3.  Estimation of a physician practice cost function.

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Journal:  Eur J Health Econ       Date:  2016-05-19

4.  Quantifying effect of a hospital's caseload for a surgical specialty on that of another hospital using multi-attribute market segments.

Authors:  Franklin Dexter; Ruth E Wachtel; Min-Woong Sohn; Johannes Ledolter; Elisabeth U Dexter; Alex Macario
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5.  High cost factors for leukaemia and lymphoma patients: a new analysis of costs within these diagnosis related groups.

Authors:  C Quantin; F Entezam; P Brunet-Lecomte; E Lepage; H Guy; L Dusserre
Journal:  J Epidemiol Community Health       Date:  1999-01       Impact factor: 3.710

6.  Profit efficiency of physician practices: a stochastic frontier approach using panel data.

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Journal:  Health Care Manag Sci       Date:  2016-08-30

7.  The relationship between hospital specialization and hospital efficiency: do different measures of specialization lead to different results?

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  7 in total

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