Literature DB >> 3139848

Looking at the patient in the mix: is case mix methodology unfair to the hospital outpatient department?

O Fein1, S Hoffman, E Barzel.   

Abstract

The diagnoses of 431 general internal medicine patients from an urban outpatient department (OPD) were analyzed using two methods of case mix description: 1) a visit-based method which captures a single diagnosis for each visit; 2) a patient-based method which captures multiple diagnoses for a patient over one year. Nine of the top ten diagnoses were the same using either method, but the prevalence of diagnoses was two- to twelvefold higher with the patient-based method. Next the OPD was compared by the visit-based method with a national survey of doctors' private offices. Although the visit-based case mix in the OPD appeared to be the same as that in doctors' private offices, the analysis suggested that differences may be hidden by the method of describing case mix. The authors conclude that a visit-based approach to case mix description makes urban OPDs resemble doctors' private offices because the visit-based method undercounts those patients with chronic diagnoses, co-morbid conditions, and psychosocial problems, so common in the urban OPD. These findings have major implications for ambulatory reimbursement schemes, most of which capture only one diagnosis for each visit.

Entities:  

Mesh:

Year:  1988        PMID: 3139848     DOI: 10.1007/bf02595924

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  16 in total

1.  Health care episodes: definition, measurement and use.

Authors:  M C Hornbrook; A V Hurtado; R E Johnson
Journal:  Med Care Rev       Date:  1985

2.  Ambulatory visit groups: implications for hospital outpatient departments.

Authors:  J Lion; A Malbon; A Bergman
Journal:  J Ambul Care Manage       Date:  1987-02

3.  Ambulatory care classification systems.

Authors:  D H Stimson; G Charles; C L Rogerson
Journal:  Health Serv Res       Date:  1986-02       Impact factor: 3.402

4.  Classification of ambulatory care using patient-based, time-oriented indexes.

Authors:  C L Rogerson; D H Stimson; D W Simborg; G Charles
Journal:  Med Care       Date:  1985-06       Impact factor: 2.983

Review 5.  Analytical potential for multiple cause-of-death data.

Authors:  R A Israel; H M Rosenberg; L R Curtin
Journal:  Am J Epidemiol       Date:  1986-08       Impact factor: 4.897

6.  Common sense on extending DRG concepts to pay for ambulatory care.

Authors:  M Gold
Journal:  Inquiry       Date:  1988       Impact factor: 1.730

7.  The effect of including secondary diagnoses on the description of the diagnostic content of family practice.

Authors:  R Schneeweiss; D C Cherkin; G L Hart
Journal:  Med Care       Date:  1984-11       Impact factor: 2.983

8.  Ambulatory visit groups: a framework for measuring productivity in ambulatory care.

Authors:  R B Fetter; R F Averill; J L Lichtenstein; J L Freeman
Journal:  Health Serv Res       Date:  1984-10       Impact factor: 3.402

9.  A method for analyzing resource use in ambulatory care settings.

Authors:  I Moscovice
Journal:  Med Care       Date:  1977-12       Impact factor: 2.983

10.  The content of ambulatory medical care in the United States. An interspecialty comparison.

Authors:  R A Rosenblatt; D C Cherkin; R Schneeweiss; L G Hart
Journal:  N Engl J Med       Date:  1983-10-13       Impact factor: 91.245

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  3 in total

1.  Restructuring ambulatory services in the academic medical center: one approach to primary care services for the urban poor.

Authors:  O Fein
Journal:  Bull N Y Acad Med       Date:  1991 Jan-Feb

Review 2.  Ambulatory care casemix measures.

Authors:  D R Berlowitz; A K Rosen; M A Moskowitz
Journal:  J Gen Intern Med       Date:  1995-03       Impact factor: 5.128

3.  A patient-based system for describing ambulatory medicine practices using diagnosis clusters.

Authors:  B C Williams; J T Philbrick; D M Becker; A McDermott; R C Davis; P C Buncher
Journal:  J Gen Intern Med       Date:  1991 Jan-Feb       Impact factor: 5.128

  3 in total

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