Literature DB >> 6808259

The measurement of hospital case mix.

W W Young, R B Swinkola, D M Zorn.   

Abstract

This paper describes the design and preliminary results of research being conducted by Blue Cross of Western Pennsylvania to measure hospital case mix. The model of patient management used in this research interrelates symptoms, diagnosis and treatment. Analyses of detailed patient data have indicated that patient classifications that are based on discharge diagnosis, singly or in combination with other variables such as secondary or multiple diagnoses, procedure and age, do not necessarily result in patient categories that require similar management or similar hospital services. Patients who are clinically similar, and even the same patient, can have a number of diverse, but appropriate, reasons for being in the hospital, and their use of hospital resources in each hospital episode will differ accordingly. The implications of including all reasons for hospitalizing these patients under the same rubric are clear: the resultant category would not be homogeneous with respect to resource use or hospital costs. Any case-mix index constructed using such categories as its basis could not only be misleading, but could also be financially damaging or extremely profitable to selected hospitals if used in hospital reimbursement. Both the model presented and preliminary analysis will be useful in designing other strategies for research and application in the area of case mix.

Entities:  

Mesh:

Year:  1982        PMID: 6808259     DOI: 10.1097/00005650-198205000-00006

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  18 in total

Review 1.  Case mix planning in hospitals: a review and future agenda.

Authors:  Sebastian Hof; Andreas Fügener; Jan Schoenfelder; Jens O Brunner
Journal:  Health Care Manag Sci       Date:  2015-09-19

2.  Measuring outcomes of hospital care using multiple risk-adjusted indexes.

Authors:  S DesHarnais; L F McMahon; R Wroblewski
Journal:  Health Serv Res       Date:  1991-10       Impact factor: 3.402

Review 3.  How severity measures rate hospitalized patients.

Authors:  J S Hughes; L I Iezzoni; J Daley; L Greenberg
Journal:  J Gen Intern Med       Date:  1996-05       Impact factor: 5.128

4.  A method for constructing case-mix indexes, with application to hospital length of stay.

Authors:  R H Shachtman; S M Snapinn; D Quade; D A Freund; A K Kronhaus
Journal:  Health Serv Res       Date:  1986-02       Impact factor: 3.402

Review 5.  Measurement of severity of illness and the Medicare prospective payment system: state of the art and future directions.

Authors:  L F McMahon; J E Billi
Journal:  J Gen Intern Med       Date:  1988 Sep-Oct       Impact factor: 5.128

6.  Do severity measures explain differences in length of hospital stay? The case of hip fracture.

Authors:  M Shwartz; L I Iezzoni; A S Ash; Y D Mackiernan
Journal:  Health Serv Res       Date:  1996-10       Impact factor: 3.402

7.  Comparison of a disease-specific and a generic severity of illness measure for patients with community-acquired pneumonia.

Authors:  M J Fine; B H Hanusa; J R Lave; D E Singer; R A Stone; L A Weissfeld; C M Coley; T J Marrie; W N Kapoor
Journal:  J Gen Intern Med       Date:  1995-07       Impact factor: 5.128

8.  Access to hospitals with high-technology cardiac services: how is race important?

Authors:  J Blustein; B C Weitzman
Journal:  Am J Public Health       Date:  1995-03       Impact factor: 9.308

9.  DRGs and severity of illness measures: an analysis of patient classification systems.

Authors:  M D Rosko
Journal:  J Med Syst       Date:  1988-08       Impact factor: 4.460

10.  Case-mix adjustment using objective measures of severity: the case for laboratory data.

Authors:  B Mozes; M J Easterling; L B Sheiner; K L Melmon; R Kline; E S Goldman; A N Brown
Journal:  Health Serv Res       Date:  1994-02       Impact factor: 3.402

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.