Literature DB >> 3929632

Severity of illness within DRGs: impact on prospective payment.

S D Horn, P D Sharkey, A F Chambers, R A Horn.   

Abstract

This study compares the financial impact of a Diagnosis Related Group (DRG) prospective payment system with that of a Severity of Illness-adjusted DRG prospective payment system. The data base of about 106,000 discharges is from 15 hospitals, all of which had a Health Care Financing Administration (HCFA) DRG case mix index greater than 1. In order to pool the data over the 15 hospitals, all charges were converted to costs, normalized to Fiscal Year 1983, and adjusted for medical education and wage levels. The findings showed that, for the study population as a whole, DRGs explained 28 per cent of the variability in resource use per case while Severity of Illness-adjusted DRGs explained 61 per cent of the variability in resource use per case. When we simulated prospective payment systems based on DRGs and on Severity-adjusted DRGs, we found that the financial impact of the two systems differed by very little in some hospitals and by as much as 35 per cent of total operating costs in other hospitals. Thus, even with a data set that is relatively homogeneous (with respect to the HCFA DRG case mix index definition of hospitals), we found substantial inequities in payment when DRGs were not adjusted for Severity of Illness. These findings suggest that, with a more representative set of hospitals, the difference between unadjusted and Severity-adjusted DRG-based prospective payment could be greater than 35 per cent of a hospital's total operating costs.

Mesh:

Year:  1985        PMID: 3929632      PMCID: PMC1646367          DOI: 10.2105/ajph.75.10.1195

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  6 in total

1.  Does severity of illness make a difference in prospective payment?

Authors:  S D Horn
Journal:  Healthc Financ Manage       Date:  1983-05

2.  Measuring severity of illness: homogeneous case mix groups.

Authors:  S D Horn; P D Sharkey; D A Bertram
Journal:  Med Care       Date:  1983-01       Impact factor: 2.983

3.  An empiric study of ecological inference.

Authors:  M J Connor; D Gillings
Journal:  Am J Public Health       Date:  1984-06       Impact factor: 9.308

4.  Three case-type classifications: suitability for use in reimbursing hospitals.

Authors:  R P Ament; J L Dreachslin; E J Kobrinski; W R Wood
Journal:  Med Care       Date:  1982-05       Impact factor: 2.983

5.  Measuring severity of illness: comparisons across institutions.

Authors:  S D Horn
Journal:  Am J Public Health       Date:  1983-01       Impact factor: 9.308

6.  The Severity of Illness Index as a severity adjustment to diagnosis-related groups.

Authors:  S D Horn; R A Horn; P D Sharkey
Journal:  Health Care Financ Rev       Date:  1984
  6 in total
  10 in total

1.  The Computerized Severity Index. A new tool for case-mix management.

Authors:  S D Horn; R A Horn
Journal:  J Med Syst       Date:  1986-02       Impact factor: 4.460

2.  A method for analyzing inpatient care variability through physicians' orders.

Authors:  Matthew C Lenert; Randolph A Miller; Yevgeniy Vorobeychik; Colin G Walsh
Journal:  J Biomed Inform       Date:  2019-01-30       Impact factor: 6.317

3.  Relationship between severity, costs and claims of hospitalized patients using the Severity of Illness Index.

Authors:  M A Asenjo; L Baré; J M Bayas; A Prat; R Lledó; J Grau; L Salleras
Journal:  Eur J Epidemiol       Date:  1994-10       Impact factor: 8.082

4.  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

5.  Trauma case mix and hospital payment: the potential for refining DRGs.

Authors:  E J MacKenzie; D M Steinwachs; A I Ramzy; J W Ashworth; B Shankar
Journal:  Health Serv Res       Date:  1991-04       Impact factor: 3.402

6.  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

7.  The effect of resident involvement on community hospital charges.

Authors:  P M Dunn; D F Parker; W Levinson; J P Mullooly
Journal:  J Gen Intern Med       Date:  1989 Mar-Apr       Impact factor: 5.128

8.  Impact of Inpatient Harms on Hospital Finances and Patient Clinical Outcomes.

Authors:  Lee Adler; David Yi; Michael Li; Barry McBroom; Loran Hauck; Christine Sammer; Cason Jones; Terry Shaw; David Classen
Journal:  J Patient Saf       Date:  2018-06       Impact factor: 2.844

9.  Trend in healthcare-associated infections due to vancomycin-resistant Enterococcus at a hospital in the era of COVID-19: More than hand hygiene is needed.

Authors:  Mizuho Fukushige; Ling-Shang Syue; Kazuya Morikawa; Wen-Liang Lin; Nan-Yao Lee; Po-Lin Chen; Wen-Chien Ko
Journal:  J Microbiol Immunol Infect       Date:  2022-08-07       Impact factor: 10.273

10.  Policy issues related to prospective payment for pediatric hospitalization.

Authors:  S M Payne; J D Restuccia
Journal:  Health Care Financ Rev       Date:  1987
  10 in total

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