» Articles » PMID: 3081772

Severity of Illness Within DRGs. Homogeneity Study

Overview
Journal Med Care
Specialty Health Services
Date 1986 Mar 1
PMID 3081772
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

The authors assess the ability of the Severity of Illness Index to explain variability of resource use within each DRG. The data came from 15 hospitals, all of which had a HCFA DRG case mix index greater than 1. The data set comprised approximately 106,000 discharges, for which discharge abstract data, financial data, and Severity of Illness data were available. To pool the data over the 15 hospitals, the authors converted all charges to costs and normalized them to fiscal year 1983. Adjustments were also made for medical education and wage levels. The Severity of Illness Index explained more than 10% of the variability in resource use in 94% of the DRGs, which contained 97% of the patients, and more than 50% of the variability in resource use in 36% of the DRGs, which contained 24% of the patients. For the whole data set, DRGs explained 28% of the variability in resource use, and severity-adjusted DRGs explained 61% of the variability in resource use. Thus the Severity of Illness Index explained a large amount of the variability in resource use within individual DRGs as well as in the whole data set. This explanatory power remained when outliers were removed. These results go beyond previous studies that were based on six disease conditions and/or were analyzed only within individual hospitals. The findings indicate that the phenomenon of severity of illness differences within DRGs, and the corresponding differences in resource use, is consistent across 15 hospitals that represent all sections of the United States and all teaching types.

Citing Articles

Variations in the impact of the new case-based payment reform on medical costs, length of stay, and quality across different hospitals in China: an interrupted time series analysis.

Tang X, Zhang X, Chen Y, Yan J, Qian M, Ying X BMC Health Serv Res. 2023; 23(1):568.

PMID: 37264450 PMC: 10236872. DOI: 10.1186/s12913-023-09553-x.


Capturing patients' needs in casemix: a systematic literature review on the value of adding functioning information in reimbursement systems.

Hopfe M, Stucki G, Marshall R, Twomey C, Ustun T, Prodinger B BMC Health Serv Res. 2016; 16:40.

PMID: 26847062 PMC: 4741002. DOI: 10.1186/s12913-016-1277-x.


High cost factors for leukaemia and lymphoma patients: a new analysis of costs within these diagnosis related groups.

Quantin C, Entezam F, Lepage E, Guy H, DUSSERRE L J Epidemiol Community Health. 1999; 53(1):24-31.

PMID: 10326049 PMC: 1756772. DOI: 10.1136/jech.53.1.24.


Could distance be a proxy for severity-of-illness? A comparison of hospital costs in distant and local patients.

Welch H, Larson E, Welch W Health Serv Res. 1993; 28(4):441-58.

PMID: 8407337 PMC: 1069951.


Using a hospital information system to assess the effects of adverse drug events.

Evans R, Classen D, Stevens L, Pestotnik S, Gardner R, Lloyd J Proc Annu Symp Comput Appl Med Care. 1993; :161-5.

PMID: 8130454 PMC: 2248496.