Explaining variability of cost using a severity-of-illness measure for ICU patients

• Published in: Medical care Vol. 28; no. 4; p. 338
• Main Authors: Rapoport, J, Teres, D, Lemeshow, S, Avrunin, J S, Haber, R
• Format: Journal Article
• Language: English
• Published: United States 01.04.1990
• Subjects: Costs and Cost Analysis - statistics & numerical data; Hospital Bed Capacity, 500 and over; Humans; Intensive Care Units - economics; Intensive Care Units - statistics & numerical data; Length of Stay - statistics & numerical data; Massachusetts; Models, Statistical; Mortality; Outcome and Process Assessment (Health Care) - methods; Probability; Severity of Illness Index
• DOI: 10.1097/00005650-199004000-00005
• ISSN: 0025-7079

Factors related to hospital resource use by intensive care unit (ICU) patients, including severity of illness at admission and intensity of therapy during the first 24 ICU hours were explored in this study. Analysis was based on 2,749 patients admitted to the general medical-surgical ICU at Baystate Medical Center, Springfield, Massachusetts, between February 1, 1983 and January 10, 1985. Resource use was indexed by hospital length of stay (LOS) adjusted for differences between ICU and other hospital days. Severity of illness was measured by the Mortality Prediction Model (MPM0), a validated predictor of outcome but not previously used to analyze resource consumption. Intensity of therapy was measured using the Therapeutic Intervention Scoring System (TISS). The 10% of patients with longest ICU stays were significantly different from the other 90% with respect to previous ICU use, MPM probability, and TISS score. Variability in resource use was analyzed using four diagnosis-related groups (DRGs) accounting for large numbers of ICU patients. The relationship between severity of illness and resource was nonlinear: as severity increased from low levels, resource use increased at a decreasing rate, reached a plateau, and eventually declined. Within each DRG, MPM0 explained a statistically significant percentage of the variability in resource use.