Eduard E Vasilevskis1, Michael W Kuzniewicz2, Brian A Cason3, Rondall K Lane4, Mitzi L Dean5, Ted Clay5, Deborah J Rennie5, Eric Vittinghoff6, R Adams Dudley7. 1. Philip R. Lee Institute for Health Policy Studies, University of California at San Francisco, San Francisco, CA; Division of General Internal Medicine, University of California at San Francisco, San Francisco, CA; Division of Hospital Medicine, University of California at San Francisco, San Francisco, CA; Department of Medicine (General Internal Medicine and Public Health) [Dr. Vasilevskis], Vanderbilt University, Nashville, TN; Geriatric Research Education and Clinical Care, Tennessee Valley Healthcare System, Nashville, TN; Clinical Research Training Center of Excellence, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN. Electronic address: eduard.vasilevskis@vanderbilt.edu. 2. Philip R. Lee Institute for Health Policy Studies, University of California at San Francisco, San Francisco, CA; Division of Neonatology, University of California at San Francisco, San Francisco, CA. 3. Department of Anesthesiology and Perioperative Medicine, University of California at San Francisco, San Francisco, CA; Veterans Affairs Medical Center, San Francisco, CA. 4. Philip R. Lee Institute for Health Policy Studies, University of California at San Francisco, San Francisco, CA; Department of Anesthesiology and Perioperative Medicine, University of California at San Francisco, San Francisco, CA. 5. Philip R. Lee Institute for Health Policy Studies, University of California at San Francisco, San Francisco, CA. 6. Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA. 7. Philip R. Lee Institute for Health Policy Studies, University of California at San Francisco, San Francisco, CA; Division of Pulmonary and Critical Care Medicine, University of California at San Francisco, San Francisco, CA.
Abstract
BACKGROUND: To develop and compare ICU length-of-stay (LOS) risk-adjustment models using three commonly used mortality or LOS prediction models. METHODS: Between 2001 and 2004, we performed a retrospective, observational study of 11,295 ICU patients from 35 hospitals in the California Intensive Care Outcomes Project. We compared the accuracy of the following three LOS models: a recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; and models developed using risk factors in the mortality probability model III at zero hours (MPM(0)) and the simplified acute physiology score (SAPS) II mortality prediction model. We evaluated models by calculating the following: (1) grouped coefficients of determination; (2) differences between observed and predicted LOS across subgroups; and (3) intraclass correlations of observed/expected LOS ratios between models. RESULTS: The grouped coefficients of determination were APACHE IV with coefficients recalibrated to the LOS values of the study cohort (APACHE IVrecal) [R(2) = 0.422], mortality probability model III at zero hours (MPM(0) III) [R(2) = 0.279], and simplified acute physiology score (SAPS II) [R(2) = 0.008]. For each decile of predicted ICU LOS, the mean predicted LOS vs the observed LOS was significantly different (p <or= 0.05) for three, two, and six deciles using APACHE IVrecal, MPM(0) III, and SAPS II, respectively. Plots of the predicted vs the observed LOS ratios of the hospitals revealed a threefold variation in LOS among hospitals with high model correlations. CONCLUSIONS: APACHE IV and MPM(0) III were more accurate than SAPS II for the prediction of ICU LOS. APACHE IV is the most accurate and best calibrated model. Although it is less accurate, MPM(0) III may be a reasonable option if the data collection burden or the treatment effect bias is a consideration.
BACKGROUND: To develop and compare ICU length-of-stay (LOS) risk-adjustment models using three commonly used mortality or LOS prediction models. METHODS: Between 2001 and 2004, we performed a retrospective, observational study of 11,295 ICU patients from 35 hospitals in the California Intensive Care Outcomes Project. We compared the accuracy of the following three LOS models: a recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; and models developed using risk factors in the mortality probability model III at zero hours (MPM(0)) and the simplified acute physiology score (SAPS) II mortality prediction model. We evaluated models by calculating the following: (1) grouped coefficients of determination; (2) differences between observed and predicted LOS across subgroups; and (3) intraclass correlations of observed/expected LOS ratios between models. RESULTS: The grouped coefficients of determination were APACHE IV with coefficients recalibrated to the LOS values of the study cohort (APACHE IVrecal) [R(2) = 0.422], mortality probability model III at zero hours (MPM(0) III) [R(2) = 0.279], and simplified acute physiology score (SAPS II) [R(2) = 0.008]. For each decile of predicted ICU LOS, the mean predicted LOS vs the observed LOS was significantly different (p <or= 0.05) for three, two, and six deciles using APACHE IVrecal, MPM(0) III, and SAPS II, respectively. Plots of the predicted vs the observed LOS ratios of the hospitals revealed a threefold variation in LOS among hospitals with high model correlations. CONCLUSIONS: APACHE IV and MPM(0) III were more accurate than SAPS II for the prediction of ICU LOS. APACHE IV is the most accurate and best calibrated model. Although it is less accurate, MPM(0) III may be a reasonable option if the data collection burden or the treatment effect bias is a consideration.
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