OBJECTIVE: Intensive care units (ICUs) use severity-adjusted mortality measures such as the standardized mortality ratio to benchmark their performance. Prognostic scoring systems such as Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 permit performance-based comparisons of ICUs by adjusting for severity of disease and case mix. Whether different risk-adjustment methods agree on the identity of ICU quality outliers within a single database has not been previously investigated. The objective of this study was to determine whether the identity of ICU quality outliers depends on the ICU scoring system used to calculate the standardized mortality ratio. DESIGN, SETTING, PATIENTS: Retrospective cohort study of 16,604 patients from 32 hospitals based on the outcomes database (Project IMPACT) created by the Society of Critical Care Medicine. The ICUs were a mixture of medical, surgical, and mixed medical-surgical ICUs in urban and nonurban settings. Standardized mortality ratios for each ICU were calculated using APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II. ICU quality outliers were defined as ICUs whose standardized mortality ratio was statistically different from 1. Kappa analysis was used to determine the extent of agreement between the scoring systems on the identity of hospital quality outliers. The intraclass correlation coefficient was calculated to estimate the reliability of standardized mortality ratios obtained using the three risk-adjustment methods. MEASUREMENTS AND MAIN RESULTS: Kappa analysis showed fair to moderate agreement among the three scoring systems in identifying ICU quality outliers; the intraclass correlation coefficient suggested moderate to substantial agreement between the scoring systems. The majority of ICUs were classified as high-performance ICUs by all three scoring systems. All three scoring systems exhibited good discrimination and poor calibration in this data set. CONCLUSION: APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 exhibit fair to moderate agreement in identifying quality outliers. However, the finding that most ICUs in this database were judged to be high-performing units limits the usefulness of these models in their present form for benchmarking.
OBJECTIVE: Intensive care units (ICUs) use severity-adjusted mortality measures such as the standardized mortality ratio to benchmark their performance. Prognostic scoring systems such as Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 permit performance-based comparisons of ICUs by adjusting for severity of disease and case mix. Whether different risk-adjustment methods agree on the identity of ICU quality outliers within a single database has not been previously investigated. The objective of this study was to determine whether the identity of ICU quality outliers depends on the ICU scoring system used to calculate the standardized mortality ratio. DESIGN, SETTING, PATIENTS: Retrospective cohort study of 16,604 patients from 32 hospitals based on the outcomes database (Project IMPACT) created by the Society of Critical Care Medicine. The ICUs were a mixture of medical, surgical, and mixed medical-surgical ICUs in urban and nonurban settings. Standardized mortality ratios for each ICU were calculated using APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II. ICU quality outliers were defined as ICUs whose standardized mortality ratio was statistically different from 1. Kappa analysis was used to determine the extent of agreement between the scoring systems on the identity of hospital quality outliers. The intraclass correlation coefficient was calculated to estimate the reliability of standardized mortality ratios obtained using the three risk-adjustment methods. MEASUREMENTS AND MAIN RESULTS: Kappa analysis showed fair to moderate agreement among the three scoring systems in identifying ICU quality outliers; the intraclass correlation coefficient suggested moderate to substantial agreement between the scoring systems. The majority of ICUs were classified as high-performance ICUs by all three scoring systems. All three scoring systems exhibited good discrimination and poor calibration in this data set. CONCLUSION: APACHE II, Simplified Acute Physiology Score II, and Mortality Probability Model II0 exhibit fair to moderate agreement in identifying quality outliers. However, the finding that most ICUs in this database were judged to be high-performing units limits the usefulness of these models in their present form for benchmarking.
Authors: Dana B Mukamel; Laurent G Glance; Yue Li; David L Weimer; William D Spector; Jacqueline S Zinn; Laura Mosqueda Journal: Med Care Date: 2008-05 Impact factor: 2.983
Authors: Rebeccah M Brusca; Catherine E Simpson; Sarina K Sahetya; Zeba Noorain; Varshitha Tanykonda; R Scott Stephens; Dale M Needham; David N Hager Journal: J Intensive Care Med Date: 2019-10-21 Impact factor: 3.510