OBJECTIVES: To present an approach for assessing intensive care unit (ICU) performance which takes into account both economic and clinical performance while adjusting for severity of illness. To present a graphic display which permits comparisons among a group of hospitals. DESIGN: A multicenter, inception cohort study. SETTING: Twenty-five ICUs in U.S. hospitals that participated in the European and North American Study of Severity Systems for ICU Patients. PATIENTS: Consecutive patients (n = 3,397) admitted to ICUs in participating hospitals between September 30, 1991 and December 27, 1991. Excluded were coronary care patients, burn patients, cardiac surgery patients and patients aged < 18 yrs. MEASUREMENTS AND MAIN RESULTS: The clinical performance index is the difference between observed hospital survival rate and survival rate predicted by the Mortality Probability Model measuring severity of illness at ICU admission. The economic performance (resource use) measure is a length of stay index, Weighted Hospital Days, which weights ICU days more heavily than non-ICU days. The economic performance index is the difference between actual mean resource use and the resource use predicted by a regression including severity of illness and percent of surgical patients. Both the clinical and economic performance indices are standardized to show how far a particular hospital is from the overall mean and are graphed together. Most of the 25 hospitals lie within 1 SD of the mean on both clinical and economic performance scales. The graph makes it easy to identify those hospitals that are outside this range. There is no evidence of a trade-off between high clinical performance and high economic performance; i.e., it is possible to achieve both. CONCLUSIONS: Cross-indexing of clinical and economic ICU performance is easy to calculate. It has potential as a research and evaluation tool used by physicians, hospital administrators, payers, and others.
OBJECTIVES: To present an approach for assessing intensive care unit (ICU) performance which takes into account both economic and clinical performance while adjusting for severity of illness. To present a graphic display which permits comparisons among a group of hospitals. DESIGN: A multicenter, inception cohort study. SETTING: Twenty-five ICUs in U.S. hospitals that participated in the European and North American Study of Severity Systems for ICU Patients. PATIENTS: Consecutive patients (n = 3,397) admitted to ICUs in participating hospitals between September 30, 1991 and December 27, 1991. Excluded were coronary care patients, burn patients, cardiac surgery patients and patients aged < 18 yrs. MEASUREMENTS AND MAIN RESULTS: The clinical performance index is the difference between observed hospital survival rate and survival rate predicted by the Mortality Probability Model measuring severity of illness at ICU admission. The economic performance (resource use) measure is a length of stay index, Weighted Hospital Days, which weights ICU days more heavily than non-ICU days. The economic performance index is the difference between actual mean resource use and the resource use predicted by a regression including severity of illness and percent of surgical patients. Both the clinical and economic performance indices are standardized to show how far a particular hospital is from the overall mean and are graphed together. Most of the 25 hospitals lie within 1 SD of the mean on both clinical and economic performance scales. The graph makes it easy to identify those hospitals that are outside this range. There is no evidence of a trade-off between high clinical performance and high economic performance; i.e., it is possible to achieve both. CONCLUSIONS: Cross-indexing of clinical and economic ICU performance is easy to calculate. It has potential as a research and evaluation tool used by physicians, hospital administrators, payers, and others.
Authors: J Randall Curtis; Paul S Ciechanowski; Lois Downey; Julia Gold; Elizabeth L Nielsen; Sarah E Shannon; Patsy D Treece; Jessica P Young; Ruth A Engelberg Journal: Contemp Clin Trials Date: 2012-07-06 Impact factor: 2.226
Authors: Eduard E Vasilevskis; Michael W Kuzniewicz; Brian A Cason; Rondall K Lane; Mitzi L Dean; Ted Clay; Deborah J Rennie; Eric Vittinghoff; R Adams Dudley Journal: Chest Date: 2009-04-10 Impact factor: 9.410