OBJECTIVE: To evaluate the amount of variation in in-hospital mortality and length of intensive care unit (ICU) stay that can be accounted for by clinical data available at ICU admission. DESIGN: Inception cohort study. SETTING: Forty-two ICUs in 40 hospitals, including 26 hospitals that were randomly selected and 14 large tertiary care hospitals that volunteered for the study. PARTICIPANTS: A consecutive sample of 16,622 patients and 17,440 ICU admissions. MEASUREMENTS AND MAIN OUTCOMES: Data on selected demographic characteristics, comorbidity, and specific physiologic variables were recorded during the first ICU day for an average of 415 admissions at each ICU; hospital discharge status (dead or alive) and length of ICU stay were recorded for individual patients; and the ratio of actual to predicted in-hospital mortality, standardized mortality ratios, and the ratio of actual to predicted length of ICU stay were recorded for individual ICUs. RESULTS: Unadjusted in-hospital mortality rates for the 42 units varied from 6.4% to 40%, and 90% (R2 = 0.90) of this variation was attributable to patient characteristics at admission. The standard mortality ratio varied from 0.67 to 1.25. The mean unadjusted length of ICU stay varied from 3.3 to 7.3 days, and 78% of the variation (R2 = 0.78) was attributed to patient and selected institutional characteristics. The best performing unit had a length of stay ratio of 0.88, whereas the poorest performing unit had a ratio of 1.21. CONCLUSIONS: Clinicians can use readily available admission data to adjust for considerable variations in patient severity and type in different ICUs. Such data should permit precise evaluation and comparison of ICU effectiveness and efficiency, which varied substantially in this study, and result in improved methods of risk prediction and evaluation of new medical practices.
OBJECTIVE: To evaluate the amount of variation in in-hospital mortality and length of intensive care unit (ICU) stay that can be accounted for by clinical data available at ICU admission. DESIGN: Inception cohort study. SETTING: Forty-two ICUs in 40 hospitals, including 26 hospitals that were randomly selected and 14 large tertiary care hospitals that volunteered for the study. PARTICIPANTS: A consecutive sample of 16,622 patients and 17,440 ICU admissions. MEASUREMENTS AND MAIN OUTCOMES: Data on selected demographic characteristics, comorbidity, and specific physiologic variables were recorded during the first ICU day for an average of 415 admissions at each ICU; hospital discharge status (dead or alive) and length of ICU stay were recorded for individual patients; and the ratio of actual to predicted in-hospital mortality, standardized mortality ratios, and the ratio of actual to predicted length of ICU stay were recorded for individual ICUs. RESULTS: Unadjusted in-hospital mortality rates for the 42 units varied from 6.4% to 40%, and 90% (R2 = 0.90) of this variation was attributable to patient characteristics at admission. The standard mortality ratio varied from 0.67 to 1.25. The mean unadjusted length of ICU stay varied from 3.3 to 7.3 days, and 78% of the variation (R2 = 0.78) was attributed to patient and selected institutional characteristics. The best performing unit had a length of stay ratio of 0.88, whereas the poorest performing unit had a ratio of 1.21. CONCLUSIONS: Clinicians can use readily available admission data to adjust for considerable variations in patient severity and type in different ICUs. Such data should permit precise evaluation and comparison of ICU effectiveness and efficiency, which varied substantially in this study, and result in improved methods of risk prediction and evaluation of new medical practices.
Authors: Jennifer L Perri; Brian W Nolan; Philip P Goodney; Randall R DeMartino; Benjamin S Brooke; Shipra Arya; Mark F Conrad; Jack L Cronenwett Journal: J Vasc Surg Date: 2017-07-14 Impact factor: 4.268
Authors: C A Zauner; R C Apsner; A Kranz; L Kramer; C Madl; B Schneider; B Schneeweiss; K Ratheiser; F Stockenhuber; K Lenz Journal: Intensive Care Med Date: 1996-06 Impact factor: 17.440