BACKGROUND: The validity of outcome report cards may depend on the ways in which they are adjusted for risk. OBJECTIVES: To compare the predictive ability of generic and disease-specific survival prediction models appropriate for use in patients with heart failure, to simulate outcome report cards by comparing survival across hospitals and adjusting for severity of illness using these models, and to assess the ways in which the results of these comparisons depend on the adjustment method. DESIGN: Analysis of data from a prospective cohort study. SETTING: A university hospital, a Veterans Affairs (VA) medical center, and a community hospital. PATIENTS: Sequential patients presenting in the emergency department with acute congestive heart failure. MEASUREMENTS: Unadjusted 30-day and 1-year mortality across hospitals and 30-day and 1-year mortality adjusted by using disease-specific survival prediction models (two sickness-at-admission models, the Cleveland Health Quality Choice model, the Congestive Heart Failure Mortality Time-Independent Predictive Instrument) and generic models (Acute Physiology and Chronic Health Evaluation [APACHE] II, APACHE III, the mortality prediction model, and the Chadson comorbidity index). RESULTS: The community hospital's unadjusted 30-day survival rate (85.0%) and the VA medical center's unadjusted 1-year survival rate (60.9%) were significantly lower than corresponding rates at the university hospital (92.7% and 67.5%, respectively). No severity model had excellent ability to discriminate patients by survival rates (all areas under the receiver-operating characteristic curve < 0.73). Whether the VA medical center, the community hospital, both, or neither had worse survival rates on simulated report cards than the university hospital depended on the prediction model used for adjustment. CONCLUSIONS: Results of simulated outcome report cards for survival in patients with congestive heart failure depend on the method used to adjust for severity.
BACKGROUND: The validity of outcome report cards may depend on the ways in which they are adjusted for risk. OBJECTIVES: To compare the predictive ability of generic and disease-specific survival prediction models appropriate for use in patients with heart failure, to simulate outcome report cards by comparing survival across hospitals and adjusting for severity of illness using these models, and to assess the ways in which the results of these comparisons depend on the adjustment method. DESIGN: Analysis of data from a prospective cohort study. SETTING: A university hospital, a Veterans Affairs (VA) medical center, and a community hospital. PATIENTS: Sequential patients presenting in the emergency department with acute congestive heart failure. MEASUREMENTS: Unadjusted 30-day and 1-year mortality across hospitals and 30-day and 1-year mortality adjusted by using disease-specific survival prediction models (two sickness-at-admission models, the Cleveland Health Quality Choice model, the Congestive Heart Failure Mortality Time-Independent Predictive Instrument) and generic models (Acute Physiology and Chronic Health Evaluation [APACHE] II, APACHE III, the mortality prediction model, and the Chadson comorbidity index). RESULTS: The community hospital's unadjusted 30-day survival rate (85.0%) and the VA medical center's unadjusted 1-year survival rate (60.9%) were significantly lower than corresponding rates at the university hospital (92.7% and 67.5%, respectively). No severity model had excellent ability to discriminate patients by survival rates (all areas under the receiver-operating characteristic curve < 0.73). Whether the VA medical center, the community hospital, both, or neither had worse survival rates on simulated report cards than the university hospital depended on the prediction model used for adjustment. CONCLUSIONS: Results of simulated outcome report cards for survival in patients with congestive heart failure depend on the method used to adjust for severity.
Authors: Montserrat Carmona; Luis M García-Olmos; Pilar García-Sagredo; Ángel Alberquilla; Fernando López-Rodríguez; Mario Pascual; Adolfo Muñoz; Carlos H Salvador; José L Monteagudo; Ángel Otero-Puime Journal: Fam Pract Date: 2013-06-17 Impact factor: 2.267