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Validation of the hospital outcome prediction equation (HOPE) model for monitoring clinical performance
Authors:G J Duke  M Graco  J Santamaria  and F Shann
Institution:Critical Care Department, The Northern Hospital and;Northern Clinical Research Centre, Northern Health, Epping, and;Intensive Care Department, St Vincent's Hospital and;Intensive Care Unit, Royal Children's Hospital, Melbourne, Victoria, Australia
Abstract:Background: The aim of this study was to validate a risk-adjusted hospital outcome prediction equation (HOPE) using a statewide administrative dataset.
Methods: Retrospective observational study using multivariate logistic regression modelling. Calibration and discrimination were assessed by standardized mortality ratio (SMR), area under the receiver operating characteristic plot (ROC AUC), Hosmer–Lemeshow contingency tables and goodness-of-fit statistic in an independent dataset, and in all 23 important tertiary, metropolitan and regional hospitals. The dependent variable was in-hospital death. All consecutive adult hospital separations between 1 July 2004 and 30 June 2006, excluding obstetric and day-case only admissions, from all acute health services within the State of Victoria, Australia were included.
Results: A total of 379 676 consecutive records (1 July 2004 to 30 June 2005) was used to derive the HOPE model. Six variables (age, male sex, admission diagnosis, emergency admission, aged-care resident and inter-hospital transfer) were selected for inclusion in the final model. It was validated in the 384 489 consecutive records from the following year (1 July 2005 to 30 June 2006). The 95% confidence interval for the SMR was 0.98–1.02, and for the ROC AUC, 0.87–0.88. Discrimination and (one or more) calibration criteria were achieved in 22 (96%) of the 23 hospitals.
Conclusion: The HOPE model is a simple risk-adjusted outcome prediction tool, based on six variables from data that are routinely collected for administrative purposes and appears to be a reliable predictor of hospital outcome.
Keywords:clinical indicators  hospital performance  risk adjustment  health-care outcomes
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