Automated intensive care unit risk adjustment: results from a National Veterans Affairs study
| Autor: | Marta L. Render, Deborah E. Welsh, Joseph A. Johnston, Timothy P. Hofer, Stephen Timmons, Alfred F. Connors, Siu Hui, Jennifer Daley, Douglas P. Wagner, H. Myra Kim |
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| Rok vydání: | 2003 |
| Předmět: |
Adult
Male medicine.medical_specialty Hospitals Veterans Critical Care and Intensive Care Medicine Risk Assessment Severity of Illness Index law.invention Automation law Chart review Intensive care Severity of illness Medicine Humans Hospital Mortality Intensive care medicine Veterans Affairs Aged Aged 80 and over business.industry Reproducibility of Results Risk adjustment Middle Aged Intensive care unit United States Intensive Care Units Informatics Calibration Hospital Information Systems Female Risk Adjustment Risk of death business |
| Zdroj: | Critical care medicine. 31(6) |
| ISSN: | 0090-3493 |
| Popis: | Comparison of outcome among intensive care units (ICUs) requires risk adjustment for differences in severity of illness and risk of death at admission to the ICU, historically obtained by costly chart review and manual data entry.To accurately estimate patient risk of death in the ICU using data easily available in hospital electronic databases to permit automation.Cohort study to develop and validate a model to predict mortality at hospital discharge using multivariate logistic regression with a split derivation (17,731) and validation (11,646) sample formed from 29,377 consecutive first ICU admissions to medical, cardiac, and surgical ICUs in 17 Veterans' Health Administration hospitals between February 1996 and July 1997.Mortality at hospital discharge adjusted for age, laboratory data, diagnosis, source of ICU admission, and comorbid illness.The overall hospital death rate was 11.3%. In the validation sample, the model separated well between survivors and nonsurvivors (area under the receiver operating characteristic curve = 0.885). Examination of the observed vs. the predicted mortality across the range of mortality showed the model was well calibrated.Automation could broaden access to risk adjustment of ICU outcomes with only a small trade-off in discrimination. Broader use might promote valid evaluation of ICU outcomes, encouraging effective practices and improving ICU quality. |
| Databáze: | OpenAIRE |
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