Alexandre Tran1, Shannon M Fernando1, Daniel I McIsaac1, Bram Rochwerg1, Garrick Mok1, Andrew J E Seely1, Dalibor Kubelik1, Kenji Inaba1, Dennis Y Kim1, Peter M Reardon1, Jennifer Shen1, Peter Tanuseputro1, Kednapa Thavorn1, Kwadwo Kyeremanteng1. 1. From the Department of Surgery, University of Ottawa, Ottawa, Ont. (Tran, Seely, Kubelik); the Division of Critical Care Medicine, Department of Medicine, University of Ottawa, Ottawa, Ont. (Fernando, Seely, Kubelik, Reardon, Kyeremanteng); the Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ont. (Tran, McIsaac, Seely, Shen, Tanuseputro, Thavorn, Kyeremanteng); the Department of Emergency Medicine, University of Ottawa, Ottawa, Ont. (Fernando, Mok, Reardon); the Department of Anesthesiology and Pain Medicine, University of Ottawa, Ottawa, Ont. (McIsaac); the School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ont. (McIsaac, Seely, Tanuseputro, Thavorn); the Department of Medicine, Division of Critical Care, McMaster University, Hamilton, Ont. (Rochwerg); the Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ont. (Rochwerg); the Division of Acute Care Surgery, Department of Surgery, University of Southern California, Los Angeles, Calif. (Inaba); the Department of Surgery, University of California, Los Angeles, Calif. (Kim); the Division of Palliative Care, Department of Medicine, University of Ottawa, Ottawa, Ont. (Tanuseputro, Kyeremanteng); and the Institut du Savoir Montfort, Ottawa, Ont. (Kyeremanteng).
Abstract
Background: Prior studies of rapid response team (RRT) implementation for surgical patients have demonstrated mixed results with respect to reductions in poor outcomes. The aim of this study was to identify predictors of in-hospital mortality and hospital costs among surgical inpatients requiring RRT activation. Methods: We analyzed data prospectively collected from May 2012 to May 2016 at The Ottawa Hospital. We included patients who were at least 18 years of age, who were admitted to hospital, who received either preoperative or postoperative care, and and who required RRT activation. We created a multivariable logistic regression model to describe mortality predictors and a multivariable generalized linear model to describe cost predictors. Results: We included 1507 patients. The in-hospital mortality rate was 15.9%. The patient-related factors most strongly associated with mortality included an Elixhauser Comorbidity Index score of 20 or higher (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.96-6.60) and care designations excluding admission to the intensive care unit and cardiopulmonary resuscitation (OR 3.52, 95% CI 2.25-5.52). The strongest surgical predictors included neurosurgical admission (OR 2.09, 95% CI 1.17-3.75), emergent surgery (OR 2.04, 95% CI 1.37-3.03) and occurrence of 2 or more operations (OR 1.73, 95% CI 1.21-2.46). Among RRT factors, occurrence of 2 or more RRT assessments (OR 2.01, 95% CI 1.44-2.80) conferred the highest mortality. Increased cost was strongly associated with admitting service, multiple surgeries, multiple RRT assessments and medical comorbidity. Conclusion: RRT activation among surgical inpatients identifies a population at high risk of death. We identified several predictors of mortality and cost, which represent opportunities for future quality improvement and patient safety initiatives.
Background: Prior studies of rapid response team (RRT) implementation for surgical patients have demonstrated mixed results with respect to reductions in poor outcomes. The aim of this study was to identify predictors of in-hospital mortality and hospital costs among surgical inpatients requiring RRT activation. Methods: We analyzed data prospectively collected from May 2012 to May 2016 at The Ottawa Hospital. We included patients who were at least 18 years of age, who were admitted to hospital, who received either preoperative or postoperative care, and and who required RRT activation. We created a multivariable logistic regression model to describe mortality predictors and a multivariable generalized linear model to describe cost predictors. Results: We included 1507 patients. The in-hospital mortality rate was 15.9%. The patient-related factors most strongly associated with mortality included an Elixhauser Comorbidity Index score of 20 or higher (odds ratio [OR] 3.60, 95% confidence interval [CI] 1.96-6.60) and care designations excluding admission to the intensive care unit and cardiopulmonary resuscitation (OR 3.52, 95% CI 2.25-5.52). The strongest surgical predictors included neurosurgical admission (OR 2.09, 95% CI 1.17-3.75), emergent surgery (OR 2.04, 95% CI 1.37-3.03) and occurrence of 2 or more operations (OR 1.73, 95% CI 1.21-2.46). Among RRT factors, occurrence of 2 or more RRT assessments (OR 2.01, 95% CI 1.44-2.80) conferred the highest mortality. Increased cost was strongly associated with admitting service, multiple surgeries, multiple RRT assessments and medical comorbidity. Conclusion: RRT activation among surgical inpatients identifies a population at high risk of death. We identified several predictors of mortality and cost, which represent opportunities for future quality improvement and patient safety initiatives.
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