• Matthew E Lissauer, Jose J Diaz, Mayur Narayan, Paulesh K Shah, and Nader N Hanna.
• Program in Trauma, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA. mlissauer@umm.edu
• Am Surg. 2013 Jun 1;79(6):583-8.

AbstractIntensive care unit (ICU) readmissions are associated with increased resource use. Defining predictors may improve resource use. Surgical ICU patients requiring readmission will have different characteristics than those who do not. We conducted a retrospective cohort study of a prospectively maintained database. The Acute Physiology and Chronic Health Evaluation (APACHE) IV quality database identified patients admitted January 1 through December 31, 2011. Patients were divided into groups: NREA = patients admitted to the ICU, discharged, and not readmitted versus REA = patients admitted to the ICU, discharged, and readmitted. Comparisons were made at index admission, not readmission. Categorical variables were compared by Fisher's exact testing and continuous variables by t test. Multivariate logistic regression identified independent predictors of readmission. There were 765 admissions. Seventy-seven patients required readmission 94 times (12.8% rate). Sixty-two patients died on initial ICU admission. Admission severity of illness was significantly higher (APACHE III score: 69.54 ± 21.11 vs 54.88 ± 23.48) in the REA group. Discharge acute physiology scores were equal between groups (47.0 ± 39.2 vs 44.2 ± 34.0, P = nonsignificant). In multivariate analysis, REA patients were more likely admitted to emergency surgery (odds ratio, 1.9; 95% confidence interval, 1.01 ± 3.5) more likely to have a history of immunosuppression (2.7, 1.4 ± 5.3) or higher Acute Physiology Score (1.02; 1.0 ± 1.03) than NREA. Patients who require ICU readmission have a different admission profile than those who do not "bounce back." Understanding these differences may allow for quality improvement projects such as instituting different discharge criteria for different patient populations.

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