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Frequency, Risk Factors, and Outcomes of Early Unplanned Readmissions to PICUs*

Edwards, Jeffrey D. MD, MA, MAS1; Lucas, Adam R. PhD2; Stone, Patricia W. PhD, RN3,4; Boscardin, W. John PhD5,6; Dudley, R. Adams MD, MBA7,8

doi: 10.1097/CCM.0b013e31829eb970
Pediatric Critical Care

Objectives: To determine the rate of unplanned PICU readmissions, examine the characteristics of index admissions associated with readmission, and compare outcomes of readmissions versus index admissions.

Design: Retrospective cohort analysis.

Setting: Ninety North American PICUs that participated in the Virtual Pediatric Intensive Care Unit Systems.

Patients: One hundred five thousand four hundred thirty-seven admissions between July 2009 and March 2011.

Interventions: None.

Measurements and Main Results: Unplanned PICU readmission within 48 hours of index discharge was the primary outcome. Summary statistics, bivariate analyses, and mixed-effects logistic regression model with random effects for each hospital were performed.There were 1,161 readmissions (1.2%). The readmission rate varied among PICUs (0–3.3%), and acute respiratory (56%), infectious (35%), neurological (28%), and cardiovascular (20%) diagnoses were often present on readmission. Readmission risk increased in patients with two or more complex chronic conditions (adjusted odds ratio, 1.72; p < 0.001), unscheduled index admission (adjusted odds ratio, 1.37; p < 0.001), and transfer to an intermediate unit (adjusted odds ratio, 1.29; p = 0.004, compared with ward). Trauma patients had a decreased risk of readmission (adjusted odds ratio, 0.67; p = 0.003). Gender, race, insurance, age more than 6 months, perioperative status, and nighttime transfer were not associated with readmission. Compared with index admissions, readmissions had longer median PICU length of stay (3.1 vs 1.7 d, p < 0.001) and higher mortality (4% vs 2.5%, p = 0.002).

Conclusions: Unplanned PICU readmissions were relatively uncommon, but were associated with worse outcomes. Several patient and admission characteristics were associated with readmission. These data help identify high-risk patient groups and inform risk-adjustment for standardized readmission rates.

Supplemental Digital Content is available in the text.

1Division of Pediatric Critical Care, Columbia University College of Physician and Surgeons, New York, NY.

2Department of Mathematics, Mills College, Oakland, CA.

3Columbia University School of Nursing, Columbia University, New York, NY.

4Center for Health Policy, Columbia University, New York, NY.

5Department of Epidemiology and Biostatistics, University of California, San Francisco, CA.

6Department of Medicine, University of California, San Francisco, CA.

7Division of Pulmonary and Critical Care, University of California, San Francisco, CA.

8Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, CA.

* See also p. 2831.

This study was performed at Columbia University.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (

Supported, in part, by Pediatric Critical Care Scientist Development Program.

Dr. Edwards was supported by a National Institutes of Health (NIH) Pediatric Critical Care Scientist Development Program grant (K12 HD047349) during the time of this study. Dr. Stone’s institution received grant support from NIH. Dr. Stone is employed by Columbia University. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Address requests for reprints to: Jeffrey Edwards, MD, MA, MAS, Division of Pediatric Critical Care, 3959 Broadway, CHN 10–24, New York, NY 10032. E-mail:

© 2013 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins