Institutional members access full text with Ovid®

Share this article on:

An Empirical Derivation of the Optimal Time Interval for Defining ICU Readmissions

Brown, Sydney E. S. PhD*; Ratcliffe, Sarah J. PhD*; Halpern, Scott D. MD, PhD*,†,‡

doi: 10.1097/MLR.0b013e318293c2fa
Original Articles

Background: Intensive care unit (ICU) readmission rates are commonly viewed as indicators of ICU quality. However, definitions of ICU readmissions vary, and it is unknown which, if any, readmissions are associated with ICU quality.

Objective: Empirically derive the optimal interval between ICU discharge and readmission for purposes of considering ICU readmission as an ICU quality indicator.

Research Design: Retrospective cohort study.

Subjects: A total of 214,692 patients discharged from 157 US ICUs participating in the Project IMPACT database, 2001–2008.

Measures: We graphically examined how patient characteristics and ICU discharge circumstances (eg, ICU census) were related to the odds of ICU readmissions as the allowable interval between ICU discharge and readmission was lengthened. We defined the optimal interval by identifying inflection points where these relationships changed significantly and permanently.

Results: A total of 2242 patients (1.0%) were readmitted to the ICU within 24 hours; 9062 (4.2%) within 7 days. Patient characteristics exhibited stronger associations with readmissions after intervals >48–60 hours. By contrast, ICU discharge circumstances and ICU interventions (eg, mechanical ventilation) exhibited weaker relationships as intervals lengthened, with inflection points at 30–48 hours. Because of the predominance of afternoon readmissions regardless of time of discharge, using intervals defined by full calendar days rather than fixed numbers of hours produced more valid results.

Discussion: It remains uncertain whether ICU readmission is a valid quality indicator. However, having established 2 full calendar days (not 48 h) after ICU discharge as the optimal interval for measuring ICU readmissions, this study will facilitate future research designed to determine its validity.

Supplemental Digital Content is available in the text.

*Center for Clinical Epidemiology and Biostatistics

Division of Pulmonary, Allergy, and Critical Care Medicine

Leonard Davis Institute of Health Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA

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, www.lww-medicalcare.com.

Supported by: (1) F30 HL107020 from the National Heart, Lung, and Blood Institute (S.E.S.B.); and (2) K08 HS018406 from the Agency for Healthcare Research and Quality (S.D.H.). Neither funding sources nor Cerner Corporation had a role in the design of this study or in the decision to submit it for publication.

The authors declare no conflict of interest.

Reprints: Sydney E.S. Brown, PhD, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, 108 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021. E-mail: sydney2@mail.med.upenn.edu.

© 2013 by Lippincott Williams & Wilkins.