An Empirical Derivation of the Optimal Time Interval for Defining ICU Readmissions
*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.Medical care (Impact Factor: 3.23). 05/2013; 51(8). DOI: 10.1097/MLR.0b013e318293c2fa
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.
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ABSTRACT: Good quality indicators should have face validity, relevance to patients, and be able to be measured reliably. Beyond these general requirements, good quality indicators should also have certain statistical properties, including sufficient variability to identify poor performers, relative insensitivity to severity adjustment, and the ability to capture what providers do rather than patients' characteristics. We assessed the performance of candidate indicators of ICU quality on these criteria. Indicators included ICU readmission, mortality, several length of stay outcomes, and the processes of venous-thromboembolism and stress ulcer prophylaxis provision. Retrospective cohort study SETTING:: One hundred thirty-eight U.S. ICUs from 2001-2008 in the Project IMPACT database. Two hundred sixty-eight thousand eight hundred twenty-four patients discharged from U.S. ICUs. None. We assessed indicators' (1) variability across ICU-years; (2) degree of influence by patient vs. ICU and hospital characteristics using the Omega statistic; (3) sensitivity to severity adjustment by comparing the area under the receiver operating characteristic curve (AUC) between models including vs. excluding patient variables, and (4) correlation between risk adjusted quality indicators using a Spearman correlation. Large ranges of among-ICU variability were noted for all quality indicators, particularly for prolonged length of stay (4.7-71.3%) and the proportion of patients discharged home (30.6-82.0%), and ICU and hospital characteristics outweighed patient characteristics for stress ulcer prophylaxis (ω, 0.43; 95% CI, 0.34-0.54), venous thromboembolism prophylaxis (ω, 0.57; 95% CI, 0.53-0.61), and ICU readmissions (ω, 0.69; 95% CI, 0.52-0.90). Mortality measures were the most sensitive to severity adjustment (area under the receiver operating characteristic curve % difference, 29.6%); process measures were the least sensitive (area under the receiver operating characteristic curve % differences: venous thromboembolism prophylaxis, 3.4%; stress ulcer prophylaxis, 2.1%). None of the 10 indicators was clearly and consistently correlated with a majority of the other nine indicators. No indicator performed optimally across assessments. Future research should seek to define and operationalize quality in a way that is relevant to both patients and providers.
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ABSTRACT: ICU readmissions are associated with increased mortality and costs; however, it is unclear whether these outcomes are caused by readmissions as opposed to residual confounding by illness severity. An assessment of temporal changes in ICU readmission in response to a specific policy change could help disentangle these possibilities. We sought to determine whether ICU readmission rates changed after 2003 ACGME Resident Duty Hours reform ("reform"), and whether there were temporally corresponding changes in other ICU outcomes.
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