Affiliation:
1. Division of Critical Care, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
2. Department of Epidemiology and Biostatistics, Western University, London, Ontario, Canada
Abstract
Purpose: To describe factors (demographics and clinical characteristics) that predict patients who are at an increased risk of adverse events or unplanned return visits to a health-care facility following discharge direct to home (DDH) from intensive care units (ICUs). Methods: Prospective cohort study of all adult patients who survived their stay in our medical–surgical–trauma ICU between February 2016 and 2017 and were discharged directly home. Patients were followed for 8 weeks postdischarge. Univariable and multivariable logistic regression analyses were performed to identify factors associated with adverse events or unplanned return visits to a health-care facility following DDH from ICU. Results: A total of 129 DDH patients were enrolled and completed the 8-week follow-up. We identified 39 unplanned return visits (URVs). There was 0% mortality at 8 weeks postdischarge. Eight potential predictors of hospital URVs ( P < .2) were identified in the univariable analysis: prior substance abuse (odds ratio [OR] of URV of 2.50 [95% confidence interval: 1.08-5.80], hepatitis (OR: 6.92 [1.68-28.48]), sepsis (OR: 11.03 [1.19-102.29]), admission nine equivalents of nursing manpower score (NEMS) <24 (OR: 2.28 [1.03-5.04], no fixed address (OR: 22.9 [1.2-437.3]), ICU length of stay (LOS) <2 days (OR: 2.95 [1.28-6.78]), home discharge within London, Ontario (OR: 2.44 [1.00-5.92]), and left against medical advice (AMA; OR: 6.06 [2.04-17.98]). Conclusions: Our study identified 8 covariates that were potential predictors of URV: prior substance abuse, hepatitis, sepsis, admission NEMS <24, no fixed address, ICU LOS <2 days, home discharge within London, Ontario, and left AMA. The practice of direct discharges home from the ICU would benefit from adequately powered multicenter study in order to construct a clinical prediction model (that would require further testing and validation).
Subject
Critical Care and Intensive Care Medicine
Cited by
6 articles.
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