1.Large observational study on risks predicting emergency department return visits and associated disposition deviations
Charles HUGGINS ; Richard D ROBINSON ; Heidi KNOWLES ; Jennalee CIZENSKI ; Rosalia MBUGUA ; Jessica LAUREANO-PHILLIPS ; Chet D SCHRADER ; Nestor R ZENAROSA ; Hao WANG
Clinical and Experimental Emergency Medicine 2019;6(2):144-151
OBJECTIVE: A common emergency department (ED) patient care outcome metric is 72-hour ED return visits (EDRVs). Risks predictive of EDRV vary in different studies. However, risk differences associated with related versus unrelated EDRV and subsequent EDRV disposition deviations (EDRVDD) are rarely addressed. We aim to compare the potential risk patterns predictive of related and unrelated EDRV and further determine those potential risks predictive of EDRVDD.METHODS: We conducted a large retrospective observational study from September 1, 2015 through June 30, 2016. ED Patient demographic characteristics and clinical metrics were compared among patients of 1) related; 2) unrelated; and 3) no EDRVs. EDRVDD was defined as obvious disposition differences between initial ED visit and return visits. A multivariate multinomial logistic regression was performed to determine the independent risks predictive of EDRV and EDRVDD after adjusting for all confounders.RESULTS: A total of 63,990 patients were enrolled; 4.65% were considered related EDRV, and 1.80% were unrelated. The top risks predictive of EDRV were homeless, patient left without being seen, eloped, or left against medical advice. The top risks predictive of EDRVDD were geriatric and whether patients had primary care physicians regardless as to whether patient returns were related or unrelated to their initial ED visits.CONCLUSION: Over 6% of patients experienced ED return visits within 72 hours. Though risks predicting such revisits were multifactorial, similar risks were identified not only for ED return visits, but also for return ED visit disposition deviations.
Emergencies
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Emergency Service, Hospital
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Humans
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Logistic Models
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Observational Study
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Patient Care
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Patient Outcome Assessment
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Physicians, Primary Care
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Retrospective Studies