Evaluation of a Split Flow Model for the Emergency Department

Juan Camilo David Gomez (), Amy L. Cochran (), Brian W. Patterson () and Gabriel Zayas-Cabán ()
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Juan Camilo David Gomez: Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison, Wisconsin 53706
Amy L. Cochran: Department of Mathematics, University of Wisconsin–Madison, Madison, Wisconsin 53706; Department of Population Health Sciences, University of Wisconsin–Madison, Madison, Wisconsin 53706
Brian W. Patterson: BerbeeWalsh Department of Emergency Medicine, University of Wisconsin–Madison, Madison, Wisconsin 53706
Gabriel Zayas-Cabán: Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison, Wisconsin 53706

Manufacturing & Service Operations Management, 2024, vol. 26, issue 3, 911-930

Abstract: Problem definition : Split flow models, in which a physician rather than a nurse performs triage, are increasingly being used in hospital emergency departments (EDs) to improve patient flow. Before deciding whether such interventions should be adopted, it is important to understand how split flows causally impact patient flow and outcomes. Methodology/results : We employ causal inference methodology to estimate average causal effects of a split flow model on time to be roomed, time to disposition after being roomed, admission decisions, and ED revisits at a large tertiary teaching hospital that uses a split flow model during certain hours each day. We propose a regression discontinuity design to identify average causal effects, which we formalize with causal diagrams. Using electronic health records data ( n = 21,570), we estimate that split flow increases average time to be roomed by about 4.6 minutes (95% confidence interval (95% CI): 2.9, 6.2 minutes) but decreases average time to disposition by 14.4 minutes (95% CI: 4.1, 24.7 minutes), leading to an overall reduction in length of stay. Split flow is also found to decrease admission rates by 5.9% (95% CI: 2.3%, 9.4%) but not at the expense of a significant change in revisit rates. Lastly, we find that the split flow model is especially effective at reducing length of stay during low congestion levels, which mediation analysis partly attributes to early task initiation by the physician assigned to triage. Managerial implications : A split flow model can improve flow and may have downstream effects on admissions but not revisits.

Keywords: split flow model; causal inference; emergency department; patient discharge; electronic health records (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:26:y:2024:i:3:p:911-930

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