Evaluation of a Split Flow Model for the Emergency Department

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. Funding: This work was supported by the National Institutes of Health [Grants KL2TR002374 and UL1TR002373]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0003

• 저널Manufacturing & Service Operations Management · 26(3) · 911–930
• 토픽Emergency and Acute Care Studies · Emergency Medicine
• DOI10.1287/msom.2022.0003
• 저자Juan Camilo David Gomez, Amy L. Cochran, Brian W. Patterson, Gabriel Zayas‐Cabán