Evaluation of a Split Flow Model for the Emergency Department
Juan Camilo David Gomez, Amy L. Cochran, Brian W. Patterson, Gabriel, Zayas-Caban

TL;DR
This study uses causal inference to evaluate how a split flow model, where physicians perform triage, affects patient flow and outcomes in an emergency department, showing it reduces length of stay and admissions without increasing revisits.
Contribution
It introduces a causal inference approach with a regression discontinuity design to quantify the effects of split flow models on ED patient flow and outcomes.
Findings
Split flow increases time to be roomed by 4.6 minutes.
It decreases time to disposition by 14.4 minutes.
Reduces admission rates by 5.9% without increasing revisits.
Abstract
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. 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 (RD) 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% CI: [2.9,6.2]…
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Taxonomy
TopicsEmergency and Acute Care Studies · Healthcare Policy and Management · Healthcare Operations and Scheduling Optimization
