  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] 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.
