Emergency departments (EDs) typically have multiple areas where patients of different acuity levels receive treatments. In practice, different areas often operate with fixed nurse staffing levels. When there are substantial imbalances in congestion among different areas, it could be beneficial to deviate from the original assignment and reassign nurses. However, reassignments typically are only feasible at the beginning of 8–12-h shifts, providing partial flexibility in adjusting staffing levels. In this work, we propose a stochastic queueing network model of patient flow in the ED and study an associated fluid control problem to guide the reassignment decision for two types of nursing staff. We propose a heuristic solution approach and investigate its performance both analytically and using simulation. Analytical results and simulation experiments suggest a significant reduction of waiting times in parameter regimes relevant to the ED setting. We further implement the staffing approach at a large ED. This pilot study highlights several challenges of implementing operational interventions in the ED, including the difficulty of establishing a clean statistical environment in such setting. Despite these challenges, we find that guiding reassignment decisions using our approach is associated with significant improvements to patient flow including a reduction in average total ED length-of-stay of 1.7 h.

Carri Chan, Vahid Sarhangian, Prem Talwai, and Kriti Gogia
Journal Article
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Full Citation

Chan, Carri, Vahid Sarhangian, Prem Talwai, and Kriti Gogia
. “Utilizing Partial Flexibility to Improve Emergency Department Flow: Theory and Implementation.” (August 05, 2022).