Emergency Departments (EDs) commonly face capacity imbalances and long wait times in a service system handling patients with different priorities. These problems are particularly important for low-priority patients who often remain in the queue for extended periods. We investigate two distinct approaches to address these challenges: fast track (FT) and dynamic priority queue (DPQ). Traditionally, EDs have prioritized patients using an Emergency Severity Index (ESI), in conjunction with FT, to strictly or partially dedicate resources to different ESI patient classes. With our proposed DPQ, patients are prioritized using ESI and additional real-time operational information about the patient, specifically the amount of accumulated wait time and flow time. Using an empirical simulation, we compare the impact of different resource allocation and prioritization approaches on patient length of stay (LOS), including the existing system at the ED, FT with strict and partial dedication and the possibility of shorter and less variable service times, and versions of the proposed DPQ using simple dynamic prioritization. Our main results are that: (i) the DPQ approach dominates the other approaches tested; (ii) for various ED sizes, FT with strict and partial dedication do not reduce average LOS of low-priority patients without significantly increasing average LOS of high-priority patients, unless service time mean and variance are reduced; (iii) DPQ using accumulated wait time or accumulated flow time improves performance. The results are robust to changes in the proportion of patients in each priority level. Overall, expanding decision making about patient prioritization from only considering the patient's clinical condition to also including operational data can improve performance dramatically, even without improved service times.
- Customer prioritization
- Focused and flexible resources
- Service system design
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering