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theses

An Emergency Department (ED) is a health care service that delivers time-critical care to unscheduled patient arrivals. Due to an ever increasing number of arrivals, the number of patients often exceed the physical and stang capacity resulting in long waiting times, patients leaving without being seen by medical sta↵ and higher mortality levels. In this work we investigate the scheduling of sta↵ and equipment resources in EDs. We propose a spatial agent-based simulation framework to quantify the impacts of sta↵ decision processes, such as patient selection, on patient length of stay and waiting times. To explore the ED administration intuition that patient throughput could be increased by prioritizing short patient visits, and corroborate our findings from our simulations that the order in which providers see their next patient a↵ects the length of time patients spend in the ED, we proposed a real-time scheduler that prioritizes short visits. We concluded that Emergency Departments need an online system that is constantly adapting to find an optimal scheduling of patient tasks to available resources. To that e↵ect we propose a mixed-integer linear programming model (MILP) to find an optimal schedule of tasks to resources that minimizes the time spent in the ED for every patient. Our findings show a large fraction of unaccounted tasks on the JSUMC Electronic Health Records (EHR), and that time and motion studies would be needed to complement EHR’s to accurately model ED scheduling.

ETD_9507

Ph.D.

Includes bibliographical references

by Ana Paula Centeno

doi:10.7282/t3-f7yg-nx91

ETD doctoral

The author owns the copyright to this work.