A Mixed Integer Linear Program For Human And Material Resources Optimization In Emergency Department

TL;DR

This paper presents a mixed integer linear programming model to optimize human and material resources in an emergency department, aiming to reduce patient waiting times using real data and an SAA solution approach.

Contribution

It introduces a novel MILP model for ED resource optimization and demonstrates its effectiveness with real hospital data and SAA methodology.

Findings

Reduction in total patient waiting time

Effective resource allocation improves ED throughput

Validated with real hospital data

Abstract

The discrepancy between patient demand and the emergency departments (ED) capacity, that mainly depends on human resources and on beds available for patients, often lead to ED's overcrowding and to the increase in waiting time. In this paper, we focus on the optimization of the human (medical and paramedical staff) and material resources (beds) in the ED of the hospital center of Troyes, France (CHT). We seek to minimize the total number of waiting patients from their arrival to their discharge. We propose a mixed integer linear program solved by a sample average approximation (SAA) approach. The program has been tested on a set of real data gathered from the ED information system. Numerical results show that the optimization of human and material resources leads to a decrease of total number of waiting patients.