Simulation-based optimisation approach to improve emergency department resource planning: A case study of Tunisian hospital.

Background: The emergency department (ED) is a gateway to hospitals and is in the centre of hospital management efforts. It is often saturated by a continuous flow of patients, which causes excessive patient waiting time.

Aims: This study integrates simulations with optimisation to design planning decision support for an ED. We considered all the processes of the ED, from triage to bed assignment. This study's main objective was to determine the optimal number of doctors, nurses, and beds required to schedule patients with different acuity levels to minimise both the total patient waiting time and the patient average length of stay and balance the resource utilisation rates. The problem is also characterised by multiple uncertainties, such as the patient arrival rate and service times in each stage of the process.

Method: We first propose a stochastic mixed-integer programing model that is solved using the sample average approximation approach. The resulting resource sizing is then evaluated using a discrete-event simulation model by comparing different patient scheduling rules.

Results: Numerical experiments highlight the performance of the proposed approach using data from a Tunisian ED hospital.