Discrete Event Simulation for Healthcare Organizations: A Tool for Decision Making

TLDR

Healthcare organizations must balance rising patient demand with limited resources, striving for operational efficiency and cost reduction while maintaining quality, yet leaders often rely on subjective data for critical decisions. The article aims to show how discrete event simulation can serve as an evidence‑based tool for developing and vetting operational solutions in healthcare. The authors employ discrete event simulation to model patient flow, bed capacity, staff scheduling, admission procedures, and ancillary resource use, illustrating the approach with a model of crowding and staffing decisions in an urban academic emergency department. The model demonstrates how DES can assess crowding and inform staffing decisions in an urban academic emergency department.

Abstract

EXECUTIVE SUMMARY Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.