A novel healthcare resource allocation decision support tool: A forecasting-simulation-optimization approach

Abstract

The increasing pressures on the healthcare system in the UK are well documented. The solution lies in making best use of existing resources (e.g. beds), as additional funding is not available. Increasing demand and capacity shortages are experienced across all specialties and services in hospitals. Modelling at this level of detail is a necessity, as all the services are interconnected, and cannot be assumed to be independent of each other. Our review of the literature revealed two facts; First an entire hospital model is rare, and second, use of multiple OR techniques are applied more frequently in recent years. Hybrid models which combine forecasting, simulation and optimization are becoming more popular. We developed a model that linked each and every service and specialty including A&E, and outpatient and inpatient services, with the aim of, 1) forecasting demand for all the specialties, 2) capturing all the uncertainties of patient pathway within a hospital setting using discrete event simulation, and 3) developing a linear optimization model to estimate the required bed capacity and staff needs of a mid-size hospital in England (using essential outputs from simulation). These results will bring a different perspective to key decision makers with a decision support tool for short and long term strategic planning to make rational and realistic plans, and highlight the benefits of hybrid models.

Goal Programming and Mathematical Modelling for Developing a Capacity Planning Decision Support System-Based Framework in Higher Education Institutions

“…They created a linear optimization model to predict the needed bed capacity and staff demands of an England mid-size hospital. These findings were meant to provide important decision-makers with a new viewpoint by providing a decision support tool for short-and long-term strategic planning, allowing them to generate more reasonable and realistic plans, as well as highlighting the benefits of hybrid models [28].…”

Resources management impact on neonatal services performance in the United Kingdom: A system dynamics modelling approach

“…Examples of DES applications in healthcare include demand and capacity modelling for emergency services, 47 resources management in hospitals, 48 reconfiguration of cataract surgery pathways 25 and prevention of mother to child HIV transmission 49 . SD was used to investigate antibiotics prescription in UK hospitals, 50 health seeking behaviour of pregnant women in Pakistan, 51 planning of cardiovascular disease interventions in the United States 52 and evaluation of policies to reduce tuberculosis and HIV infections in Estonia 53 .…”

A DEA-Based Complexity of Needs Approach for Hospital Beds Evacuation during the COVID-19 Outbreak

“…The increasing pressure on limited resources of health systems during the pandemic has highlighted the need for efficiency-based tools and methodologies to offer new combined perspectives on how to use the hospital's facilities, resources, and capabilities optimally. Ordu et al [ 8 , 9 ] develop an interesting decision support tool for modelling capacity constraints, and allocating hospitals' resources, combining discrete event simulation and forecasting techniques. The application in the accident and emergency department captures the outpatient demand for each specialty by age and first/followup referrals and the entire service pathway on different scenarios.…”