A configurable discrete event simulation to model patient flow along cancer pathways

Abstract

Many European healthcare systems are increasingly challenged in delivering services to ageing populations. The COVID-19 pandemic exacerbated the situation, particularly in the UK where the NHS had little spare capacity and was forced to suspend many routine services during the first and second wave of the pandemic. Cancer services have been particularly impacted, with patients currently facing long waiting times. Addressing current bottlenecks is crucial for clearing the accumulated backlog and meeting the national performance targets. We developed a configurable discrete event simulation model of cancer pathways and a corresponding bespoke software tool (“Cancer Pathway Simulator”) for use in partnership with hospital analysts. Our approach involves strong engagement with clinicians and operational managers to identify the right model configuration and parameter values for the pathway of interest. We discuss a case study in which we collaborated with a London-based hospital and applied the simulation tool to the lung cancer pathway. We conducted a bottleneck analysis and utilised a design of experiments approach to analyse the system. Results from the simulation were used to identify system bottlenecks and system characteristics that significantly affect the mean throughput time. This paper presents our tool and demonstrates its usefulness in informing decision-making regarding resource allocation.