Demand and capacity modelling for acute services using discrete event simulation. Issue 1 (1st March 2017) - Demir, Eren; Gunal, Murat M; Southern, David
Abstract: Increasing demand for services in England with limited healthcare budget has put hospitals under immense pressure. Given that almost all National Health Service (NHS) hospitals have severe capacity constraints (beds and staff shortages), a decision support tool (DST) is developed for the management of a major NHS Trust in England. Acute activities are forecasted over a 5-year period broken down by age groups for 10 specialty areas. Our statistical models have produced forecast accuracies in the region of 90%. We then developed a discrete event simulation model capturing individual patient pathways until discharge (in accident and emergency, inpatient and outpatients), where arrivals are based on the forecasted activity outputting key performance metrics over a period of time, for example, future activity, bed occupancy rates, required bed capacity, theatre utilisations for electives and non-electives, clinic utilisations and diagnostic/treatment procedures. The DST allows Trusts to compare key performance metrics for thousands of different scenarios against their existing service (baseline). The power of DST is that hospital decision makers can make better decisions using the simulation model with plausible assumptions that are supported by statistically validated data.