Patient Flow Simulation Using Historically Informed Synthetic Data

Hospital overcrowding is a major problem for healthcare systems around the globe. In order to better estimate future demands and adequate resources coping with such demands, statistical computerised modelling can be applied. This then allow administrators decision makers quantify impacts of various “what-if” scenarios on hospital performance measures. paper investigates application Discrete Event Simulation towards optimising Emergency Department while measuring overall length stay queuing time emergency patients as target measure. particular, we explore strategies generating historically informed synthetic data that helps simulation model track patient flow through over frame. Using developed model, several resource configurations are tested using from one busiest departments in state Queensland baseline quantifying changes key metrics. It was found adding single bed (and associated resources) department would result 23% decrease average treatment delay.