Long-Range Forecasting for Emergency Care Systems in a Highly Dynamic Setting: A Singapore Case Study.

Objectives: In aging societies such as Singapore, emergency care systems (ECSs) face the challenge of ever-increasing demand for urgent care. The uncertainties around population aging are compounded by the downstream effects of population health interventions. We forecast the demand for ECS use in Singapore, in terms of emergency department length of stay (ED-LOS) hours per person per year, until 2050, with and without the effects of a major intervention that enhances the role of primary and community care. Methods: Using a system dynamics simulation model, we applied age-specific emergency department usage rates-derived from our analysis of 1,736,405 attendances in a large tertiary hospital and stratified by acuity-to an age-stratified population forecast. We simulated a baseline and 4 intervention scenarios based on different efficacy-time and effect size levels. Results: In the baseline scenario, median ED-LOS increased from 580 hours per 1000 residents per year in 2010 to 644 hours per 1000 residents in 2050. Median ED-LOS increased from 276 to 372 hours per 1000 residents per year for high-acuity patients, whereas it decreased from 302 to 274 hours per 1000 residents per year for low-acuity patients. Under all intervention scenarios, low-acuity ECS use per person decreased, caused by "decanting" of this patient group to primary care. However, high-acuity ECS use per person increased because of longevity. Conclusions: In the long term, an overall increase in ECS demand is driven by an increase in high-acuity use; population health interventions can further exacerbate the high-acuity burden. Our work casts light on the relatively less-studied dynamics of long-term ECS demand.