![]() Policies designed to improve population health will reduce ED attendances and enhance quality and safety in the long-term.Ībstract = "BackgroundIn the United Kingdom, Emergency Departments (EDs) are under significant pressure due to an ever-increasing number of attendances. ![]() ![]() Using the MGSR to forecast long-term demand under different scenarios, we found improving population health would reduce peak ED attendances per CCG by approximately 1000 per month after 2 years.Ĭombining models of population health and wider urgent care service capacity for predicting monthly ED attendances leads to an improved performance compared to each model individually. The MGSR leads to an overall improvement in performance, with an R-squared of 0.79 ± 0.02 and MAPE of 3% when forecasting mean monthly ED attendances per CCG. Measures of service capacity explain 41 ± 4% of the variance in monthly ED attendances and measures of population health explain 62 ± 22%. We used the MGSR to forecast ED demand over a 4-year period under hypothetical scenarios where service capacity is increased, or population health is improved. We assessed model performance using the R-squared statistic, measuring variance explained, and the Mean Absolute Percentage Error (MAPE), measuring forecasting accuracy. The MGSR combines measures of population health and health service capacity in other related settings. We developed a novel multi-granular stacked regression (MGSR) model using publicly available data to predict future mean monthly ED attendances within Clinical Commissioning Group regions in England. Understanding how the capacity of other urgent care services and the health of a population may influence ED attendances is imperative for commissioners and policy makers to develop long-term strategies for reducing this pressure and improving quality and safety. In the United Kingdom, Emergency Departments (EDs) are under significant pressure due to an ever-increasing number of attendances.
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