Improving Efficiency and Equity of Ambulance Services through Advanced Demand Modelling

点击翻译按钮获取中文摘要

Demand for Ambulance Services in England has risendramatically over recent years, with growing pressureanticipated for future years. The disparity between theincreasing demand and limited ambulance resources makesthe major challenge for maintaining a high-quality service. In2017, NHS England undertook a significant national reformcalled the Ambulance Response Programme (ARP), designedto address efficiency and performance issues. It noted theover-use of immediate dispatch decisions and the insufficientallocation of resources to incidents. Key issues concerned:the quality of care; its cost-effectiveness; and the equality ofprovision across areas and population groups. Given suchsituation, from 2017 to 2018, King's researchers haveworked with the London Ambulance Service (LAS) on anESRC-funded project - DASH, exploring how big data couldimprove decision-making in ambulance response. The finalreport suggested six new data initiatives, out of which, threeare strongly related to demand prediction.In view of the growing pressures of NHS, and the necessity ofambulance services to understand the needs of thepopulations they serve, the proposed PhD project aims todevelop an advanced demand prediction model forambulance services taking LAS as a case study. Theresearch is to find the most correlated socioeconomic,environmental, and spatiotemporal factors and to modelthese factors as predictors of ambulance demand. The finalcomponent of the PhD will develop the implications of themodel as Demand Management innovations, for futuretesting.