Improving Efficiency and Equity of Ambulance Services through Advanced Demand Modelling


Supervisor: Dr Chen Zhong

Non-accademic partner: London Ambulance Service NHS Trust

Demand for Ambulance Services in England has risen dramatically over recent years, with growing pressure anticipated for future years. The disparity between the increasing demand and limited ambulance resources makes the major challenge for maintaining a high-quality service. In 2017, NHS England undertook a significant national reform called the Ambulance Response Programme (ARP), designed to address efficiency and performance issues. It noted the over-use of immediate dispatch decisions and the insufficient allocation of resources to incidents. Key issues concerned: the quality of care; its cost-effectiveness, and the equality of provision across areas and population groups. In view of the growing pressures of NHS, and the necessity of ambulance services to understand the needs of the populations they serve, the proposed PhD project aims to develop an advanced demand prediction model for ambulance services taking LAS as a case study. The research is to find the most correlated socioeconomic, environmental, and spatiotemporal factors and to model these factors as predictors of ambulance demand. The final component of the PhD will develop the implications of the model as Demand Management innovations, for future testing. PhD candidate selected for this project will have the opportunity to closely work with the forecasting and planning team at LAS, and research domain/centres at KCL including CUSP, SUPHI and Geocomputation.