Historically there has been a lack of data science or accurate forecasting in developing capacity. Between 2011 and 2021 the growth in the population served by the Royal Devon & Exeter Hospital rose by 13% which was twice the average national population growth. This increase in demand was not met by sufficient increase in physical infrastructure or capacity. This led to significant waiting list problems with RD&E having some of the longest waiting patients in the country. Exeter and surrounding areas have high housing targets and predict further growth as well as significant growth in an ageing population.
This project aims
- To develop a demonstrator forecasting tool (using breast services as an example) which is made available through a StreamLit app to predict referrals and service demand.
- To use this tool to demonstrate the impact of specific housing developments on service demand to inform workforce planning and to provide data to justify s106 payments from developers to support NHS infrastructure expansion.
- To predict changes in geographical demand and thus feed into project in understanding optimum locations for services on the 10-20 year timescale.
The project objectives are
- To look at the growth in referrals for breast services and predict future clinic capacity required to meet 2WW targets.
- To separate the increase in referrals due to population growth from that due to changes in demographics and referral patterns (due to patient education and increasing incidence of cancer).
- To create a model of growth based on assumptions about population growth and changes in demographics to obtain best and worst case scenarios in terms of demand.