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Predictive Modelling for Planned and Unplanned Care

Two proof of concept apps have been developed, one supporting unplanned care for emergency departments, and the other supporting clusters of General Practices with long term planning.  

Through collaboration with practice managers, NHS analysts and IG specialists, practical modelling, planning and decision-support tools have been built and made available to key NHS stakeholders across the North East of England. The NENC CHC team partnered with Durham University who achieved success in two distinct areas; one modelling approach was developed for Accident and Emergency (A&E) Admissions at key acute Hospitals in the region ‘Unplanned care’, and a second for Practice Managers and GPs within General Practice settings ‘Planned care’. The team has gained momentum and is currently working with additional partners with further investment such as the NENC ARC on exemplar projects. Unplanned care A&E admissions data were received from several regional NHS Trusts. This was analysed to produce a meaningful predictive model of future A&E attendances. This model was developed in consultation with the NHS Trust analysts to ensure it addressed practical needs in planning and could be easily installed and used on site. The app was useful in detecting patterns and peaks in demand and can be used to support planning decisions which were previously based on anecdotal beliefs relating to service demand. The app was adopted by a trust outside of the project. Planned care Darlington was a pathfinder site in a national NHSE initiative, ‘Healthy New Towns’ (HNT), which reviewed health provision and design in sites planned for extensive housing developments. As part of this programme, the Durham University team, funded by CHC developed a planning support tool that could allow demand and activity changes in population workforce and house building programmes to be modelled. This tool, co-developed with several GP practices and local authorities at 2 sites within the HNT programme, allows managers to model different scenarios and ways of working. As well as modelling the impact of large scale house building on GP practices, managers can also model impacts such as GP retirements, changes to appointment lengths or number of sessions, with visual representations of key targets. This has the potential to lead to efficiencies in delivery. The planning app allows users to better understand current levels of activity and to investigate how different scenarios are likely to affect their practice. For example, one practice manager involved in the programme noticed a significant number of GP and nurse appointments allocated to women aged in their thirties – more so than any other age group. This insight enabled the practice to plan their clinics to meet this demand in a more efficient way.


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