To secure improved health outcomes for their population and deliver QIPP targets, CCGs are developing and implementing plans to reduce or avoid acute activity. At the same time, Acute Trust need to continue to reduce the resource implications of activity in order to operate within deflating national tariffs.
CCG and Trust are often not fully sighted on each other’s plans and a further set of extrinsic factors (demography, top-down reconfigurations) will also impact on activity levels.
Understanding the combined impact of these factors and the interaction between them is not trivial, but is essential in order to plan and deliver a sustainable health economy. Remotely constructed, ‘black-box’ models of future activity are unlikely to be owned and trusted by CCGs and Trusts.
The Strategic Analytics Team have worked with a number of health economies in the West Midlands to deliver collaborative modelling exercises to support the CCGs and Trust to reach a shared view about future acute activity.
The approach brings together managers and clinicians from local commissioning and provider organisations to negotiate and agree a set of change parameters. These parameters, reflecting the group’s ambition and expectations for change and emerge over the course of 4 or 5 facilitated workshops. Whilst ultimately these change parameter rely on judgements, they are informed by detailed information packs supplied by the Strategic Analytics Team.
The model consists of five components;
- (Commissioner) activity avoidance strategies
- (Provider) efficiency strategies
- Top down or bottom up service or specialty reconfigurations
- Demographic shift
- Patient flows
The Strategic Analytics Team have built, over several years, a catalogue of those subsets of acute activity which are commonly the focus of commissioner activity avoidance schemes and provider efficiency strategies and a set of algorithms that can identify these subsets of activity from Hospital Episode Statistics.
Demographic changes take account not only of the change in population size and age structure, but also the change in age-specific health status.
The outputs of the modelling exercise include;
- A detailed description of the modelled activity, bed day use and commissioner costs in 2018/19 (or at some other agreed future point)
- A bridge analysis showing the impact of the modelled changes on activity, bed day use and costs
- Data cubes to support local analysis of the modelled future county
- a classification of the avoided activity into 3 groups;
- dependant on community or primary care alternative
- dependant on public health intervention
- deliverable with improved process or policy
- a high level description and where possible, quantification of the non-acute services or interventions that partner organisations would be required to provide