The Lab is focused on generating a shared picture and understanding of what’s really going on in health and social care systems, using data.
Pooled data is powerful - it allows us to recognise trends, at both personal and wider levels. The Lab collects local data to analyse. Results are then collated to identify problems and solutions.
The local data is:
- Compared internally within the system (comparisons between viewpoints, for example: localities, GP practices, consultants, speciality)
- Benchmarked against similar places elsewhere
- Described both in terms of the categories listed but also in terms of what it means to population segments (for example: people managing diabetes; young adults)
- Described at the big picture level and at the personal level in terms of people’s stories
The following table details how we categorise and process different types of local data.
|Data theme||Data sources (high level)||Process|
|Demographic and geographical - our health needs||Much of this data has been collected already, but it requires benchmarking, from local/community level to whole system level.|
|How the system currently operates to meet our needs|
The above data can be presented with respect to demographic and geographical attributes.
|Also requires benchmarking, from local/community level to whole system level. Current data must be analysed to find key patterns.|
|How people behave in the current system to meet their needs|
Community statistics - what people can use compared to what they do use
|Mapping of citizens in different groups, from local to whole system level.|
|How data is currently used for change|
Is communication used for improvement and change - personal, academic, strategic?
|Survey clinicians, managers and citizens to generate data.|
|How the current system learns and develops|
Governmental papers on system development.
|Analyse governmental papers linguistically - see which terms form trends, identify developments and initiatives.|
|How adaptive and resilient this system is||Primarily generated by patients in real time - huge value in small data sets and observational data.|
|How fit the system is for the future||Taking all data above and interpreting it through the perspectives of possible, imagined futures.||Use scenarios from data to tell the current story, then extrapolate and model how this could play out potential future scenarios.|
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