- £1.6 million is available for research that advances the development and use of data from national clinical audits and patient registries as a mechanism for improving health care quality in the UK.
- The programme comprises two funding streams for small and large-scale awards.
- Applications closed on Tuesday 25 July 2017.
The Health Foundation is exploring what a learning health care system might look like in the UK and wants to better understand the elements that could contribute to making one. We recognise that digitisation and analysis of data and information play an important role in supporting health care systems to continuously learn and improve.
The rich information held in national clinical audits and registries can be used to inform improvements in health care quality. However, national audits and registries are yet to realise their full potential in the UK.
The Health Foundation’s £1.6 million Insight 2017 funding invites researchers to submit ideas for research that advances the development and use of data from national clinical audits and patient registries as a mechanism for improving health care quality in the UK.
The programme comprises two funding streams:
- Small-scale awards – up to £100,000 to support innovative research that is particularly novel or conducted at a small scale, completed over 18 months. Projects eligible for funding under this stream include standalone research studies, and feasibility or pilot studies.
- Large-scale awards – between £300,000 and £400,000 for substantive studies across more than one site and/or location of innovative and ambitious research with the potential to support transformational change, completed over three years.
The call aims to fund research that either:
- broadens the involvement of patients in the design and collection of clinical audit and registry data, specifically the collection and use of patient reported outcomes
- demonstrates the value of linking clinical audit and registry data to other data, to improve the value of health care
- explores variation in metrics of clinical quality and outlier identification to determine priorities for improvement.