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Maximising Data Usage in NMAHP Research

There is a need to reduce research waste, enhance efficiency and where possible respond to the needs of policymakers and the NHS with more timely production of research. The Unit has made a leading contribution in enhancing the secondary use of pre-existing research data in three key ways:

  1. Collating and curating data from international trials as a resource for researchers and to develop the potential for innovative and efficient trial designs (e.g. Trials within Cohort Studies).
  2. Conducting systematic reviews of existing research and in developing methodological innovations for producing systematic reviews.
  3. Utilising routine data (especially NHS data) for epidemiological and pathways of care analysis, and which can also be linked to trial data for cost-effective long-term trial follow-up.

This programme provides a platform to showcase existing work and to extend the international excellence achieved in the field of Stroke (systematic reviews, trials databases), by applying lessons learned to other priority clinical areas such as Cancer and Mental Health and our other workstreams such as Health Behaviour Change. 

There is now widespread recognition that research needs to be of relevance to patients (and families/carers and the public) and clinicians in order to increase its chances of having any impact. Our exemplary efforts to establish patient/public and professional research priorities will be expanded within this programme and across all workstreams.

Our objectives are to establish more international research collaborations within our workstreams which will contribute to the sharing of existing trial datasets and safe and secure access to these.  Such collaborations add to the potential to share study methods (what worked/did not work) and findings, and to pool data where possible to avoid having to re-run expensive trials. Successful methods employed in this programme and the workstreams will be shared, developed further and disseminated widely.

In going forwards, the Unit will seek to expand its existing body of quantitative researchers with the necessary skills to further NMAHP research using large/linked datasets, and seek to partner with other institutions and organisations in enhancing both skills and research opportunities in these areas.

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