Managing and exploiting routinely collected NHS data for research
<p><strong>Introduction</strong> Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed...
|Main Authors:||, ,|
BCS, The Chartered Institute for IT
|Series:||Journal of Innovation in Health Informatics|
|Summary:||<p><strong>Introduction</strong> Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed patient-level information allow this data to be applied to a variety of research questions. However, the sensitivity, complexity and scale of such data also hamper researchers from fully exploiting this potential.</p><p><strong>Objective</strong> Here, we establish the current challenges preventing researchers from making optimal use of the data sets at their disposal, on both the legislative and practical levels, and give recommendations as to how these challenges can be overcome.</p><p><strong>Method</strong> A number of projects has recently been launched in the UK to address poor research data management practices. Rapid Organisation of Healthcare Research Data (ROHRD) at Imperial College, London produced a useful prototype that provides local researchers with a one-stop index of available data sets together with relevant metadata.</p><p><strong>Findings</strong> Increased transparency of data sets’ availability and their provenance leads to better utilisation and facilitates compliance with regulatory requirements.</p><p><strong>Discussion</strong> Research data resulting from NHS data is often not utilised fully, or is handled in a haphazard manner that prevents full auditability of the research. Furthermore, lack of informatics and data management skills in research teams act as a barrier to implementing more advanced practices, such as provenance capture and detailed, regularly updated, data management strategies. Only by a concerted effort at the levels of research organisations, funding bodies and publishers, can we achieve full transparency and reproducibility of the research.</p>|