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Evaluating improvement interventions using routine data to support a learning health system: research design, data access, analysis and reporting
  1. Christopher J Weir1,2,
  2. Alexander E P Heazell3,
  3. Sonia Whyte4,
  4. Jane E Norman4,5
  1. 1 Usher Institute, The University of Edinburgh, Edinburgh, UK
  2. 2 Edinburgh Clinical Trials Unit, The University of Edinburgh, Edinburgh, UK
  3. 3 St. Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
  4. 4 Tommy’s Centre for Maternal and Fetal Health, MRC Centre for Reproductive Health, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK
  5. 5 Faculty of Health Sciences, University of Bristol, Bristol, Bristol, UK
  1. Correspondence to Professor Christopher J Weir, Usher Institute, The University of Edinburgh, Edinburgh, UK; Christopher.Weir{at}ed.ac.uk

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Introduction: learning health systems

Friedman and colleagues1 outline a vision of the learning health system founded on the sharing of data and achieved through alignment of information technology, advanced analytics and clinical expertise. The Institute of Medicine2 recognises the potential of the learning health system to generate new information automatically during the delivery of healthcare, offering continual opportunities to improve healthcare processes for the benefit of public health. The learning health system is promoted as a mechanism to accelerate the adoption of effective treatments into clinical practice, shortening the extended delay3 from publication of research findings to implementation. Furthermore, it harbours the ambition to deliver personalised medicine to each service user, rather than the systematic provision of identical care to groups of patients who share the same characteristics. Worldwide escalating costs in healthcare provision due to demographic changes, compounded by ongoing use of ineffective tests and treatments, make it critically important to harness the efficiency gains of a learning health system. Of its many potential characteristics, one distinct attribute of the learning health system is to enable efficient investigation of whether strategies promoting implementation of best practice (such as educational initiatives or care bundles) actually work. A systematic review identifying a low frequency of reports on the evaluation and impact of learning health systems4 prompted us here to reconsider the central requirements for evaluation of improvement interventions within the learning health system.

Here, we reflect on two recent implementation studies, both using efficiencies of the learning health system (minimising data acquisition and relying heavily on data acquisition from existing medical records), to illustrate the key issues arising when incorporating this type of research into the learning health system. In this paper, we argue that the presence of infrastructure which facilitates data sharing, combined with appropriate research design, analysis and reporting, …

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Footnotes

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  • Contributors CJW drafted this Viewpoint; CJW, AEPH, SW and JEN critically reviewed and edited its content.

  • Funding CJW was funded in this work by NHS Lothian via the Edinburgh Clinical Trials Unit. The AFFIRM study was investigator-initiated and funded by the Chief Scientist Office, Scottish Government (CZH/4/882), Tommy's and Sands. SPIRE was funded by NHS England.

  • Competing interests All authors were collaborators on the AFFIRM clinical trial, which is cited in this Viewpoint; AH was a lead investigator on the SPiRE study.

  • Patient consent for publication Not required.

  • Ethics approval AFFIRM received a favourable opinion from Scotland A Research Ethics Committee (Ref 13/SS/0001). SPIRE received a favourable opinion from West Midlands, Edgbaston Research Ethics Committee (Ref 17/WM/0197).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement There are no data in this work.

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