DH.L Evidence Generator

The rationale for developing the Evidence Generator

Evidence on clinical, cost and implementation effectiveness has a key role to play in facilitating appropriate uptake and implementation of innovations, though personal, professional and organisational issues are important additional factors:


Digital health applications offer huge potential for clinical trials because of their ability to collect and generate data as a direct consequence of use. Arrangements for the design and delivery of clinical trials through Clinical Trials Units and Clinical Research Networks have evolved mainly in the context of conventional interventions involving pharmacological and medicinal products, diagnostic aids and well-defined behavioural and organisational interventions.

Research and evaluation

Research and evaluation can help support quality improvement in services and ensure patient safety, and this is necessary for digital health applications, just as it is for pharma or medical devices.. Considerations of regulatory, safety and governance for digital applications often differ from those relating to pharmacological and medicinal products and are still evolving. Therefore, development of these applications requires suitably adapted procedures and processes as well as appropriate skills and experience to manage the research. This needs to include both recognition of the great potential for user data generation and analysis created by digital applications, as well as awareness of new data protection requirements such as GDPR and of any potential risks for patients or professionals.

Evidence requirements

The evidence requirements for effectiveness and cost effectiveness may mirror those for conventional interventions in many respects. However, factors relating to engagement by patients, professionals and commissioners are likely to be much more important for digital health applications and require a greater emphasis on different research methodologies and mixed methods evaluations which combine health economics, quantitative and qualitative research techniques.

The relative ease of development and the highly competitive nature of the marketplace make it necessary for timescales for development, implementation and evaluation of digital health innovations to be kept to a minimum. This poses a major challenge for current forms of evidence generation where timescales are more extended and research funding and publication channels usually highly resource intensive.

Currently, there is no clear pathway or entry point for digital health innovators that need to generate high quality evidence about the effectiveness of their technology in real world settings.  Organisations that provide support do so through their own network and not always across the whole development pathway:



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