Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context

Authors

Rayan Taher, Palak Bhanushali, Stephanie Allan, Mario Alvarez-Jimenez, Heather Bolton, Laura Dennison, Brian E. Wallace, Heather D. Hadjistavropoulos, Charlotte L. Hall, Amy Hardy, Alasdair L. Henry, Sam Lane, Tess Maguire, Adam Moreton, Talar R. Moukhtarian, Elvira Perez Vallejos, Sukhi Shergill, Daniel Stahl, Graham R. Thew, Ladislav Timulak, David van den Berg, Noemi Viganò, Ben Wensley Stock, Katherine S. Young, and Jenny Yiend

Abstract

Background

Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.

Aims
The aim of this study was to generate an experts’ consensus on how the medical regulatory method used for assessing safety could best be adapted for DMHIs.

Method
An online Delphi study containing three rounds was conducted with an international panel of 20 experts with experience/knowledge in the field of UK digital mental health.

Results
Sixty-four items were generated, of which 41 achieved consensus (64%). Consensus emerged around ten recommendations, falling into five main themes: Enhancing the quality of adverse events data in DMHIs; Re-defining serious adverse events for DMHIs; Reassessing short-term symptom deterioration in psychological interventions as a therapeutic risk; Maximising the benefit of the Yellow Card Scheme; and Developing a harmonised approach for assessing the safety of psychological interventions in general.

Conclusion
The implementation of the recommendations provided by this consensus could improve the assessment of safety of DMHIs, making them more effective in detecting and mitigating risk.