Clinical Perspectives on Using Remote Measurement Technology in Assessing Epilepsy, Multiple Sclerosis, and Depression: Delphi Study

Andrews, Jacob A; Craven, Michael P; Guo, Boliang; Weyer, Janice; Lees, Simon; Zormpas, Spyridon I; Thorpe, Sarah E; Devonshire, Julie; San Antonio-Arce, Victoria; Whitehouse, William P; Julie, Jessica; Malins, Sam; Hammers, Alexander; Reif, Andreas; Ruhe, Henricus G; Durbano, Federico; Barlati, Stefano; Sen, Arjune; Frederiksen, Jette L; Martinelli, Alessandra; Callen, Antonio; Torras-Borrell, Joan; Berrocal-Izquierdo, Nuria; Zabalza, Ana; Morriss, Richard; Hollis, Chris; RADAR-CNS Consortium

Abstract

Background: Multiple sclerosis (MS), epilepsy, and depression are chronic central nervous system conditions in which remote measurement technology (RMT) may offer benefits compared with usual assessment. We previously worked with clinicians, patients, and researchers to develop 13 use cases for RMT: 5 in epilepsy (seizure alert, seizure counting, risk scoring, triage support, and trend analysis), 3 in MS (detecting silent progression, detecting depression in MS, and donating data to a biobank), and 5 in depression (detecting trends, reviewing treatment, self-management, comorbid monitoring, and carer alert).

Objective: In this study, we aimed to evaluate the use cases and related implementation issues with an expert panel of clinicians external to our project consortium.

Methods: We used a Delphi exercise to validate the use cases and suggest a prioritization among them and to ascertain the importance of a variety of implementation issues related to RMT. The expert panel included clinicians from across Europe who were external to the project consortium. The study had 2 survey rounds (n=23 and n=17) and a follow-up interview round (n=9). Data were analyzed for consensus between participants and for stability between survey rounds. The interviews explored the reasons for answers given in the survey.

Results: The findings showed high stability between rounds on questions related to specific use cases but lower stability on questions relating to wider issues around the implementation of RMT. Overall, questions on wider issues also had less consensus. All 5 use cases for epilepsy (seizure alert, seizure counting, risk scoring, triage support, and trend analysis) were considered beneficial, with consensus among participants above the a priori threshold for most questions, although use case 3 (risk scoring) was considered less likely to facilitate or catalyze care. There was very little consensus on the benefits of the use cases in MS, although this may have resulted from a higher dropout rate of MS clinicians (50%). Participants agreed that there would be benefits for all 5 of the depression use cases, although fewer questions on use case 4 (triage support) reached consensus agreement than for depression use cases 1 (detecting trends), 2 (reviewing treatment), 3 (self-management), and 5 (carer alert). The qualitative analysis revealed further insights into each use case and generated 8 themes on practical issues related to implementation.

Conclusions: Overall, these findings inform the prioritization of use cases for RMT that could be developed in future work, which may include clinical trials, cost-effectiveness studies, and the commercial development of RMT products and services. Priorities for further development include the use of RMT to provide more accurate records of symptoms and treatment response than is currently possible and to provide data that could help inform patient triage and generate timely alerts for patients and carers.

Citation

Andrews, J. A., Craven, M. P., Guo, B., Weyer, J., Lees, S., Zormpas, S. I., …RADAR-CNS Consortium. (2023). Clinical Perspectives on Using Remote Measurement Technology in Assessing Epilepsy, Multiple Sclerosis, and Depression: Delphi Study. JMIR Neurotechnology, 2, Article e41439. https://doi.org/10.2196/41439

• Journal Article Type: Article
• Acceptance Date: Feb 24, 2023
• Online Publication Date: Apr 25, 2023
• Publication Date: 2023
• Deposit Date: Apr 25, 2023
• Publicly Available Date: Apr 27, 2023
• Journal: JMIR Neurotechnology
• Electronic ISSN: 2817-092X
• Publisher: JMIR Publications Inc.
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Article Number: e41439
• DOI: https://doi.org/10.2196/41439
• Keywords: mobile health; mHealth; wearable; wearable technology; smartphone; use case; implementation; epilepsy; multiple sclerosis; MS; depression; depressive disorder; Delphi; remote measurement technology; RMT; central nervous system; nervous system disorder; ne
• Public URL: https://nottingham-repository.worktribe.com/output/19997703
• Publisher URL: https://neuro.jmir.org/2023/1/e41439