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Informing the Development of a Digital Health Platform Through Universal Points of Care: Qualitative Survey Study

Craven, Michael P.; Andrews, Jacob; Lang, Alexandra R; Simblett, Sara K; Bruce, Stuart; Thorpe, Sarah; Wykes, Til; Morriss, Richard; Hollis, Chris; The RADAR-CNS Consortium

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Authors

JACOB ANDREWS JACOB.ANDREWS@NOTTINGHAM.AC.UK
Industry Engagement Manager: mental Heal

Sara K Simblett

Stuart Bruce

Sarah Thorpe

Til Wykes

RICHARD MORRISS richard.morriss@nottingham.ac.uk
Professor of Psychiatry and Community Mental Health

CHRIS HOLLIS chris.hollis@nottingham.ac.uk
Professor of Child and Adolescent Psychiatry and Digital Mental Health

The RADAR-CNS Consortium



Abstract

Background: Epilepsy, multiple sclerosis (MS), and depression are chronic conditions where technology holds potential in clinical monitoring and self-management. Over 5 years, the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) consortium has explored the application of remote measurement technology (RMT) to the management and self-management of patients in these clinical areas. The consortium is large and includes clinical and nonclinical researchers as well as a patient advisory board. Objective: This formative development study aimed to understand how consortium members viewed the potential of RMT in epilepsy, MS, and depression. Methods: In this qualitative survey study, we developed a methodological tool, universal points of care (UPOC), to gather views on the potential use, acceptance, and value of a novel RMT platform across 3 chronic conditions (MS, epilepsy, and depression). UPOC builds upon use case scenario methodology, using expert elicitation and analysis of care pathways to develop scenarios applicable across multiple conditions. After developing scenarios, we elicited views on the potential of RMT in these different scenarios through a survey administered to 28 subject matter experts, consisting of 16 health care practitioners; 5 health care services researchers; and 7 people with lived experience of MS, epilepsy, or depression. Survey results were analyzed thematically and using an existing framework of factors describing links between design and context. Results: The survey elicited potential beneficial applications of the RADAR-CNS RMT system as well as patient, clinical, and nonclinical requirements of RMT across the 3 conditions of interest. Potential applications included recognition of early warning signs of relapse from subclinical signals for MS, seizure precipitant signals for epilepsy, and behavior change in depression. RMT was also thought to have the potential to overcome the problem of underreporting, which is especially problematic in epilepsy, and to allow the capture of secondary symptoms that are not generally collected in MS, such as mood. Conclusions: Respondents suggested novel and unanticipated uses of RMT, including the use of RMT to detect emerging side effects of treatment, enable behavior change for sleep regulation and activity, and offer a way to include family and other carers in a care network, which could assist with goal setting. These suggestions, together with others from this and related work, will inform the development of the system for its eventual application in research and clinical practice. The UPOC methodology was effective in directing respondents to consider the value of health care technologies in condition-specific experiences of everyday life and working practice.

Citation

Craven, M. P., Andrews, J., Lang, A. R., Simblett, S. K., Bruce, S., Thorpe, S., …The RADAR-CNS Consortium. (2020). Informing the Development of a Digital Health Platform Through Universal Points of Care: Qualitative Survey Study. JMIR Formative Research, 4(11), Article e22756. https://doi.org/10.2196/22756

Journal Article Type Article
Acceptance Date Sep 30, 2020
Online Publication Date Nov 26, 2020
Publication Date Nov 26, 2020
Deposit Date Oct 1, 2020
Publicly Available Date Nov 30, 2020
Journal JMIR Formative Research
Electronic ISSN 2561-326X
Peer Reviewed Peer Reviewed
Volume 4
Issue 11
Article Number e22756
DOI https://doi.org/10.2196/22756
Keywords epilepsy; multiple sclerosis; depression; wearable electronic devices; remote sensing technology; health personnel; mobile phones; mHealth; eHealth
Public URL https://nottingham-repository.worktribe.com/output/4799537
Publisher URL https://formative.jmir.org/2020/11/e22756/

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