Health Care Professionals’ Views on Using Remote Measurement Technology in Managing Central Nervous System Disorders: Qualitative Interview Study

Abstract

Background Remote measurement technologies (RMT) can be used to collect data on a variety of bio-behavioral variables, which may improve the care of patients with central nervous system disorders. Although various studies have explored their potential, prior work has highlighted a knowledge gap in health care professionals’ (HCPs) perceptions of the value of RMT in clinical practice. Objective This study aims to understand HCPs’ perspectives on using RMT in health care practice for the care of patients with depression, epilepsy, or multiple sclerosis (MS). Methods Semistructured interviews were conducted with 26 multidisciplinary primary and secondary care HCPs who care for patients with epilepsy, depression, or MS. Interviews were transcribed verbatim and analyzed using thematic analysis. Results A total of 8 main themes emerged from the analysis: (1) potential clinical value of RMT data; (2) when to use RMT in care pathways; (3) roles of health care staff who may use RMT data; (4) presentation and accessibility of data; (5) obstacles to successful use of RMT; (6) limits to the role of RMT; (7) empowering patients; and (8) considerations around alert-based systems. Conclusions RMT could add value to the system of care for patients with central nervous system disorders by providing clinicians with graphic summaries of data in the patient record. Barriers of both technical and human nature should be considered when using these technologies, as should the limits to the benefits they can offer.

The impact of data from remote measurement technology on the clinical practice of healthcare professionals in depression, epilepsy and multiple sclerosis: survey

“…This study achieved its aim of eliciting views from a large sample of healthcare staff working in the care of patients with epilepsy, MS or depression. The results from this study have added to prior work in this area [ 19 , 20 ] by showing that smartphone apps are used by more than half (56%) of HCPs and that more than three quarters (78%) report that their patients use RMTs for health-related purposes. These figures are greater than in previous research studies that surveyed the use of apps in treatment by healthcare professionals working in epilepsy, where 45% of respondents previously reported using apps with their patients [ 28 ], and in depression, where 21.2% of respondents in a prior study stated they used apps in treatment for depression [ 25 ].…”

“…This may be because patients are more likely to discuss the data from devices they have bought themselves with primary care practitioners, who they see more regularly, and for whom relational aspects of their work are considered more important. While prior work in both Denmark [ 29 ] and the UK [ 20 ] has shown that general practitioners recognise benefits to patient use of wearables and apps, the present study has demonstrated more precisely how the attitudes of primary care professionals differ from those in other areas of care.…”

“…The consortium consists of a team of researchers, clinicians and a patient advisory board of individuals with lived experience of epilepsy, multiple sclerosis (MS), or depression ( www.radar-cns.org ). Project outputs to date have provided insight into the potential benefits of incorporating RMT in clinical pathways, via qualitative surveys of patients and healthcare professionals within the consortium [ 19 ] and interviews with HCPs outside the consortium [ 20 ]. In these small studies, HCPs and patients envisaged multiple ways that RMT could permit both ‘active’ (direct user input of data, such as mood diaries) and ‘passive’ (collection of data without the requirement of the user to input data, e.g.…”

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

“…In addition to this study, we have conducted further work with a wider community of health care professionals outside the RADAR-CNS consortium in the form of an interview study to gauge their views on the potential of RMT [ 33 ]. Whereas the interviews in the study by Andrews et al [ 33 ] aimed to elicit the types of data, specific time points, and job roles where RMT data would be used, the use of UPOC in this study asked participants to be more creative and imagine how particular processes could be differently managed with the use of RMT. Thus, responses in this study permitted capture of imagined scenarios of use for RMT at specific points of care, for example, how a change in treatment for MS might be enacted via a phone call and the platform used to monitor the effect.…”

Deep Learning for Mobile Mental Health: Challenges and recent advances

“…In general, traditional assessment largely relies on memory, due to lack of clear and objective bio-behavioural markers. In contrast, M2Health can add value to the formal clinical assessment of mental illness, by providing clinicians with summaries of the RMT data of the patient collected in a short period before an appointment [4]. Second, there have been a variety of M2health applications targeted at different stages, from prevention and assessment to intervention and treatment [5], [6].…”