In a health care context, remote measurement technologies (RMT) can be used by health care professionals (HCPs) and clinical teams to collect data on a patient’s health or behavior and use this to inform clinical decision making. The benefits of RMT have been explored in the management of patients with cardiac conditions [1-3], early stage dementia [4], neurological disease [5], and attention deficit hyperactivity disorder [6] as well as in behavior change [7] and monitoring for indicators of sepsis [8] among others.

The European Union H2020 Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) project [9] explores the use of RMT in the care of patients with epilepsy, depression, or multiple sclerosis (MS). These conditions were chosen for this project as exemplars of central nervous system disorders that are under-researched in relation to RMT. As part of this project, RADAR-base, a cloud-based platform, is being developed to explore the potential to receive data from patients’ RMT and to provide these data to HCPs with a view to informing clinical decision making [10]. This study is part of this project, aiming to understand the clinical utility of RMT in the care of patients with epilepsy, depression, or MS.

Previous literature has demonstrated the benefits of using RMT in health care practice. A 2013 literature review of the use of RMT in cardiology identified a number of studies demonstrating reduced hospital visits in terms of both emergency and routine appointments, as well as higher survival rates, in patients who were monitored using RMT [11]. Benefits were also found in patients’ relations with the care team, quality of life, and compliance with treatments. However, no quality appraisal was conducted in this narrative review.

Some studies have challenged these findings, suggesting little or no evidence of an effect of RMT on key outcomes [12,13]. Other work has highlighted a number of barriers to implementing RMT in health care practice. Erdmier et al [14] described a lack of regulatory control over wearables as well as a number of barriers to progress in implementation, including technical capability, erratic user (patient) behavior, and a lack of transparency from manufacturers. A patient and HCP-led priority setting exercise in the field of digital mental health highlighted the need to explore the impact of removing face-to-face human interaction in care pathways for mental health conditions, and raised issues of safety, effectiveness, evaluation, and inequalities [15]. These issues apply equally to the use of RMT.

Authors of prior work in the area of RMT highlighted a need for research to investigate the value to HCPs of implementing RMT [13]. Davis et al [16] conducted a systematic review of health care staffs’ views on the use of RMT in clinical practice and included 15 relevant studies. They concluded that “there is a critical need to engage end-users in the development and implementation of RMT” and highlighted that the evidence base in this area is small. This paper seeks to address these points by exploring HCPs’ perspectives on the implementation of RMT in three central nervous system disorders.

This study aims to understand the perspectives of HCPs on the use of RMT in health care practice for the care of patients with depression, epilepsy, or MS.

We purposively recruited a sample of 26 HCPs, with the intention of covering multiple clinical roles (with representation from medical, nursing, and allied health professionals). Participants were all working in the National Health Service (NHS) in England in the care of patients with epilepsy, depression, or MS or a combination of these conditions. Participants were contacted through the professional networks of the research team members.

A semistructured interview approach was used, with interviews lasting from 16 to 56 min (mean 30 min). An interview schedule was used to guide questioning, with ad hoc follow-up questions used to further explore salient points. Participants gave informed consent and were incentivized with a £15 (US $18) charity donation.

A total of 23 interviews were conducted one to one, whereas one interview was conducted with three participants together. Moreover, 13 interviews were conducted by phone, whereas 11 were conducted in person. All interviews were recorded from start to finish using a voice recorder. The study was approved by the University of Nottingham School of Medicine research ethics committee (ref 277-1802).

Interviews were transcribed verbatim and analyzed using thematic analysis [17]. Data were coded and themed (by JA) using NVivo 12 (QSR International). Initial codes and themes were discussed within the research team and were iteratively renamed and reformed throughout the analysis process. No new themes emerged when the last interview was coded, and so, it is considered that the sample reached data saturation.

Participants were HCPs (medical doctors, nurses, clinical psychologists, physiotherapists, and dietitians) from 13 NHS trusts (health care organizations) within England. Of the 26 participants, 8 (31%) were female. A total of 12 participants specialized in the care of patients with epilepsy, 6 in depression, 6 in MS, and 2 were general practitioners working across all 3 conditions. Participants included both primary and secondary care clinicians. Moreover, 13 of the 26 interviewees had used RMT with their patients, and 14 of the 26 said that their patients had brought data to appointments. The health care roles of the participants are presented in Table 1 along with their specialization and gender.

Our analysis generated 8 main themes, each of which also featured a number of subthemes.

A total of 8 themes emerged from the analysis of our interviews. The first theme covered the potential clinical value of the remote measurement data. Where RMT are currently used in health care practice, HCPs find them to be largely inaccurate, particularly in the case of epilepsy, although efforts to develop more effective ways of monitoring epilepsy are welcomed. Participants were optimistic about the future use of activity data to monitor symptoms of depression and considered that using RMT to collect measures of fatigue and cognition in patients with MS would be useful.

In theme 2, key points in care pathways for the 3 conditions were identified as times where RMT data could provide most value. These included monitoring a short period before an appointment (MS), monitoring during a change in treatment (epilepsy), and monitoring on a regular basis once a patient was in a stable condition, to allow assessment of follow-up and to create data for future research (depression, epilepsy, and MS).

The third theme considered staff roles in the management of RMT use by patients. Participants suggested that all staff involved in a patient’s care should have easy access to data generated by RMT via the patient record. Participants also made it clear that triage using data from RMT should be conducted by qualified HCPs rather than by administration staff. Primary care staff and specialist nurses in secondary care were thought to be well placed to manage incoming data from patients.

With regard to the presentation of data, in theme 4, HCPs described ease and speed of access to RMT data to be important for their successful use and emphasized the importance of interoperability with the patient record. Presentation of data in graphs was mentioned as helpful for interpretation.

Theme 5 discussed obstacles to the successful use of RMT, and these included both technical issues such as data accuracy and data security (where views differed on the risks involved) and human issues such as anxiety created by monitoring (although not all participants agreed that this was an issue).

In theme 6 on the limits of RMT benefit, participants emphasized that RMT would never completely replace face-to-face appointments, particularly in depression where relationships were considered important.

The seventh theme concerned patient empowerment. HCPs expressed the value in providing patients access to their own data, enabling them to take an active role in their own care, for example, by advancing appointments where RMT data indicated it was necessary. However, there was some concern about patients with depression having the motivation to take responsibility for their own care.

Theme 8 was related to alert-based systems. Participants debated the value of such systems and highlighted the requirements for their successful use. Some thought alerts should be used to invite the patient to take action rather than alerting a clinician, due to workload concerns. The need for further research to determine the benefits of alert-based systems was also highlighted.

Although prior work exploring RMT in health care has principally identified benefits and barriers to its implementation [11,14], this study has investigated HCPs’ perceptions of the clinical value of implementing RMT, helping to address the knowledge gap identified by Vegesna et al [13] and Davis et al [16].

The themes emerging in this study add to findings from prior work in this area. Our findings support the work of Bruno et al [18], who highlighted that HCPs may view the management of data from digital devices as a burden. Goodrich et al [19], among others, have highlighted the importance of interoperability and a preference for data from mobile technologies to be automatically integrated into clinical records, similar to the views of our participants. Clinicians’ concern about the need to respond to alert-based systems has also been raised previously [16,20].

Prior work has also emphasized the importance of face-to-face contact in the context of digital technology and mental health care [21]. A priority setting exercise for digital mental health [15] identified the need to explore the impact of removing such interactions from care pathways. Our data have shown that HCPs view face-to-face appointments as essential in the care of patients with these 3 conditions, even where RMT could provide them with detailed recent data on a patient’s status. Our data show that HCPs imagine patients could be empowered to determine their own need for a clinical appointment based on data from RMT, helping to address questions around the impact of technology on access to services, which has also been identified as a research priority [15].

Davis’ Technology Acceptance Model [22] describes perceived usefulness and perceived ease of use as key mediators to the successful uptake of a new technology. Our analysis highlights ways in which clinicians perceive RMT data could be useful (theme 1) as well as where there are limits or obstacles to this usefulness (themes 5 and 6). We have also identified how speed and ease of access to data are desirable for HCPs (theme 4), evidencing how perceived ease of use is applicable to this area. The analysis also raises the tailoring of care for patients using RMT (theme 7), where it was discussed that patients’ perception of RMT should be that it is both useful and easy to use to motivate continued use.

Beyond the findings presented in previous work, our findings specify the types of RMT data that clinicians would value in the management of epilepsy, depression, and MS as well as the points in patient care at which these data would be of most use and the health care roles that would be best placed to manage these data.

Findings from these themes will help to inform the development of the RADAR-CNS approach in the application of RMT for better care for epilepsy, MS, and depression. Researchers and companies developing monitoring technologies should ensure that the boundaries of accuracy of any new solution are well defined, such that clinicians can understand the level of confidence they should place in readings from such devices. As HCPs believe patients may benefit from the option to move or advance appointments based on their data, it would also be worthwhile for any mobile health solutions to link with appointment planning services, so that these can be easily accessed. In the United Kingdom, the NHS app is an example of such a system.

This study has several strengths. We recruited a multidisciplinary group of HCPs working in a variety of clinical staff roles in primary and secondary care. Therefore, the use of RMT was considered from multiple perspectives. The study was limited in its consideration of only three specific central nervous system disorders in one national health care system. However, the analysis has considered how insights gained from staff working in these three conditions might generalize and has permitted a deeper analysis of the three conditions mentioned. The ratio of male to female participants was high, with only 8 of 26 participants being female. Epilepsy staff were over-represented in comparison with depression and MS staff due to the convenience sampling method. However, staff were represented across most roles in the care team for each of the three conditions represented, with the exception of MS, where an MS nurse could not be recruited in the time available.

Although we have focused our consideration of the use of patient RMT data on an individual basis, further work could usefully explore the use of combined RMT data from groups of patients to assess risk or identify trends. The 2019 Topol Review highlighted the potential of integrating predictive analytics into diagnosis and care pathways [23], and data from RMT could feed into these approaches.

Future work should also explore the views of health service managers, commissioners, and public health representatives to understand the value that the implementation of RMT could provide from a health care system payer and management perspective, for example, in its potential to increase efficiencies and improve outcomes for different patient populations.

Given the participants’ views on the importance of nurses’ roles in the management of patients’ use of RMT, it would be useful to conduct further research to better understand nurses’ views on subsuming associated responsibilities into their roles. Although some work has explored nurses’ views on their roles in the use of technology in intensive care situations [24] and telehealth for diabetes [25], to our knowledge, no studies have explored views specifically relating to RMT in central nervous system disorders.

Further work should also be completed to understand how RMT might best facilitate increased patient autonomy (as advocated in the NHS Long Term Plan [26]) and situations where this may be less appropriate or successful. The remote assessment of disease and relapse-major depressive disorder study is recruiting 600 people with a major depressive disorder to use RMT over a period of 2 years, and this study may shed light in this area [27].

This paper has explored the views of HCPs on using RMT in managing central nervous system disorders, specifically epilepsy, MS, and depression. The results are as follows:

Our findings show the importance of early engagement and co-design with HCPs when considering user requirements and potential use cases before using RMT in clinical care pathways. HCPs believe that RMT data can add value to the care of patients with these three conditions but are not sufficient for decisions about care to be made exclusively on the basis of these data. We have demonstrated that clinicians are pragmatic about the data security risks of using RMT data with patients. Further research is required to establish how RMT data could be used on a population level to benefit patients with central nervous system disorders.