In the case of depression, people experience periods of low mood, low motivation, lack of interest, excessive/insufficient sleep, poor/excessive appetite, and tiredness.

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The management of these diseases associated with the brain involves repeated contact with healthcare professionals (HCPs), in which the patient’s symptoms are assessed and any treatment they are receiving is reviewed.

While evaluating there is poor accuracy of patient records, and measuring mental states over long periods may be affected by present mental state. In some cases, changes in their condition that they have noticed in the standard tests offered at the clinic may go unnoticed.

In this scenario, remote measurement technology (RMT) may offer a way to improve upon existing methods of managing these three conditions. It consists of smartphone applications and wearables to record data that may provide information about a patient’s condition.

Now, research has begun to explore the potential of these technologies in monitoring depression, detecting seizures in epilepsy, and assessing multiple sclerosis functionally.

Will Remote Technology Fit Into Clinical Pathway?

Over 6 years, the RADAR-CNS (Remote Assessment of Disease and Relapse – Central Nervous System) project investigated the utility of RMT in the care of patients with epilepsy, MS or depression.

It included large-scale observational studies using RMT to collect passive and active data from patients with each of the conditions in the home (MS, epilepsy, depression) and hospital (epilepsy) settings.

Researchers also did a prior interview study where healthcare professionals indicated multiple types of data that could be collected using RMT which would be useful in the management of patients with epilepsy, MS, or depression.

Initial findings from the first half of this survey showed that the use of smartphones for clinical purposes is widespread among clinicians (60%) and that the majority of respondents (76%) had the experience of treating patients who are using data from wearable devices ().

These findings also showed that RMT data would be useful at specific times, including initial referral; after any changes in treatment; and before routine appointments, once the condition was stable.

Healthcare professionals think that it is very essential for primary care teams, specialist nurses, and all clinical, but not administrative members of a team, should have access to RMT data from patients preferably via the electronic patient record.

Other prior research exploring clinicians’ experiences of RMT has shown that the data can enable clinicians to delegate tasks to suitably qualified but more junior staff, reducing their workload ().

Limitations in Using Wearable Devices

However, in the specific case of epilepsy, healthcare professionals have suggested that RMT may increase workload and may cause increased patient anxiety.

In the area of mental health, clinicians have put forward concerns about the reliability and accuracy of sleep and mood tracking apps, although they recognize their potential in facilitating the collection of routine data.

Clinicians treating multiple sclerosis have commented on the potential to collect more in-depth data from patients using wearable devices than can be collected in the clinic.

However, it has been proposed that several fundamental changes will be required for clinicians to integrate remote measurement technology into their work, including the set-up of virtual offices from which clinicians can operate, and a shift toward continuity of data exchange and connection between patients and their clinical team.

Despite this need for important changes in the way clinicians work to implement RMT, no research has explored the views of healthcare professionals on the practical requirements.

This project gave only a brief insight into the potential value of RMT data in clinical pathways and laid the base for future development of AI technologies to assess and improve patient care within practical settings such as clinics.

References :

1. Making remote measurement technology work in multiple sclerosis, epilepsy and depression: survey of healthcare professionals – (https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-01856-z#Sec11)
2. Sudden unexpected death in epilepsy: Assessing the public health burden – (https://onlinelibrary.wiley.com/doi/10.1111/epi.12666)
3. Our results, insights and achievements – (https://www.radar-cns.org/latest-results)
4. Digital health tools for the passive monitoring of depression: a systematic review of methods – (https://www.nature.com/articles/s41746-021-00548-8)

Source: Medindia