BACKGROUND: Despite the increasing use of remote measurement technologies (RMT) such as wearables or biosensors in health care programs, challenges associated with selecting and implementing these technologies persist. Many health care programs that use RMT rely on commercially available, "off-the-shelf" devices to collect patient data. However, validation of these devices is sparse, the technology landscape is constantly changing, relative benefits between device options are often unclear, and research on patient and health care provider preferences is often lacking. OBJECTIVE: To address these common challenges, we propose a novel device selection framework extrapolated from human-centered design principles, which are commonly used in de novo digital health product design. We then present a case study in which we used the framework to identify, test, select, and implement off-the-shelf devices for the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) consortium, a research program using RMT to study central nervous system disease progression. METHODS: The RADAR-CNS device selection framework describes a human-centered approach to device selection for mobile health programs. The framework guides study designers through stakeholder engagement, technology landscaping, rapid proof of concept testing, and creative problem solving to develop device selection criteria and a robust implementation strategy. It also describes a method for considering compromises when tensions between stakeholder needs occur. RESULTS: The framework successfully guided device selection for the RADAR-CNS study on relapse in multiple sclerosis. In the initial stage, we engaged a multidisciplinary team of patients, health care professionals, researchers, and technologists to identify our primary device-related goals. We desired regular home-based measurements of gait, balance, fatigue, heart rate, and sleep over the course of the study. However, devices and measurement methods had to be user friendly, secure, and able to produce high quality data. In the second stage, we iteratively refined our strategy and selected devices based on technological and regulatory constraints, user feedback, and research goals. At several points, we used this method to devise compromises that addressed conflicting stakeholder needs. We then implemented a feedback mechanism into the study to gather lessons about devices to improve future versions of the RADAR-CNS program. CONCLUSIONS: The RADAR device selection framework provides a structured yet flexible approach to device selection for health care programs and can be used to systematically approach complex decisions that require teams to consider patient experiences alongside scientific priorities and logistical, technical, or regulatory constraints.
- MeSH
- lidé MeSH
- technologie MeSH
- telemedicína * MeSH
- zdravotnický personál MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Smartphone apps and wearable devices could augment clinical practice by detecting changes in health status for multiple sclerosis (MS). This study sought to investigate potential barriers and facilitators for uptake and sustained use in (i) people with both relapsing remitting MS (RRMS) and progressive MS (PMS) and (ii) across different countries. METHODS: Twenty four participants with MS took part in four focus groups held in three countries (2 in the UK, 1 in Spain, and 1 in Italy) to investigate potential barriers and facilitators for mHealth technology. A systematic thematic analysis was used to extract themes and sub-themes. RESULTS: Facilitators and barriers were organised into functional technology-related factors and non-functional health-related and user-related factors. Twelve themes captured all requirements across the three countries for both RRMS and PMS. Key requirements included accommodation for varying physical abilities, providing information and memory aids. Potential negative effects on mood and providing choice and control as part of overcoming practical challenges were identified. CONCLUSIONS: We took a cross-national perspective and found many similarities between three European countries across people with RRMS and PMS. Future provision should accommodate the key requirements identified to engage people with MS in scalable mHealth interventions.
- MeSH
- dospělí MeSH
- kulturní různorodost * MeSH
- lidé středního věku MeSH
- lidé MeSH
- management nemoci * MeSH
- progrese nemoci * MeSH
- průřezové studie MeSH
- relabující-remitující roztroušená skleróza diagnóza etnologie psychologie MeSH
- roztroušená skleróza diagnóza etnologie psychologie MeSH
- telemedicína metody MeSH
- zjišťování skupinových postojů MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Itálie MeSH
- Španělsko MeSH
- Spojené království MeSH