Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jul 11, 2020
Date Accepted: Feb 15, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Patients and clinicians’ vision of a future Internet-of-things (IoT) systems to support asthma self-management: a mixed method study from the A4A+ group
ABSTRACT
Background:
Supported self-management for asthma reduces acute attacks and improves control. The Internet-of-Things (IoT) could connect patients to their healthcare providers, the community services and their living environment to provide over-arching support for self-management.
Objective:
We aimed to identify patients’ and clinicians’ preferences for a future IoT system and explore their vision of its potential to support holistic self-management.
Methods:
We recruited patients from volunteer databases and charities’ social media. We purposively sampled participants for interviews about their vision of the design and utility of the IoT as a future strategy for supporting self-management; other respondents completed an online questionnaire about the features they wanted. Clinicians were recruited from professional networks. Interviews were transcribed and analysed thematically with reference to the PRISMS self-management taxonomy.
Results:
We interviewed twelve patients and twelve clinicians in the UK. 140 patients completed the questionnaires. Patients mostly wanted the system to log their asthma automatically and provide real-time advice to help them learn about their asthma, identify and avoid triggers and to advise on treatment adjustment and other actions. Peak flow (23.6%), environmental (pollen, humidity/air temperature) (23.6%), and asthma symptoms (17.9%) were the top three data types that patients most wanted. Information about asthma and text/email access to clinical advice, provided a feeling of ‘safety’ for patients. Clinicians wanted automated, objective logs about patients’ conditions that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians, potentially saving patients’ travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients, though of less interest to clinicians.
Conclusions:
An IoT system can address the range of components needed to support self-management for people with asthma. An automated IoT system requiring minimal input from the user could improve health outcomes and potentially conserve healthcare resources.
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