Patients’ and Clinicians’ Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed Methods Study

Bibliographic Details
Title: Patients’ and Clinicians’ Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed Methods Study
Authors: Hui, Chi Yan, McKinstry, Brian, Fulton, Olivia, Buchner, Mark, Pinnock, Hilary
Source: Journal of Medical Internet Research, Vol 23, Iss 4, p e22432 (2021)
Publisher Information: JMIR Publications, 2021.
Publication Year: 2021
Collection: LCC:Computer applications to medicine. Medical informatics
LCC:Public aspects of medicine
Subject Terms: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
More Details: BackgroundSupported self-management for asthma reduces acute attacks and improves control. The internet of things could connect patients to health care providers, community services, and their living environments to provide overarching support for self-management. ObjectiveWe aimed to identify patients’ and clinicians’ preferences for a future internet-of-things system and explore their visions of its potential to support holistic self-management. MethodsIn an exploratory sequential mixed methods study, we recruited patients from volunteer databases and charities’ social media. We purposively sampled participants to interview them about their vision of the design and utility of the internet of things as a future strategy for supporting self-management. Respondents who were not invited to participate in the interviews were invited to complete a web-based questionnaire to prioritize the features suggested by the interviewees. Clinicians were recruited from professional networks. Interviews were transcribed and analyzed thematically using PRISMS self-management taxonomy. ResultsWe interviewed 12 patients and 12 clinicians in the United Kingdom, and 140 patients completed the web-based questionnaires. Patients expressed mostly wanting a system to log their asthma control status automatically; provide real-time advice to help them learn about their asthma, identify and avoid triggers, and adjust their treatment. Peak flow (33/140, 23.6%), environmental (pollen, humidity, air temperature) (33/140, 23.6%), and asthma symptoms (25/140, 17.9%) were the specific data types that patient most wanted. Information about asthma and text or email access to clinical advice provided a feeling of safety for patients. Clinicians wanted automated objective data about the patients’ condition that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians which they perceived could potentially save patients’ travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients but were of less interest to clinicians. ConclusionsAn automated internet-of-things system that requires minimal input from the user and provides timely advice in line with an asthma action plan agreed by the patient with their clinician was preferred by most respondents. Links to asthma information and the ability to connect with clinicians by text or email were perceived by patients as features that would provide a sense of safety. Further studies are needed to evaluate the usability and effectiveness of internet-of-things systems in routine clinical practice.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1438-8871
Relation: https://www.jmir.org/2021/4/e22432; https://doaj.org/toc/1438-8871
DOI: 10.2196/22432
Access URL: https://doaj.org/article/cfe24e46f2f54894a2de325fbeea8dfc
Accession Number: edsdoj.fe24e46f2f54894a2de325fbeea8dfc
Database: Directory of Open Access Journals
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More Details
ISSN:14388871
DOI:10.2196/22432
Published in:Journal of Medical Internet Research
Language:English