Bath, P. orcid.org/0000-0002-6310-7396, Basholli, A. orcid.org/0000-0002-2893-1830, Lagkas, T. orcid.org/0000-0002-0749-9794 et al. (1 more author) (2021) Sensor-based platforms for remote management of chronic diseases in developing regions: a qualitative approach examining the perspectives of healthcare professionals. Health Informatics Journal, 27 (1). ISSN 1460-4582
Abstract
The continuous monitoring of chronic diseases serves as one of the cornerstones in the efforts to improve the quality of life of patients and maintain the healthcare services provided to them. This study aims to provide an in-depth understanding of the perspectives of healthcare professionals on using sensor-based networks (SBN) used for remote and continuous monitoring of patients with chronic illness in Kosovo, a developing country. A qualitative research method was used to interview 26 healthcare professionals. The study results demonstrate the positive attitudes of participants to using SBN, and considers their concerns on the impact of these platforms on the patient’s life, the number of visits in the medical centre, data privacy concerning interactions between patients and their medical personnel and the costs of the platform. Further to that, the study makes an important contribution to knowledge by identifying the challenges and drawbacks of these platforms and provides recommendations for system designers.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s). This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | e-health; medical information; sensor-based platforms; qualitative study; vital sign monitoring |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) The University of Sheffield > International Faculty (Sheffield) > City College - Computer Science |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 09 Feb 2021 15:17 |
Last Modified: | 06 Jun 2024 10:46 |
Status: | Published |
Publisher: | SAGE Publications (UK and US) |
Refereed: | Yes |
Identification Number: | 10.1177/1460458220979350 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:170021 |