Data-driven digital health technologies in the remote clinical care of diabetic foot ulcers: a scoping review

Frontiers in Clinical Diabetes and Healthcare

Clinical Diabetes and Healthcare

Ezio Preatoni¹  Benjamin Metcalfe²  Prasad Nishtala³  David Gurevich⁴  Lisa Kreusser⁵  Iulia Cioroianu⁶  Tamsin H. Sharp⁷  Joel Lazarus⁸  Beate Ehrhardt⁹ 

[1] Department for Health, Faculty of Humanities and Social Sciences, University of Bath, Bath, United Kingdom;Department of Electronic and Electrical Engineering, Faculty of Science, University of Bath, Bath, United Kingdom;Department of Life Sciences, Faculty of Engineering and Design, University of Bath, Bath, United Kingdom;Department of Life Sciences, University of Bath, Bath, United Kingdom;Department of Mathematical Sciences, Faculty of Science, University of Bath, Bath, United Kingdom;Department of Politics, Languages and International Studies, Faculty of Humanities and Social Sciences, University of Bath, Bath, United Kingdom;Department of Psychology, Faculty of Humanities and Social Sciences, University of Bath, Bath, United Kingdom;Department of Social and Policy Studies, University of Bath, Bath, United Kingdom;Institute for Mathematical Innovation, Languages and International Studies, Faculty of Humanities and Social Sciences, University of Bath, Bath, United Kingdom;

关键词: digital health;    data science;    machine learning;    wearable sensors;    remote monitoring;    telemedicine;    diabetes;    diabetic foot ulcers;   

DOI  :  10.3389/fcdhc.2023.1212182

 received in 2023-04-26, accepted in 2023-07-31,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundThe availability and effectiveness of Digital Health Technologies (DHTs) to support clinicians, empower patients, and generate economic savings for national healthcare systems are growing rapidly. Of particular promise is the capacity of DHTs to autonomously facilitate remote monitoring and treatment. Diabetic Foot Ulcers (DFUs) are characterised by high rates of infection, amputation, mortality, and healthcare costs. With clinical outcomes contingent on activities that can be readily monitored, DFUs present a promising focus for the application of remote DHTs.ObjectiveThis scoping review has been conducted as a first step toward ascertaining fthe data-related challenges and opportunities for the development of more comprehensive, integrated, and individualised sense/act DHTs. We review the latest developments in the application of DHTs to the remote care of DFUs. We cover the types of DHTs in development and their features, technological readiness, and scope of clinical testing.Eligibility criteriaOnly peer-reviewed original experimental and observational studies, case series and qualitative studies were included in literature searches. All reviews and manuscripts presenting pre-trial prototype technologies were excluded.MethodsAn initial search of three databases (Web of Science, MEDLINE, and Scopus) generated 1,925 English-language papers for screening. 388 papers were assessed as eligible for full-text screening by the review team. 81 manuscripts were found to meet the eligibility criteria.ResultsOnly 19% of studies incorporated multiple DHTs. We categorised 56% of studies as ‘Treatment-Manual’, i.e. studies involving technologies aimed at treatment requiring manual data generation, and 26% as ‘Prevention-Autonomous’, i.e. studies of technologies generating data autonomously through wearable sensors aimed at ulcer prevention through patient behavioural change. Only 10% of studies involved more ambitious ‘Treatment-Autonomous’ interventions. We found that studies generally reported high levels of patient adherence and satisfaction.ConclusionsOur findings point to a major potential role for DHTs in remote personalised medical management of DFUs. However, larger studies are required to assess their impact. Here, we see opportunities for developing much larger, more comprehensive, and integrated monitoring and decision support systems with the potential to address the disease in a more complete context by capturing and integrating data from multiple sources from subjective and objective measurements.

【 授权许可】

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Copyright © 2023 Lazarus, Cioroianu, Ehrhardt, Gurevich, Kreusser, Metcalfe, Nishtala, Preatoni and Sharp