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Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice

Authors :
Evan Minty
Emily Bray
Courtney B. Bachus
Breanne Everett
Karen M. Smith
Emily Matijevich
Maryam Hajizadeh
David G. Armstrong
Brock Liden
Source :
Sensors, Vol 23, Iss 15, p 6712 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Diabetes and its complications, particularly diabetic foot ulcers (DFUs), pose significant challenges to healthcare systems worldwide. DFUs result in severe consequences such as amputation, increased mortality rates, reduced mobility, and substantial healthcare costs. The majority of DFUs are preventable and treatable through early detection. Sensor-based remote patient monitoring (RPM) has been proposed as a possible solution to overcome limitations, and enhance the effectiveness, of existing foot care best practices. However, there are limited frameworks available on how to approach and act on data collected through sensor-based RPM in DFU prevention. This perspective article offers insights from deploying sensor-based RPM through digital DFU prevention regimens. We summarize the data domains and technical architecture that characterize existing commercially available solutions. We then highlight key elements for effective RPM integration based on these new data domains, including appropriate patient selection and the need for detailed clinical assessments to contextualize sensor data. Guidance on establishing escalation pathways for remotely monitored at-risk patients and the importance of predictive system management is provided. DFU prevention RPM should be integrated into a comprehensive disease management strategy to mitigate foot health concerns, reduce activity-associated risks, and thereby seek to be synergistic with other components of diabetes disease management. This integrated approach has the potential to enhance disease management in diabetes, positively impacting foot health and the healthspan of patients living with diabetes.

Details

Language :
English
ISSN :
14248220
Volume :
23
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.b7573e66bd9e4faf934a3f894a3fb804
Document Type :
article
Full Text :
https://doi.org/10.3390/s23156712