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

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 preven...

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Autores principales: Minty, Evan, Bray, Emily, Bachus, Courtney B., Everett, Breanne, Smith, Karen M., Matijevich, Emily, Hajizadeh, Maryam, Armstrong, David G., Liden, Brock
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422561/
https://www.ncbi.nlm.nih.gov/pubmed/37571496
http://dx.doi.org/10.3390/s23156712
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author Minty, Evan
Bray, Emily
Bachus, Courtney B.
Everett, Breanne
Smith, Karen M.
Matijevich, Emily
Hajizadeh, Maryam
Armstrong, David G.
Liden, Brock
author_facet Minty, Evan
Bray, Emily
Bachus, Courtney B.
Everett, Breanne
Smith, Karen M.
Matijevich, Emily
Hajizadeh, Maryam
Armstrong, David G.
Liden, Brock
author_sort Minty, Evan
collection PubMed
description 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.
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spelling pubmed-104225612023-08-13 Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice Minty, Evan Bray, Emily Bachus, Courtney B. Everett, Breanne Smith, Karen M. Matijevich, Emily Hajizadeh, Maryam Armstrong, David G. Liden, Brock Sensors (Basel) Perspective 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. MDPI 2023-07-27 /pmc/articles/PMC10422561/ /pubmed/37571496 http://dx.doi.org/10.3390/s23156712 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
Minty, Evan
Bray, Emily
Bachus, Courtney B.
Everett, Breanne
Smith, Karen M.
Matijevich, Emily
Hajizadeh, Maryam
Armstrong, David G.
Liden, Brock
Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title_full Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title_fullStr Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title_full_unstemmed Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title_short Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice
title_sort preventative sensor-based remote monitoring of the diabetic foot in clinical practice
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422561/
https://www.ncbi.nlm.nih.gov/pubmed/37571496
http://dx.doi.org/10.3390/s23156712
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