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Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program. OBJECTIVE: The objective of this paper was to survey the curr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273236/ https://www.ncbi.nlm.nih.gov/pubmed/32348262 http://dx.doi.org/10.2196/16147 |
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author | Fan, Kathleen G Mandel, Jess Agnihotri, Parag Tai-Seale, Ming |
author_facet | Fan, Kathleen G Mandel, Jess Agnihotri, Parag Tai-Seale, Ming |
author_sort | Fan, Kathleen G |
collection | PubMed |
description | BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program. OBJECTIVE: The objective of this paper was to survey the current medical technologies for remote patient monitoring (RPM) tools that forecast COPD exacerbations in order to reduce COPD readmissions. METHODS: We searched literature and digital health news to find commercially available RPM devices focused on predicting COPD exacerbations. These technologies were reviewed and compared according to four criteria: forecasting ability, cost, ease of use, and appearance. A rating system was developed to facilitate the evaluation process. RESULTS: As of June 2019, a list of handheld and hands-free devices was compiled. We compared features and found substantial variations. Devices that ranked higher on all criteria tended to have a high or unlisted price. Commonly mass-marketed devices like the pulse oximeter and spirometer surprisingly fulfilled the least criteria. CONCLUSIONS: The COPD RPM technologies with most technological promise and compatibility with daily living appear to have high or unlisted prices. Consumers and providers need better access to product information to make informed decisions. |
format | Online Article Text |
id | pubmed-7273236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-72732362020-06-05 Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison Fan, Kathleen G Mandel, Jess Agnihotri, Parag Tai-Seale, Ming JMIR Mhealth Uhealth Original Paper BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program. OBJECTIVE: The objective of this paper was to survey the current medical technologies for remote patient monitoring (RPM) tools that forecast COPD exacerbations in order to reduce COPD readmissions. METHODS: We searched literature and digital health news to find commercially available RPM devices focused on predicting COPD exacerbations. These technologies were reviewed and compared according to four criteria: forecasting ability, cost, ease of use, and appearance. A rating system was developed to facilitate the evaluation process. RESULTS: As of June 2019, a list of handheld and hands-free devices was compiled. We compared features and found substantial variations. Devices that ranked higher on all criteria tended to have a high or unlisted price. Commonly mass-marketed devices like the pulse oximeter and spirometer surprisingly fulfilled the least criteria. CONCLUSIONS: The COPD RPM technologies with most technological promise and compatibility with daily living appear to have high or unlisted prices. Consumers and providers need better access to product information to make informed decisions. JMIR Publications 2020-05-21 /pmc/articles/PMC7273236/ /pubmed/32348262 http://dx.doi.org/10.2196/16147 Text en ©Kathleen G Fan, Jess Mandel, Parag Agnihotri, Ming Tai-Seale. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 21.05.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Fan, Kathleen G Mandel, Jess Agnihotri, Parag Tai-Seale, Ming Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title | Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title_full | Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title_fullStr | Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title_full_unstemmed | Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title_short | Remote Patient Monitoring Technologies for Predicting Chronic Obstructive Pulmonary Disease Exacerbations: Review and Comparison |
title_sort | remote patient monitoring technologies for predicting chronic obstructive pulmonary disease exacerbations: review and comparison |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273236/ https://www.ncbi.nlm.nih.gov/pubmed/32348262 http://dx.doi.org/10.2196/16147 |
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