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A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers–some of which have been shown to lead to improved health manage...

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Autores principales: Bloss, Cinnamon S., Wineinger, Nathan E., Peters, Melissa, Boeldt, Debra L., Ariniello, Lauren, Kim, Ju Young, Sheard, Judith, Komatireddy, Ravi, Barrett, Paddy, Topol, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4715435/
https://www.ncbi.nlm.nih.gov/pubmed/26788432
http://dx.doi.org/10.7717/peerj.1554
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author Bloss, Cinnamon S.
Wineinger, Nathan E.
Peters, Melissa
Boeldt, Debra L.
Ariniello, Lauren
Kim, Ju Young
Sheard, Judith
Komatireddy, Ravi
Barrett, Paddy
Topol, Eric J.
author_facet Bloss, Cinnamon S.
Wineinger, Nathan E.
Peters, Melissa
Boeldt, Debra L.
Ariniello, Lauren
Kim, Ju Young
Sheard, Judith
Komatireddy, Ravi
Barrett, Paddy
Topol, Eric J.
author_sort Bloss, Cinnamon S.
collection PubMed
description Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers–some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program–making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.
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spelling pubmed-47154352016-01-19 A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors Bloss, Cinnamon S. Wineinger, Nathan E. Peters, Melissa Boeldt, Debra L. Ariniello, Lauren Kim, Ju Young Sheard, Judith Komatireddy, Ravi Barrett, Paddy Topol, Eric J. PeerJ Clinical Trials Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers–some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program–making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group. PeerJ Inc. 2016-01-14 /pmc/articles/PMC4715435/ /pubmed/26788432 http://dx.doi.org/10.7717/peerj.1554 Text en © 2016 Bloss et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Clinical Trials
Bloss, Cinnamon S.
Wineinger, Nathan E.
Peters, Melissa
Boeldt, Debra L.
Ariniello, Lauren
Kim, Ju Young
Sheard, Judith
Komatireddy, Ravi
Barrett, Paddy
Topol, Eric J.
A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title_full A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title_fullStr A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title_full_unstemmed A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title_short A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
title_sort prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
topic Clinical Trials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4715435/
https://www.ncbi.nlm.nih.gov/pubmed/26788432
http://dx.doi.org/10.7717/peerj.1554
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