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Medical Internet of Things and Big Data in Healthcare
OBJECTIVES: A number of technologies can reduce overall costs for the prevention or management of chronic illnesses. These include devices that constantly monitor health indicators, devices that auto-administer therapies, or devices that track real-time health data when a patient self-administers a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korean Society of Medical Informatics
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981575/ https://www.ncbi.nlm.nih.gov/pubmed/27525156 http://dx.doi.org/10.4258/hir.2016.22.3.156 |
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author | Dimitrov, Dimiter V. |
author_facet | Dimitrov, Dimiter V. |
author_sort | Dimitrov, Dimiter V. |
collection | PubMed |
description | OBJECTIVES: A number of technologies can reduce overall costs for the prevention or management of chronic illnesses. These include devices that constantly monitor health indicators, devices that auto-administer therapies, or devices that track real-time health data when a patient self-administers a therapy. Because they have increased access to high-speed Internet and smartphones, many patients have started to use mobile applications (apps) to manage various health needs. These devices and mobile apps are now increasingly used and integrated with telemedicine and telehealth via the medical Internet of Things (mIoT). This paper reviews mIoT and big data in healthcare fields. METHODS: mIoT is a critical piece of the digital transformation of healthcare, as it allows new business models to emerge and enables changes in work processes, productivity improvements, cost containment and enhanced customer experiences. RESULTS: Wearables and mobile apps today support fitness, health education, symptom tracking, and collaborative disease management and care coordination. All those platform analytics can raise the relevancy of data interpretations, reducing the amount of time that end users spend piecing together data outputs. Insights gained from big data analysis will drive the digital disruption of the healthcare world, business processes and real-time decision-making. CONCLUSIONS: A new category of "personalised preventative health coaches" (Digital Health Advisors) will emerge. These workers will possess the skills and the ability to interpret and understand health and well-being data. They will help their clients avoid chronic and diet-related illness, improve cognitive function, achieve improved mental health and achieve improved lifestyles overall. As the global population ages, such roles will become increasingly important. |
format | Online Article Text |
id | pubmed-4981575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-49815752016-08-12 Medical Internet of Things and Big Data in Healthcare Dimitrov, Dimiter V. Healthc Inform Res Review Article OBJECTIVES: A number of technologies can reduce overall costs for the prevention or management of chronic illnesses. These include devices that constantly monitor health indicators, devices that auto-administer therapies, or devices that track real-time health data when a patient self-administers a therapy. Because they have increased access to high-speed Internet and smartphones, many patients have started to use mobile applications (apps) to manage various health needs. These devices and mobile apps are now increasingly used and integrated with telemedicine and telehealth via the medical Internet of Things (mIoT). This paper reviews mIoT and big data in healthcare fields. METHODS: mIoT is a critical piece of the digital transformation of healthcare, as it allows new business models to emerge and enables changes in work processes, productivity improvements, cost containment and enhanced customer experiences. RESULTS: Wearables and mobile apps today support fitness, health education, symptom tracking, and collaborative disease management and care coordination. All those platform analytics can raise the relevancy of data interpretations, reducing the amount of time that end users spend piecing together data outputs. Insights gained from big data analysis will drive the digital disruption of the healthcare world, business processes and real-time decision-making. CONCLUSIONS: A new category of "personalised preventative health coaches" (Digital Health Advisors) will emerge. These workers will possess the skills and the ability to interpret and understand health and well-being data. They will help their clients avoid chronic and diet-related illness, improve cognitive function, achieve improved mental health and achieve improved lifestyles overall. As the global population ages, such roles will become increasingly important. Korean Society of Medical Informatics 2016-07 2016-07-31 /pmc/articles/PMC4981575/ /pubmed/27525156 http://dx.doi.org/10.4258/hir.2016.22.3.156 Text en © 2016 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Dimitrov, Dimiter V. Medical Internet of Things and Big Data in Healthcare |
title | Medical Internet of Things and Big Data in Healthcare |
title_full | Medical Internet of Things and Big Data in Healthcare |
title_fullStr | Medical Internet of Things and Big Data in Healthcare |
title_full_unstemmed | Medical Internet of Things and Big Data in Healthcare |
title_short | Medical Internet of Things and Big Data in Healthcare |
title_sort | medical internet of things and big data in healthcare |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981575/ https://www.ncbi.nlm.nih.gov/pubmed/27525156 http://dx.doi.org/10.4258/hir.2016.22.3.156 |
work_keys_str_mv | AT dimitrovdimiterv medicalinternetofthingsandbigdatainhealthcare |