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Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform

The aim of this study was to introduce the implemented MEDBIZ platform based on the internet of medical things (IoMT) supporting real-time digital health services for precision medicine. In addition, we demonstrated four empirical studies of the digital health ecosystem that could provide real-time...

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Autores principales: Lee, Hee Young, Lee, Kang Hyun, Lee, Kyu Hee, Erdenbayar, Urtnasan, Hwang, Sangwon, Lee, Eun Young, Lee, Jung Hun, Kim, Hee Jin, Park, Sung Bin, Park, Joon Wook, Chung, Tae Yun, Kim, Tae Hyoung, Youk, Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9834931/
https://www.ncbi.nlm.nih.gov/pubmed/36644659
http://dx.doi.org/10.1177/20552076221149659
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author Lee, Hee Young
Lee, Kang Hyun
Lee, Kyu Hee
Erdenbayar, Urtnasan
Hwang, Sangwon
Lee, Eun Young
Lee, Jung Hun
Kim, Hee Jin
Park, Sung Bin
Park, Joon Wook
Chung, Tae Yun
Kim, Tae Hyoung
Youk, Hyun
author_facet Lee, Hee Young
Lee, Kang Hyun
Lee, Kyu Hee
Erdenbayar, Urtnasan
Hwang, Sangwon
Lee, Eun Young
Lee, Jung Hun
Kim, Hee Jin
Park, Sung Bin
Park, Joon Wook
Chung, Tae Yun
Kim, Tae Hyoung
Youk, Hyun
author_sort Lee, Hee Young
collection PubMed
description The aim of this study was to introduce the implemented MEDBIZ platform based on the internet of medical things (IoMT) supporting real-time digital health services for precision medicine. In addition, we demonstrated four empirical studies of the digital health ecosystem that could provide real-time healthcare services based on IoMT using real-world data from in-hospital and out-hospital patients. Implemented MEDBIZ platform based on the IoMT devices and big data to provide digital healthcare services to the enterprise and users. The big data platform is consisting of four main components: IoMT, core, analytics, and services. Among the implemented MEDBIZ platform, we performed four clinical trials that designed monitoring services related to chronic obstructive pulmonary disease, metabolic syndrome, arrhythmia, and diabetes mellitus. Of the four empirical studies on monitoring services, two had been completed and the rest were still in progress. In the metabolic syndrome monitoring service, two studies were reported. One was reported that intervention components, especially wearable devices and mobile apps, made systolic blood pressure, diastolic blood pressure, waist circumference, and glycosylated hemoglobin decrease after 6 months. Another one was presented that increasing high-density lipoprotein cholesterol and triglyceride levels were prevented in participants with the pre-metabolic syndrome. Also, self-care using healthcare devices might help prevent and manage metabolic syndrome. In the arrhythmia monitoring service, during the real-time monitoring of vital signs remotely at the monitoring center, 318 (15.9%) general hikers found abnormal signals, and 296 (93.1%) people were recommended for treatment. We demonstrated the implemented MEDBIZ platform based on IoMT supporting digital healthcare services by acquiring real-world data for getting real-world evidence. And then through this platform, we were developing software as a medical device, digital therapeutics, and digital healthcare services, and contributing to the development of the digital health ecosystem.
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spelling pubmed-98349312023-01-13 Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform Lee, Hee Young Lee, Kang Hyun Lee, Kyu Hee Erdenbayar, Urtnasan Hwang, Sangwon Lee, Eun Young Lee, Jung Hun Kim, Hee Jin Park, Sung Bin Park, Joon Wook Chung, Tae Yun Kim, Tae Hyoung Youk, Hyun Digit Health Original Research The aim of this study was to introduce the implemented MEDBIZ platform based on the internet of medical things (IoMT) supporting real-time digital health services for precision medicine. In addition, we demonstrated four empirical studies of the digital health ecosystem that could provide real-time healthcare services based on IoMT using real-world data from in-hospital and out-hospital patients. Implemented MEDBIZ platform based on the IoMT devices and big data to provide digital healthcare services to the enterprise and users. The big data platform is consisting of four main components: IoMT, core, analytics, and services. Among the implemented MEDBIZ platform, we performed four clinical trials that designed monitoring services related to chronic obstructive pulmonary disease, metabolic syndrome, arrhythmia, and diabetes mellitus. Of the four empirical studies on monitoring services, two had been completed and the rest were still in progress. In the metabolic syndrome monitoring service, two studies were reported. One was reported that intervention components, especially wearable devices and mobile apps, made systolic blood pressure, diastolic blood pressure, waist circumference, and glycosylated hemoglobin decrease after 6 months. Another one was presented that increasing high-density lipoprotein cholesterol and triglyceride levels were prevented in participants with the pre-metabolic syndrome. Also, self-care using healthcare devices might help prevent and manage metabolic syndrome. In the arrhythmia monitoring service, during the real-time monitoring of vital signs remotely at the monitoring center, 318 (15.9%) general hikers found abnormal signals, and 296 (93.1%) people were recommended for treatment. We demonstrated the implemented MEDBIZ platform based on IoMT supporting digital healthcare services by acquiring real-world data for getting real-world evidence. And then through this platform, we were developing software as a medical device, digital therapeutics, and digital healthcare services, and contributing to the development of the digital health ecosystem. SAGE Publications 2023-01-09 /pmc/articles/PMC9834931/ /pubmed/36644659 http://dx.doi.org/10.1177/20552076221149659 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Lee, Hee Young
Lee, Kang Hyun
Lee, Kyu Hee
Erdenbayar, Urtnasan
Hwang, Sangwon
Lee, Eun Young
Lee, Jung Hun
Kim, Hee Jin
Park, Sung Bin
Park, Joon Wook
Chung, Tae Yun
Kim, Tae Hyoung
Youk, Hyun
Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title_full Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title_fullStr Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title_full_unstemmed Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title_short Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform
title_sort internet of medical things-based real-time digital health service for precision medicine: empirical studies using medbiz platform
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9834931/
https://www.ncbi.nlm.nih.gov/pubmed/36644659
http://dx.doi.org/10.1177/20552076221149659
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