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Lee HY, Lee KH, Lee KH, Erdenbayar U, Hwang S, Lee EY, Lee JH, Kim HJ, Park SB, Park JW, Chung TY, Kim TH, Youk H. Internet of medical things-based real-time digital health service for precision medicine: Empirical studies using MEDBIZ platform. Digit Health 2023; 9:20552076221149659. [PMID: 36644659 PMCID: PMC9834931 DOI: 10.1177/20552076221149659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023] Open
Abstract
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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Affiliation(s)
- Hee Young Lee
- Department of Emergency Medicine, Wonju College of Medicine, Yonsei
University, Wonju, Republic of Korea,Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea
| | - Kang Hyun Lee
- Department of Emergency Medicine, Wonju College of Medicine, Yonsei
University, Wonju, Republic of Korea
| | - Kyu Hee Lee
- Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea
| | - Urtnasan Erdenbayar
- Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea
| | - Sangwon Hwang
- Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea
| | - Eun Young Lee
- Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea
| | - Jung Hun Lee
- Department of Emergency Medicine, Wonju College of Medicine, Yonsei
University, Wonju, Republic of Korea
| | - Hee Jin Kim
- Department of Emergency Medicine, Wonju College of Medicine, Yonsei
University, Wonju, Republic of Korea
| | - Sung Bin Park
- Digital Healthcare Team, Corporate Support Division, Wonju Medical
Industry Technovalley, Wonju, Republic of Korea
| | - Joon Wook Park
- Digital Healthcare Team, Corporate Support Division, Wonju Medical
Industry Technovalley, Wonju, Republic of Korea
| | - Tae Yun Chung
- Open Platform Team, Platform Research Department, Gangwon Research
Institute of ICT Convergence, Wonju, Republic of Korea
| | - Tae Hyoung Kim
- Open Platform Team, Platform Research Department, Gangwon Research
Institute of ICT Convergence, Wonju, Republic of Korea
| | - Hyun Youk
- Department of Emergency Medicine, Wonju College of Medicine, Yonsei
University, Wonju, Republic of Korea,Artificial Intelligence Bigdata Medical Center, Wonju College of
Medicine, Yonsei University, Wonju, Republic of Korea,Hyun Youk, Department of Emergency
Medicine, Wonju College of Medicine, Yonsei University, 20 Ilsan-ro, Wonju
Severance Christian Hospital, Wonju, Gangwon, 26426, Republic of Korea.
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