Mobile Health Technologies for Diabetes Mellitus: Current State and Future Challenges

被引:18
|
作者
El-Sappagh, Shaker [1 ,2 ]
Ali, Farman [2 ]
El-Masri, Samir [3 ]
Kim, Kyehyun [4 ]
Ali, Amjad [2 ,5 ]
Kwak, Kyung-Sup [2 ]
机构
[1] Benha Univ, Informat Syst Dept, Fac Comp & Informat, Banha 13518, Egypt
[2] Inha Univ, Dept Informat & Commun Engn, Incheon 22212, South Korea
[3] Sharjah Media City, Digitalizat, Sharjah, U Arab Emirates
[4] Inha Univ, Dept Geoinformat Engn, Incheon 22212, South Korea
[5] COMSATS Inst Informat Technol, Dept Comp Sci, Lahore 54000, Pakistan
来源
IEEE ACCESS | 2019年 / 7卷
基金
新加坡国家研究基金会;
关键词
Mobile health; diabetes mellitus; electronic health record; cloud computing; clinical decision support system; big data analytics; wireless body area network; medical informatics; CLINICAL DECISION-SUPPORT; ONTOLOGY-BASED APPROACH; BIG DATA; SEMANTIC INTEROPERABILITY; SELF-MANAGEMENT; CHRONIC DISEASE; GLYCEMIC CONTROL; CLOUD; CARE; SYSTEM;
D O I
10.1109/ACCESS.2018.2881001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The prevalence of diabetes is rising globally. Diabetes patients need continuous monitoring, and to achieve this objective, they have to be engaged in their healthcare management process. Mobile health (MH) is an information and communications technology trend to empower chronically ill patients in a smart environment. Discussing the current state of MH technologies is required in order to address their limitations. Existing review articles have evaluated the MH literature based on applicability and level of adoption by patients and healthcare providers. Most of these reviews asserted that MH apps and research have not reached a stable level yet. To the best of our knowledge, there is no clear description of solutions to these problems. In addition, no one has investigated and analyzed MH in its contextual environment in a detailed way. We conducted a comprehensive survey of MH research on diabetes management articles published between 2011 and September 27, 2017. In this survey, we discuss current challenges in MH, along with research gaps, opportunities, and trends. Our literature review searched three academic databases (ScienceDirect, IEEE Xplore, and SpringerLink). A total of 60 articles were analyzed, with 30% from ScienceDirect, 38% from IEEE Xplore, and 32% from SpringerLink. MH was analyzed in the context of the electronic health record (EHR) ecosystem. We consider dimensions such as clinical decision support systems, EHRs, cloud computing, semantic interoperability, wireless body area networks, and big data analytics. We propose specific metrics to analyze and evaluate MH from each of these dimensions. A comprehensive analysis of the literature from this viewpoint is valuable for both theoretical and developmental progress. This paper provides a critical analysis of challenges that have not been fully met and highlights directions for future research that could improve MH applicability.
引用
收藏
页码:21917 / 21947
页数:31
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