An Investigation into Usability of Big Data Analytics in the Management of Type 2 Diabetes Mellitus
An Investigation into Usability of Big Data Analytics in the Management of Type 2 Diabetes Mellitus
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大数据分析在 2 型糖尿病管理中的可用性调查
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
D. Krishnan
中科院分区：
文献类型：
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作者：
Dinakar Bhotta;A. Baig;R. Gururajan;Subrata Chakraborty;Srinivas Phani Kavuri;D. Krishnan
在过去的40年里，全球2型糖尿病(T2 DM)的患病率一直在上升，预计未来还会进一步上升。人工智能(AI)和机器学习(ML)等大数据应用程序越来越多地被用于医疗行业，以管理患者护理的各个方面。到目前为止，研究人员使用信息系统(IS)领域的技术采用框架研究了包括AI和ML在内的技术在各种环境中的采用，在IS领域，技术的可用性仅被视为一个因素。尽管IS领域的技术采用模型研究表明，可用性对一项技术的采用具有重大影响，但对于影响大数据应用程序(如用于管理T2 DM的AI和ML)的可用性的因素进行研究的尝试似乎有限。由于可用性不仅是影响技术采用的因素，而且还决定管理过程的结果，因此有必要了解影响大数据分析应用程序在T2 DM管理中的可用性的因素，本研究旨在确定和分析影响大数据应用程序(如人工智能和ML)在T2 DM管理中的可用性的因素。研究设计为混合方法研究，首先进行定性研究，以确定概念化的研究模型，然后进行定量研究，以使模型泛化。这项研究将有助于在信息系统质量、人机交互、设计和开发大数据应用、可用性工程、用户体验(UX)和可用性测量模型等领域的学术文献。这项研究的贡献也将使医疗保健行业受益，主要是直接参与T2 DM管理和间接参与T2 DM合并疾病管理的行业。从这项研究中学到的知识也可以扩展到许多其他慢性病和许多其他环境的管理。
The global prevalence of Type 2 Diabetes Mellitus (T2DM) has been on the rise over the last four decades and is expected to rise further in the future. Big Data applications such as Artificial Intelligence (AI) and Machine learning (ML) are increasingly being used in the healthcare industry to manage various aspects of patient care. Researchers have so far studied the adoption of technologies including AI and ML in various contexts using technology adoption frameworks in the information systems (IS) domain, where the usability of technology is just viewed as one factor. Although, researches on technology adoption models in the IS domain has indicated that usability has a significant influence on the adoption of a technology, it appears that there are limited attempts made to study the factors influencing the usability of big data applications such as AI and ML for the management of T2DM. Since usability not only a factor that impacts the adoption of a technology, but also determines the outcomes of the management process, there is a need to understand the factors that influence the usability of a big data analytics application for the management of T2DM, this research aims to identify and analyse the factors influencing the usability of big data applications such as AI and ML in management of T2DM. The research is designed as mixed method research with qualitative research undertaken first to confirm the conceptualised research model followed by quantitative research to genaralise the model. This research would contribute to the academic literature in the areas of Information Systems Quality, Human-Computer Interaction (HCI), design and development big data applications, usability engineering, user experience (UX), and usability measurement model. The contributions from this research would also benefit the healthcare industry, predominantly that part of an industry that is directly involved in the management of T2DM and indirectly involved in the management of comorbidities on T2DM. The learnings from this research can also be extended to the management of many other chronic conditions and many other contexts.