Mayya Veena, Kandala Rajesh N V P S, Gurupur Varadraj, King Christian, Vu Giang T, Wan Thomas T H
Center for Decision Support Systems and Informatics, School of Global Health Management and Informatics, University of Central Florida, Orlando, Florida, USA.
Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Health Serv Res Manag Epidemiol. 2024 Aug 28;11:23333928241275292. doi: 10.1177/23333928241275292. eCollection 2024 Jan-Dec.
Diabetes mellitus is an important chronic disease that is prevalent around the world. Different countries and diverse cultures use varying approaches to dealing with this chronic condition. Also, with the advancement of computation and automated decision-making, many tools and technologies are now available to patients suffering from this disease. In this work, the investigators attempt to analyze approaches taken towards managing this illness in India and the United States.
In this work, the investigators have used available literature and data to compare the use of artificial intelligence in diabetes management.
The article provides key insights to comparison of diabetes management in terms of the nature of the healthcare system, availability, electronic health records, cultural factors, data privacy, affordability, and other important variables. Interestingly, variables such as quality of electronic health records, and cultural factors are key impediments in implementing an efficiency-driven management system for dealing with this chronic disease.
The article adds to the body of knowledge associated with the management of this disease, establishing a critical need for using artificial intelligence in diabetes care management.
糖尿病是一种在全球普遍存在的重要慢性病。不同国家和多样文化采用不同方法来应对这种慢性病。此外,随着计算和自动化决策的进步,现在有许多工具和技术可供糖尿病患者使用。在这项研究中,研究人员试图分析印度和美国针对这种疾病的管理方法。
在这项研究中,研究人员利用现有文献和数据来比较人工智能在糖尿病管理中的应用。
本文从医疗保健系统的性质、可及性、电子健康记录、文化因素、数据隐私、可承受性以及其他重要变量等方面,对糖尿病管理的比较提供了关键见解。有趣的是,诸如电子健康记录质量和文化因素等变量是实施效率驱动的慢性病管理系统的关键障碍。
本文丰富了与这种疾病管理相关的知识体系,确立了在糖尿病护理管理中使用人工智能的迫切需求。