Department of Accounting and Information Systems, College of Business and Law, University of Canterbury, Christchurch, New Zealand.
Help 4 U Limited, Christchurch, New Zealand.
Int J Med Inform. 2021 May;149:104420. doi: 10.1016/j.ijmedinf.2021.104420. Epub 2021 Feb 19.
Of the Sustainable Development Goals (SDGs), the third presents the opportunity for a predictive universal digital healthcare ecosystem, capable of informing early warning, assisting in risk reduction and guiding management of national and global health risks. However, in reality, the existing technology infrastructure of digital healthcare systems is insufficient, failing to satisfy current and future data needs.
This paper systematically reviews emerging information technologies for data modelling and analytics that have potential to achieve Data-Centric Health-Care (DCHC) for the envisioned objective of sustainable healthcare. The goal of this review is to: 1) identify emerging information technologies with potential for data modelling and analytics, and 2) explore recent research of these technologies in DCHC.
A total of 1619 relevant papers have been identified and analysed in this review. Of these, 69 were probed deeply. Our analysis found that the extant research focused on elder care, rehabilitation, chronic diseases, and healthcare service delivery. Use-cases of the emerging information technologies included providing assistance, monitoring, self-care and self-management, diagnosis, risk prediction, well-being awareness, personalized healthcare, and qualitative and/or quantitative service enhancement. Limitations identified in the studies included vendor hardware specificity, issues with user interface and usability, inadequate features, interoperability, scalability, and compatibility, unjustifiable costs and insufficient evaluation in terms of validation.
Achievement of a predictive universal digital healthcare ecosystem in the current context is a challenge. State-of-the-art technologies demand user centric design, data privacy and protection measures, transparency, interoperability, scalability, and compatibility to achieve the SDG objective of sustainable healthcare by 2030.
在可持续发展目标(SDGs)中,第三个目标提出了建立一个具有预测能力的通用数字化医疗生态系统的机会,该系统能够提供早期预警,帮助降低风险,并指导国家和全球卫生风险的管理。然而,在现实中,现有的数字化医疗系统技术基础设施还不够完善,无法满足当前和未来的数据需求。
本文系统地回顾了新兴信息技术在数据建模和分析方面的应用,这些技术有可能实现以数据为中心的医疗保健(DCHC),以实现可持续医疗保健的预期目标。本综述的目的是:1)确定具有数据建模和分析潜力的新兴信息技术,2)探索这些技术在 DCHC 中的最新研究。
本综述共识别和分析了 1619 篇相关论文,其中对 69 篇进行了深入探讨。我们的分析发现,现有的研究主要集中在老年护理、康复、慢性病和医疗服务提供方面。新兴信息技术的应用案例包括提供辅助、监测、自我护理和自我管理、诊断、风险预测、幸福感意识、个性化医疗以及定性和/或定量服务增强。研究中发现的局限性包括供应商硬件的特殊性、用户界面和可用性问题、功能不足、互操作性、可扩展性和兼容性、不合理的成本以及在验证方面的评估不足。
在当前背景下,实现具有预测能力的通用数字化医疗生态系统是一项挑战。最先进的技术需要以用户为中心的设计、数据隐私和保护措施、透明度、互操作性、可扩展性和兼容性,以实现到 2030 年可持续医疗保健的 SDG 目标。