Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates.
Faculty of Informatics, Furtwangen University, Furtwangen, Germany.
J Med Internet Res. 2020 Jul 7;22(7):e17508. doi: 10.2196/17508.
Over the last century, disruptive incidents in the fields of clinical and biomedical research have yielded a tremendous change in health data management systems. This is due to a number of breakthroughs in the medical field and the need for big data analytics and the Internet of Things (IoT) to be incorporated in a real-time smart health information management system. In addition, the requirements of patient care have evolved over time, allowing for more accurate prognoses and diagnoses. In this paper, we discuss the temporal evolution of health data management systems and capture the requirements that led to the development of a given system over a certain period of time. Consequently, we provide insights into those systems and give suggestions and research directions on how they can be improved for a better health care system.
This study aimed to show that there is a need for a secure and efficient health data management system that will allow physicians and patients to update decentralized medical records and to analyze the medical data for supporting more precise diagnoses, prognoses, and public insights. Limitations of existing health data management systems were analyzed.
To study the evolution and requirements of health data management systems over the years, a search was conducted to obtain research articles and information on medical lawsuits, health regulations, and acts. These materials were obtained from the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery, Elsevier, MEDLINE, PubMed, Scopus, and Web of Science databases.
Health data management systems have undergone a disruptive transformation over the years from paper to computer, web, cloud, IoT, big data analytics, and finally to blockchain. The requirements of a health data management system revealed from the evolving definitions of medical records and their management are (1) medical record data, (2) real-time data access, (3) patient participation, (4) data sharing, (5) data security, (6) patient identity privacy, and (7) public insights. This paper reviewed health data management systems based on these 7 requirements across studies conducted over the years. To our knowledge, this is the first analysis of the temporal evolution of health data management systems giving insights into the system requirements for better health care.
There is a need for a comprehensive real-time health data management system that allows physicians, patients, and external users to input their medical and lifestyle data into the system. The incorporation of big data analytics will aid in better prognosis or diagnosis of the diseases and the prediction of diseases. The prediction results will help in the development of an effective prevention plan.
在上个世纪，临床和生物医学研究领域的破坏性事件导致了医疗数据管理系统的巨大变革。这是由于医学领域的一些突破以及将大数据分析和物联网 (IoT) 纳入实时智能健康信息管理系统的需要。此外，随着时间的推移，对患者护理的要求也在不断发展，从而能够进行更准确的预后和诊断。在本文中，我们讨论了医疗数据管理系统的时间演变，并捕捉到了导致特定系统在特定时间段内发展的要求。因此，我们深入了解了这些系统，并就如何改进它们以改善医疗保健系统提供了建议和研究方向。
本研究旨在表明需要一个安全有效的医疗数据管理系统，使医生和患者能够更新分散的医疗记录，并分析医疗数据以支持更精确的诊断、预后和公共洞察。分析了现有医疗数据管理系统的局限性。
为了研究多年来医疗数据管理系统的演变和要求，我们进行了搜索，以获取有关医疗诉讼、医疗法规和法案的研究文章和信息。这些材料是从电气和电子工程师协会、计算机协会、爱思唯尔、MEDLINE、PubMed、Scopus 和 Web of Science 数据库中获得的。
多年来，医疗数据管理系统经历了从纸质到计算机、网络、云、物联网、大数据分析，最终到区块链的颠覆性转变。从不断演变的病历及其管理定义中揭示的医疗数据管理系统的要求是 (1) 病历数据，(2) 实时数据访问，(3) 患者参与，(4) 数据共享，(5) 数据安全，(6) 患者身份隐私，(7) 公共洞察。本文根据多年来进行的研究，基于这 7 项要求对医疗数据管理系统进行了回顾。据我们所知，这是对医疗数据管理系统时间演变的首次分析，深入了解了更好的医疗保健系统的系统要求。
需要一个全面的实时医疗数据管理系统，允许医生、患者和外部用户将他们的医疗和生活方式数据输入系统。大数据分析的纳入将有助于更好地预测或诊断疾病，并预测疾病。预测结果将有助于制定有效的预防计划。
