@文章{信息:doi/10.2196/17508，作者="Ismail, Leila和Materwala, Huned和Karduck, Achim P和Adem, Abdu"，标题="生物医学护理和研究的健康数据管理系统的要求:范围审查"，期刊="J医学互联网Res"，年="2020"，月="7月"，日="7"，卷="22"，数="7"，页="e17508"，关键词="大数据;区块链;数据分析;电子健康;电子病历;卫生保健;健康信息管理;物联网;医学研究;背景:在上个世纪，临床和生物医学研究领域的破坏性事件使健康数据管理系统发生了巨大变化。 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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. ", issn="1438-8871", doi="10.2196/17508", url="//www.mybigtv.com/2020/7/e17508", url="https://doi.org/10.2196/17508", url="http://www.ncbi.nlm.nih.gov/pubmed/32348265" }