Faculty of Computers and Information, Mansoura University, Egypt.
J Biomed Inform. 2021 Feb;114:103670. doi: 10.1016/j.jbi.2020.103670. Epub 2020 Dec 25.
With the extensive adoption of electronic health records (EHRs) by several healthcare organizations, more efforts are needed to manage and utilize such massive, various, and complex healthcare data. Databases' performance and suitability to health care tasks are dramatically affected by how their data storage model and query capabilities are well-adapted to the use case scenario. On the other hand, standardized healthcare data modeling is one of the most favorable paths for achieving semantic interoperability, facilitating patient data integration from different healthcare systems. This paper compares the state-of-the-art of the most crucial database management systems used for storing standardized EHRs data. It discusses different database models' appropriateness for meeting different EHRs functions with different database specifications and workload scenarios. Insights into relevant literature show how flexible NoSQL databases (document, column, and graph) effectively deal with standardized EHRs data's distinctive features, especially in the distributed healthcare system, leading to better EHR.
随着电子健康记录 (EHR) 在多家医疗保健机构的广泛采用，需要更多的努力来管理和利用如此庞大、多样和复杂的医疗保健数据。数据库的性能和对医疗保健任务的适用性受到其数据存储模型和查询功能适应用例场景的程度的极大影响。另一方面，标准化医疗保健数据建模是实现语义互操作性的最有利途径之一，有助于从不同的医疗保健系统集成患者数据。本文比较了用于存储标准化 EHR 数据的最关键的数据库管理系统的最新技术。它讨论了不同的数据库模型对于满足不同 EHR 功能的适当性，以及不同的数据库规范和工作负载场景。对相关文献的深入了解表明，灵活的 NoSQL 数据库（文档、列和图形）如何有效地处理标准化 EHR 数据的独特特征，特别是在分布式医疗保健系统中，从而实现更好的 EHR。
