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.
Keywords: EHRs Data Modeling; Health care task; Interoperability; NoSQL; Standardized Electronic Health Record; Workload Characteristics.
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