Developing Data Model for Electronic Health Record System

The development of an Electronic Health Record (EHR) system requires a standardized Minimum Data Set (MDS) and a robust data model to effectively support complex clinical workflows, interoperability, and data quality. Many current EHR implementations lack integrated and standardized data models, leading to redundancy, semantic inconsistencies, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on an MDS that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach includes the design of conceptual, logical, and physical data models. Business processes were analyzed to identify relationships among clinical and administrative data classes, which were then transformed into a conceptual data model. The logical data model was developed through database normalization and schema definition, while the physical data model was created to represent the actual database structure for implementation. The results show a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows, supporting data consistency, interoperability, and efficient data storage and access. A prototype EHR system demonstrated that the proposed model is feasible, stable, usable, and aligned with functional requirements, providing a strong foundation for national or institutional EHR development and future data standardization efforts.