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  • https://doi.org/10.47191/etj/v11i02.13Copy DOI Icon

Developing Data Model for Electronic Health Record System

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Abstract

The development of an Electronic Health Record (EHR) system requires a well-defined data set and a robust data model to support complex clinical workflows, interoperability, and data quality. Many existing EHR implementations lack standardized and integrated data models, resulting in redundancy, semantic inconsistency, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on a Minimum Data Set (MDS) that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach involves the design of a conceptual, logical, and physical data model. Business processes were first analysed 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 constructed to represent the actual database structure for implementation. The results demonstrate a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows. The conceptual data model establishes clear entity relationships, supporting data consistency and interoperability. The logical data model provides a normalized SQL-based schema that minimizes redundancy and enhances data integrity, while the physical data model enables efficient data storage and access. A prototype EHR system was implemented to evaluate the feasibility of the proposed data model, showing stable performance, usability, and alignment with functional requirements. This study concludes that a standardized EHR data model derived from an MDS can effectively support comprehensive clinical documentation, interoperability, and future scalability. The proposed model provides a strong foundation for developing national or institutional EHR systems and can serve as a reference for further EHR data standardization efforts.

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