The increasing digitalization of healthcare necessitates laboratory data interoperability to ensure reliable clinical decision-making, efficient data exchange, and effective secondary use. Most Korean institutions use electronic systems for laboratory test reporting. However, the lack of standardized terminology, measurement units, and data structures has led to reporting inconsistencies and limited integration across institutions. We have developed a guideline using a consensus-based laboratory data framework for essential laboratory data elements that is aligned with international standards and guidelines. The laboratory data framework organizes essential laboratory data elements into five categories: Patient, Test, Specimen, Date/time, and Administrative data. Each element is also assigned to one or more usage three tiers: Data for Clinical Data Interchange, Data for Report, and Data for Laboratory. Mandatory and conditional elements are further differentiated, incorporating aspects of clinical relevance, regulatory requirements, and implementation feasibility. The laboratory data framework incorporates terminology standards, such as the Logical Observation Identifiers Names and Codes, Systematized Nomenclature of Medicine-Clinical Terms, and Unified Code for Units of Measure, supporting both semantic and syntactic interoperability. This approach enables improved data consistency, facilitates national health information exchange, and lays a foundation for advanced applications, such as clinical decision support and artificial intelligence-driven analytics.
Kim et al. (Thu,) studied this question.
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