Data Quality Assurance Strategies In Interoperable Health Systems
Keywords:
data quality assurance, interoperable health systemsAbstract
Interoperable health systems require data quality assurance for correctness, consistency, and dependability. The methodologies are assessed here. Quality patient care requires platform compatibility and data integrity. Quality assurance is crucial when healthcare organizations construct integrated data exchange systems, which increase data inconsistencies, redundancies, and errors. This article discusses data integration issues and technological and administrative ways to enhance healthcare data quality.
Assessing interoperable health system data accuracy, completeness, consistency, validity, and timeliness. These challenges impact data integrity, patient care, clinical judgments, and health management efficiency. This research also examines important cross-organizational healthcare data quality assurance systems. Study emphasizes SNOMED CT, LOINC, and ICD-10 data validation, cleansing, and semantic interoperability.
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