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Representing Knowledge Consistently Across Health Systems
Yearbook of Medical Informatics
|October 25, 2017
Summary
Standardizing electronic health records (EHRs) data through common data models enhances research capabilities. This progress facilitates secure, high-quality clinical data sharing across institutions for broader scientific discovery.
Area of Science:
- Health Informatics
- Clinical Data Management
- Biomedical Research
Background:
- Electronic health records (EHRs) are valuable for research and health applications.
- A significant challenge is standardizing knowledge representation across diverse EHR systems.
- Interoperability is crucial for leveraging EHR data effectively.
Purpose of the Study:
- To review knowledge representation in common data models for EHRs.
- To assess standards supporting interoperable health applications.
- To understand the landscape of standardized clinical data sharing.
Main Methods:
- Literature review of studies on OMOP CDM and PCORNet.
- Review of Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) standard.
- Analysis of efforts in quality-assured clinical data standardization.
Main Results:
- Significant growth in high-impact initiatives for standardized clinical data sharing.
- Focus on three major efforts advancing shareable, transportable, and computable clinical data.
- Development of common data models is increasing.
Conclusions:
- Advancements in common data models support interoperable knowledge representation.
- Expect increased availability of high-quality clinical data for research.
- Future data sharing will enable global research participation.
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