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Updated: May 9, 2026
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Personalized-detailed clinical model for data interoperability among clinical standards.
Wajahat Ali Khan1, Maqbool Hussain, Muhammad Afzal
1Department of Computer Engineering, Kyung Hee University , Yongin-si, Gyeonggi-do, Republic of Korea.
Summary
A personalized-detailed clinical model (P-DCM) approach enables data interoperability in health information exchange (HIE) systems. This method generates customized mappings between healthcare standards, improving telemedicine services.
Area of Science:
- Health Informatics
- Data Interoperability
- Clinical Modeling
Background:
- Health information exchange (HIE) systems face challenges due to data and standards heterogeneity.
- Achieving data interoperability is crucial for effective telemedicine and timely healthcare information exchange.
Purpose of the Study:
- To propose a personalized-detailed clinical model (P-DCM) approach for generating customized mappings.
- To establish linkages between organization-specific data and clinical models for enhanced interoperability.
Main Methods:
- Utilized P-DCM for transforming Electronic Health Record (EHR) standards, openEHR, and HL7 CDA instances.
- Applied P-DCM to datasets including diabetic patient data and Alzheimer's disease patient data.
- Generated P-DCMs to derive instances for HL7 CDA and openEHR standards.
Main Results:
- Demonstrated P-DCM-based customized mappings for openEHR and HL7 CDA standards.
- Case studies included type 2 diabetes mellitus encounter information and Alzheimer's disease patient daily activities.
- Customized mappings were successfully generated based on P-DCM concept relationships.
Conclusions:
- Achieved semantic data interoperability among heterogeneous healthcare standards.
- The P-DCM approach facilitates effective resource utilization and timely information exchange.
- Enhanced interoperability supports improved healthcare delivery through telemedicine.
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