Semantic interoperation and electronic health records: context sensitive mapping from SNOMED CT to ICD-10

Area of Science:

• Health Informatics
• Medical Classification Systems
• Public Health Data Management

Background:

• Electronic Health Records (EHRs) are crucial for lifelong health data management.
• Effective reuse of clinical data from EHRs is vital for epidemiology, reimbursement, and research.
• Interoperability between different health information systems remains a significant challenge.

Purpose of the Study:

• To report on a collaboration between the International Health Terminology Standards Development Organisation (IHTSDO) and the World Health Organization (WHO).
• To develop knowledge-based tools for translating data from SNOMED CT (Systematized Nomenclature of Medicine - Clinical Terms) to the ICD-10 (International Classification of Diseases, 10th Revision) classification.
• To enhance the interoperability of health information systems through standardized data translation.

Main Methods:

• Development of knowledge-based tools for SNOMED CT to ICD-10 data translation.
• Vetting of these tools by an international community of experts.
• Making the developed tools available to system vendors.

Main Results:

• Successfully created translation tools between SNOMED CT and ICD-10.
• Tools have been validated by an international community.
• The developed maps are influencing the design of future classification systems like ICD-11.

Conclusions:

• The developed tools significantly improve the interoperability of electronic health record data.
• Availability of these tools supports system vendors in enhancing product interoperability.
• This work lays the foundation for future classifications with a common ontology base, promoting seamless data exchange.