Mapping HL7 CDA R2 Formatted Mass Screening Data to OpenEHR Archetypes.

Area of Science:

• Health Informatics
• Medical Data Standards
• Public Health

Background:

• Employee healthcare management often relies on mass screening initiatives.
• Standardizing data collection is crucial for efficient healthcare management and electronic health records (EHRs).
• HL7 Clinical Document Architecture (CDA) Release 2 is a common standard for clinical documents.

Purpose of the Study:

• To develop a model for capturing mass screening data within the HL7 CDA R2 format.
• To ensure semantic interoperability of mass screening data for nationwide EHR systems.
• To facilitate the integration of employee healthcare screening data into broader health information exchanges.

Main Methods:

• A data model was programmed adhering to the HL7 CDA R2 specifications.
• Data items from mass screenings were mapped to ISO13606/openEHR archetypes.
• The model was designed for capturing and structuring data from adult mass health screenings.

Main Results:

• A functional model for HL7 CDA R2 compliant mass screening data capture was developed.
• Successful mapping of screening data to ISO13606/openEHR archetypes was achieved, ensuring semantic interoperability.
• The programmed model facilitates the aggregation of screening data for national electronic health records.

Conclusions:

• The developed HL7 CDA R2 model effectively captures mass screening data for EHR integration.
• Semantic interoperability is achieved through mapping to ISO13606/openEHR archetypes, enhancing data usability.
• This standardized approach supports improved employee healthcare management and nationwide health data aggregation.