Health Sense: development of a universal data model and a standard for continuity of treatment paths based on international standards of new generation health information systems

The research study report focuses on developing a universal data model and continuity standard for healthcare pathways of the next-generation Estonian National Health Information System (ng-ENHIS). The study is part of the “Green ICT” program, co-financed by Norwegian Funds and conducted over 2 years.

The primary goal of the Health Sense project is to enhance the accessibility and usability of health and life course data to improve the creation of new products, services, and solutions by the private sector, public interventions, and relevant knowledge by the research and development community. The study focuses on creating a new data model for ng-ENHIS that supports semantic interoperability and continuity of care. It addresses the limitations of the current document-based data transmission system and proposes a fact-based model that allows single data entry for multiple uses. The research also involves developing a continuity of care standard and a terminology database structure to improve data exchange and usage among various stakeholders.

Problems Addressed
The Estonian National Health Information System (ENHIS) currently operates on an HL7 CDA document-based data exchange model that leads to data duplication, struggles to provide timely and complete data to key users and hinders the efficient use of information by all stakeholders, including healthcare professionals. The absence of a standardized approach for continuity of care, along with the lack of a comprehensive terminology database and streamlined data models, further complicates data exchange and limits the secondary use of valuable health information.

Novelty
A key aspect of the study is the creation of a continuity standard to ensure seamless healthcare pathways within the next-generation ENHIS (ng-ENHIS), supported by the terminology database. The study introduces a comprehensive approach to improving healthcare information systems through a fact-based data model designed to minimize data duplication and enhance accuracy. To further strengthen the system's integration, international standards such as ISO 13940 (ContSys) and ISO 23903 (Interoperability and integration reference architecture) were applied, enhancing the overall interoperability and cohesion of health information systems. Various data modelling tools, including Obsidian, Protege, Miro, and the FHIR Implementation Guide with FHIR Shorthand notation, were used to present the logical data models during the study. 
The terminology database structure to support the new data model and continuity standard in clinical practice was proposed. The integration of these elements aims to create a more efficient, interoperable, and standardized health information system. 

Key Contributions

• Development of a Fact-Based Data Models: Developed and approved necessary and optimal data models for selected treatment processes (stroke, diabetes, cancer) suitable for implementation in the ng-ENHIS, reducing duplication and improving data accuracy.
• Validation of usage International Standards: The usage of international standards HL7 FHIR, SNOMED CT and LOINC was successfully demonstrated during the project. The developed models were specified using FHIR profiles and SNOMED CT and LOINC terminologies.
• Continuity of Care Standard: The ContSys standard was translated into Estonian language, published in the ISO EE registry and introduced to the stakeholders.
• Terminology database structure: The HL7 Common Terminology Service Release 2 (CTS2) database model was recommended for implementation in the terminology server.
• Validation and Implementation: Validated the proposed models and standards with key stakeholders and demonstrated their applicability in real-world scenarios.
• Need in new tool: The study shows the lack of tools to achieve consistent and comprehensive interoperability necessary to comprehensively manage the data set and the terminology by non-technical personnel. This means that it is necessary to develop a comprehensive management tool to support data management work.

These contributions collectively provide a robust framework for improving the interoperability, usability, data accuracy and accessibility of health information systems, making them more efficient and effective for all stakeholders involved.