Clinical Modelling in Healthcare: The Role of ISO 13972 in Standardizing Clinical Information Structures

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Clinical modelling has emerged as a critical component of modern healthcare, addressing the need for standardized, interoperable, and precise representation of clinical information. It ensures that health information systems (HIS) effectively capture, store, and exchange patient data. An essential element in this domain is the ISO 13972 standard, which defines the principles for clinical information modelling and provides guidelines for developing reusable, standardized data structures. This outlines the intricacies of clinical modelling and the pivotal role of ISO 13972, offering an advanced perspective supported by references.

What is Clinical Modelling?

Clinical modelling involves creating structured, reusable representations of clinical concepts and data to facilitate accurate documentation, analysis, and health information exchange. These models are often abstract representations of clinical scenarios, designed to:

  1. Improve Interoperability: Enable seamless communication between diverse HIS.
  2. Enhance Data Quality: Ensure completeness, consistency, and clarity of clinical data.
  3. Support Clinical Decision-Making: Provide structured data for evidence-based practices and analytics.

Clinical models are implemented using various frameworks and standards, such as HL7 FHIR, openEHR archetypes, and templates. Each framework supports creating modular and adaptable models tailored to specific clinical and operational contexts.


https://www.iso.org/standard/79498.html

ISO 13972: Standardizing Clinical Information Modelling

ISO 13972:2022, titled "Health Informatics — Detailed Clinical Models," is a comprehensive standard that provides guidance on creating and managing clinical models. It specifies requirements for defining, validating, and maintaining detailed clinical models (DCMs), which are the building blocks for structured and interoperable health information.

Key Features of ISO 13972:

  1. Modularity and Reusability: Emphasizes the creation of models that can be reused across multiple systems and scenarios.
  2. Semantic Precision: Ensures that clinical models are semantically consistent, minimizing ambiguity in data representation.
  3. Validation Framework: Provides a methodology for verifying the completeness, correctness, and clinical relevance of models.
  4. Interoperability Standards: Aligns with global standards like HL7 and openEHR to enhance cross-platform compatibility.
  5. Lifecycle Management: Includes provisions for versioning, maintenance, and updating of clinical models.

The Role of ISO 13972 in Clinical Modelling

ISO 13972 serves as a cornerstone for standardized clinical modelling practices, fostering a unified approach to health information management. Its influence extends across various aspects:

Standardized Terminology Integration

ISO 13972 supports the integration of terminologies such as SNOMED CT, ICD, and LOINC, ensuring consistency and alignment with global coding systems.

Facilitating Interoperability

By adhering to ISO 13972, healthcare systems can achieve true interoperability, allowing data to flow seamlessly between electronic health records (EHRs), laboratory systems, and other HIS.

Improved Clinical Decision Support (CDS)

DCMs developed under ISO 13972 provide structured data inputs for CDS systems, enabling real-time insights and evidence-based recommendations.

Enhancing Patient Safety

The precision and clarity in clinical data representation reduce errors in diagnosis, treatment, and data interpretation, directly impacting patient safety.

Regulatory Compliance

ISO 13972 ensures compliance with international health informatics standards, simplifying adherence to regulatory requirements for data exchange and protection.

Applications of ISO 13972 in Healthcare

  • EHR Systems: Design of interoperable and user-friendly EHRs with structured clinical data.
  • Research and Analytics: Creation of datasets with uniform semantics for advanced research and predictive analytics.
  • Telemedicine: Standardized data exchange in remote consultations, ensuring consistency across platforms.
  • Public Health Surveillance: Aggregation of harmonized data for population health management and outbreak monitoring.

Challenges in Implementing ISO 13972

While the benefits are substantial, implementing ISO 13972 is not without challenges:

  • Resource Intensity: Developing and maintaining DCMs require significant expertise and time investment.
  • Stakeholder Engagement: Aligning diverse stakeholders on a standardized framework can be complex.
  • Technological Barriers: Legacy systems may not be compatible with modern modelling standards.
  • Continuous Evolution: Rapid advancements in healthcare necessitate frequent updates to clinical models.

Future Directions

The future of clinical modelling lies in further integration with emerging technologies:

  • Artificial Intelligence (AI): AI-driven tools can automate creating and validating clinical models.
  • Blockchain: Ensures secure and immutable management of model lifecycle.
  • Global Harmonization: Efforts to align ISO 13972 with other international standards will enhance its adoption and impact.

Conclusion

ISO 13972:2022 is a transformative framework in the field of clinical modelling, offering structured methodologies for creating interoperable and reusable clinical models. Its adoption addresses critical challenges in healthcare data management, paving the way for more efficient, precise, and patient-centric systems. As healthcare continues to embrace digital transformation, adherence to ISO 13972 will be essential for achieving seamless data exchange, improving patient outcomes, and fostering global collaboration.

References

  1. ISO. (2017). ISO 13972: Health Informatics — Detailed Clinical Models. International Organization for Standardization.
  2. Beale, T., & Heard, S. (2008). An openEHR approach to detailed clinical models. Studies in Health Technology and Informatics, 129(Pt 1), 139-143.
  3. Health Level Seven International (HL7). (2021). FHIR Overview. Retrieved from HL7 Website
  4. Kalra, D. (2006). Clinical models and healthcare standards. Methods of Information in Medicine, 45(1), 31-35.
  5. SNOMED International. (2023). SNOMED CT: Overview and Applications. Retrieved from SNOMED Website
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