Clinical Modelling

Introduction

Clinical modelling is the process of creating representations of healthcare concepts and their relationships. These models are used to standardize and structure clinical data, enabling better data sharing, interoperability, and analysis. Clinical models can be used to represent various aspects of healthcare, such as patient information, clinical workflows, and medical terminologies.

Why openEHR is a Good Approach for Clinical Modelling

openEHR is a widely adopted approach for clinical modelling due to several key reasons:

  1. Standardization: openEHR provides a standardized framework for representing clinical data, ensuring consistency and interoperability across different healthcare systems.

  2. Flexibility: The openEHR architecture is highly flexible, allowing for the creation of detailed and complex clinical models that can be easily adapted to various clinical scenarios.

  3. Interoperability: By using openEHR, healthcare organizations can achieve better interoperability, enabling seamless data exchange between different systems and improving patient care.

  4. Community and Collaboration: openEHR has a strong community of healthcare professionals, developers, and researchers who collaborate to continuously improve and expand the framework.

  5. Clinical Focus: The openEHR approach is specifically designed for the healthcare domain, ensuring that the models are clinically relevant and useful for healthcare providers.

  6. Longevity and Sustainability: openEHR is designed to be a long-term solution for clinical data management, with a focus on sustainability and the ability to evolve with changing healthcare needs.

Other Formalisms for Clinical Modelling

While openEHR is a popular choice for clinical modelling, there are several other formalisms that can be used:

  1. HL7 FHIR (Fast Healthcare Interoperability Resources): FHIR is a standard for exchanging healthcare information electronically. It provides a set of resources and APIs for building interoperable healthcare applications.

  2. SNOMED CT (Systematized Nomenclature of Medicine — Clinical Terms): SNOMED CT is a comprehensive clinical terminology that provides a standardized way to represent clinical concepts and their relationships.

  3. LOINC (Logical Observation Identifiers Names and Codes): LOINC is a coding system for identifying laboratory and clinical observations. It is widely used for exchanging and aggregating clinical results.

  4. CDA (Clinical Document Architecture): CDA is a standard developed by HL7 for the structure and semantics of clinical documents. It is used for the exchange of clinical documents between healthcare providers.

  5. OMOP (Observational Medical Outcomes Partnership): OMOP is a common data model used for observational healthcare data. It standardizes the structure and content of data to facilitate large-scale analytics.

Each of these formalisms has its own strengths and use cases, and the choice of which to use depends on the specific requirements of the clinical modelling project.

Best Approach for Clinical Modelling

The best approach for clinical modelling depends on the specific needs and context of the healthcare organization or project. However, a combination of the following practices can lead to successful clinical modelling:

  1. Understand the Requirements: Clearly define the clinical and technical requirements of the project. Engage with stakeholders, including clinicians, to ensure that the models will meet their needs.

  2. Choose the Right Formalism: Select the appropriate formalism or combination of formalisms based on the project’s requirements. Consider factors such as interoperability, standardization, and the specific clinical domain.

  3. Leverage Existing Models: Utilize existing clinical models and standards whenever possible. This can save time and ensure consistency with widely accepted practices.

  4. Iterative Development: Develop clinical models iteratively, allowing for feedback and refinement. This approach helps to identify and address issues early in the development process.

  5. Collaboration and Community Engagement: Collaborate with other healthcare organizations, developers, and researchers. Participate in communities and initiatives related to clinical modelling to stay updated on best practices and advancements.

  6. Validation and Testing: Rigorously validate and test the clinical models to ensure accuracy, reliability, and usability. Engage end-users in the testing process to gather valuable feedback.

  7. Documentation and Training: Provide comprehensive documentation and training for users of the clinical models. This ensures that the models are correctly implemented and used effectively.

By following these practices, healthcare organizations can create robust and effective clinical models that enhance data interoperability, improve patient care, and support clinical decision-making.

DIPS and openEHR

DIPS is a significant player in the openEHR community. As a leading provider of healthcare information systems in the Nordic region, DIPS has been actively involved in the development and implementation of openEHR-based solutions. Their contributions include:

  1. Innovative Solutions: DIPS develops innovative healthcare solutions that leverage the openEHR framework to ensure interoperability and standardization across healthcare systems.

  2. Collaboration: DIPS collaborates with various stakeholders, including healthcare providers, researchers, and other technology companies, to advance the adoption and evolution of openEHR.

  3. Implementation: DIPS has successfully implemented openEHR-based systems in numerous healthcare organizations, demonstrating the practical benefits and scalability of the framework.

  4. Community Engagement: DIPS actively participates in the openEHR community, contributing to the development of standards, sharing best practices, and supporting the growth of the ecosystem.

Through their efforts, DIPS has established itself as a key player in promoting and utilizing openEHR to improve healthcare data management and patient care.