Clinical professional governance for detailed clinical models

Area of Science:

• Health Informatics
• Clinical Knowledge Representation
• Information Modeling

Background:

• Contemporary Electronic Health Systems require standardized data structures for interoperability.
• Existing knowledge representation methods, including terminologies and information models, form the basis for clinical modeling.
• Global efforts are converging towards international standards for Detailed Clinical Models.

Purpose of the Study:

• To define Detailed Clinical Models (DCMs) and explain their role in processing clinical data.
• To illustrate the core components of well-defined DCMs, including clinical knowledge, context, data elements, and terminology bindings.
• To present examples of DCMs and their application within health information architectures.

Main Methods:

• Explanation of knowledge representation principles (terminologies, information models).
• Definition and purpose of Detailed Clinical Models.
• Illustration of DCM components and presentation of examples in text and Unified Modeling Language (UML).
• Discussion of DCMs' role in health information architectures and project examples.

Main Results:

• Detailed Clinical Models specify conceptual and logical levels of modeling, adaptable for various implementations.
• Examples demonstrate DCMs' structure and application in health information systems.
• Projects creating and deploying DCMs highlight the importance of material reuse and strict governance.

Conclusions:

• Strict governance, including clinical validation and model testing, is essential for the safe use of DCMs in healthcare.
• A Plan-Do-Check-Act cycle is applicable for governing DCMs.
• Repositories are necessary for storing, searching, and maintaining collections of clinical models at local, national, and international levels.