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Updated: Apr 26, 2026

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

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Published on: June 30, 2014

Validating archetypes for the Multiple Sclerosis Functional Composite.

Michael Braun¹, Alexander Ulrich Brandt, Stefan Schulz

¹Center for Medical Biometry and Medical Informatics, Medical Center - University of Freiburg, Stefan-Meier-Str, 26, 79104 Freiburg, Germany. michael.braun@uniklinik-freiburg.de.

BMC Medical Informatics and Decision Making

|August 4, 2014

Summary

This summary is machine-generated.

Developing and validating openEHR archetypes ensures high-quality clinical information models. Community-based review processes, like those in the openEHR Clinical Knowledge Manager, pragmatically harmonize models for better interoperability.

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Area of Science:

Health Informatics
Clinical Informatics
Information Modeling

Background:

Electronic health records rely on robust information models like openEHR archetypes for standardized semantics and interoperability.
Current validation methods for clinical models are insufficient, impacting data quality and exchange.
Ensuring high-quality information models is critical for effective healthcare data management.

Purpose of the Study:

To investigate the feasibility of developing and community-validating openEHR archetypes.
To assess the effectiveness of a structured review process for ensuring clinical model quality.
To explore how validation can harmonize models and improve data interoperability.

Main Methods:

Applied a standard archetype development approach to three multiple sclerosis assessment clinical tests.
Organized and structured data elements through iterative refinement.
Conducted a formal, community-based review process using the openEHR Clinical Knowledge Manager with clinical and information modeling experts.

Main Results:

Successfully developed and deployed four new archetypes on the openEHR Clinical Knowledge Manager.
Validated archetypes through a structured team review process, confirming pragmatic validation.
Identified development and review as time-consuming, particularly due to selecting modeling approaches.

Conclusions:

Community- and tool-enabled review processes, like those in the openEHR Clinical Knowledge Manager, effectively ensure archetype quality.
Validation harmonizes models, reducing variation and promoting a more unified, interoperable clinical information landscape.
This approach offers a feasible method for enhancing the quality and consistency of electronic health record data.