A Report on Archetype Modelling in a Nationwide Data Infrastructure Project

Background: The nationwide data infrastructure project HiGHmed strives for achieving semantic interoperability through the use of openEHR archetypes. Therefore, a knowledge governance framework defining collaborative modelling processes has been established. For long-sustained success and the creation of high-quality archetypes, continuous monitoring is vital.

Objectives: To present an update on archetype modelling and governance framework establishment in HiGHmed.

Methods: Qualitative and quantitative analyses of the progress in establishing modelling groups, roles and users, realizing modelling workflows, and modelling archetypes.

Results: Currently, 25 modellers and 17 domain experts are participating. 79 archetypes have been identified, from which 69 are pre-existing and internationally published; completion rates of review rounds are satisfying but improvable.

Conclusions: The governance framework is valuable to make the activities manageable and to accelerate modelling. Combined with highly engaged data stewards and clinicians, a reasonable number of archetypes have already been developed.