A Report on Archetype Modelling in a Nationwide Data Infrastructure Project
Wulff, A.; Sommer, K.Katrin.; Ballout, S.; Haarbrandt, B.; Gietzelt, M.
Studies in Health Technology and Informatics 258: 146-150
2019
ISSN/ISBN: 0926-9630 PMID: 30942733 Document Number: 699760
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. To present an update on archetype modelling and governance framework establishment in HiGHmed. Qualitative and quantitative analyses of the progress in establishing modelling groups, roles and users, realizing modelling workflows, and modelling archetypes. 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. 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.