title: Can openEHR Archetypes Empower Multi-Centre Clinical Research?
abstract: The Electronic Health Record is of utmost importance to enable the provision of high-quality collaborative care; one prominent development is openEHR. On the other hand, a systematic approach to support the use of routine data for multi-centre clinical research is becoming increasingly important. One example of this is the extensible architecture for using routine data for additional purposes (eardap) which features comprehensive terminological support. However, as experiences in various medical fields have shown, the terminology-based approach is limited to specialized fields and it is argued that a comprehensive terminology is simply too complex and too difficult to maintain. As the openEHR archetype approach does not rely heavily on big standardized terminologies, it offers more flexibility during standardisation of clinical concepts and overcome the shortcomings of terminology-focused approaches. It is unknown, however, how far the more generic openEHR approach can also enable re-use of routinely collected data for clinical research purposes - the use case for which eardap was designed. We therefore explored the feasibility of using the openEHR approach to support multi-centre research in comparison to eardap. Generally speaking, our results show that both eardap and openEHR are suitable to enable the use of routine data for multi-centre clinical research. As the openEHR approach also ensures open, future-proof Electronic Health Records, we conclude that it is highly desirable that multi-centre clinical trials adopt openEHR.
authors.affiliation: Health Informatics Research Group, Central Queensland University, Rockhampton, Australia.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Garde
authors.forename: Petra
authors.initials: P
authors.lastname: Knaup
authors.forename: Thilo
authors.initials: T
authors.lastname: Schuler
authors.forename: Evelyn
authors.initials: E
authors.lastname: Hovenga
mesh_terms: D035843:Biomedical Research; D057286:Electronic Health Records; D006801:Humans; D016347:Medical Records Systems, Computerized; D012660:Semantics