A survey of openEHR Clinical Data Repositories

Clinical Data Repositories (CDRs) lie at the core of both primary and secondary utilisation of vast amounts of health information. These data are intricate, heterogeneous and constantly evolving alongside advancements in biomedical sciences. The separation between clinical content and its persistence renders the archetype-based paradigm naturally well-suited to manage this complexity. This approach is adopted by a number of open source and commercial CDR solutions, mostly implementing the openEHR specifications, which also encompass the Archetype Query Language (AQL) to define portable queries independently of the persistence scheme. To provide a wide knowledge base and a set of customisable tools as a support in the selection of openEHR CDRs according to a broad ensemble of features relevant to different use cases. After conducting an extensive search of the existing openEHR CDRs, a survey consisting of fifty-four questions was administered to all the nineteen identified vendors/developers, covering an ample set of aspects such as licensing, implementation, interoperability and ecosystem. Subsequently, the answers from the eleven responders were processed and analysed, also applying statistical techniques. Two detailed tables depict the current landscape of openEHR CDRs, presenting a structured view of the most relevant survey answers. Unsupervised clustering led to the categorisation of CDRs into four groups, and a decision-making diagram has been designed to aid the CDR selection according to a restricted set of desired features. Compared to a similar study conducted in 2013, the results indicate a worldwide rise in the number of openEHR CDRs, marked by a wider adoption of the dedicated query language, to leverage AQL universality across openEHR platforms. The evolution in the last ten years also included an increased attention to exchange data with non-openEHR solutions and to simplify the content creation from clinical models based on Archetypes and Templates. Materials and analytical tools hereby presented are publicly available for further reuse.

@Article{DFMSMDL24,
  author       = {Delussu, G. and Frexia, F. and Mascia, C. and Sulis, A. and Meloni, V. and Del Rio, M. and Lianas, L.},
  title        = {A survey of openEHR Clinical Data Repositories},
  journal      = {International Journal of Medical Informatics},
  volume       = {191},
  month        = {november},
  year         = {2024},
  publisher    = {Elsevier},
  keywords     = {openEHR,Archetype,ISO 13606, Clinical Data Repository, CDR, Survey},
  doi          = {10.1016/j.ijmedinf.2024.105591},
  url          = {https://publications.crs4.it/pubdocs/2024/DFMSMDL24},
}