Objectives: We developed an electronic health records (EHR) system for regional healthcare in 2000. This EHR stores the health records of more than 6,300 patients in two regions of Japan; however, clinical updates and improved interoperability with other clinical standards, such as HL7 or others are needed. In 2015, this EHR system was upgraded to create a nationwide-scale healthcare data repository to improve the interoperability of clinical data with openEHR technology.
Methods: The clinical data in our EHR system has 16 components constructed with Medical Markup Language (MML) standards and periodic mass screening for employees and students. Therefore, we constructed mindmaps of the clinical MML and surveillance data to analyse the concept models. Based on mindmap analysis, we designed archetypes of the concepts identified using Ocean Archetype Editor. The artefacts were mainly quoted from the openEHR clinical knowledge manager (CKM). As the archetypes on CKM did not include all MML semantics, the archetypes were newly designed to complement the semantics of the MML.
Results: We developed clinical information models by archetypes that semantically equalled the EHR system. Twenty-one MML components/modules and concept models using 99 archetypes were constructed for periodic mass screening services. Most of the archetypes were quoted from CKM; however, 22 archetypes were specialised, and eight archetypes were newly designed. The reasons for specialisation were to adjust the demographics to Japanese and to extend the archetypes to the dental domain.
Conclusion: We constructed concept models with archetypes semantically equivalent to conventional data and developed new archetypes for mass screening by archetype technology. The suggested archetype technology improved the flexibility of the EHR system to cover the existing standards.