Quality requirements for EHR Archetypes

The realisation of semantic interoperability, in which any EHR data may be communicated between heterogeneous systems and fully understood by computers as well as people on receipt, is a challenging goal. Despite the use of standardised generic models for the EHR and standard terminology systems, too much optionality and variability exists in how particular clinical entries may be represented. Clinical archetypes provide a means of defining how generic models should be shaped and bound to terminology for specific kinds of clinical data. However, these will only contribute to semantic interoperability if libraries of archetypes can be built up consistently. This requires the establishment of design principles, editorial and governance policies, and further research to develop ways for archetype authors to structure clinical data and to use terminology consistently. Drawing on several years of work within communities of practice developing archetypes and implementing systems from them, this paper presents quality requirements for the development of archetypes. Clinical engagement on a wide scale is also needed to help grow libraries of good quality archetypes that can be certified. Vendor and eHealth programme engagement is needed to validate such archetypes and achieve safe, meaningful exchange of EHR data between systems.