openEHR archetype use and reuse within multilingual clinical data sets: a case study.

BACKGROUND Despite electronic health records being in existence for over 50 years, our ability to exchange health data remains frustratingly limited. Commonly used clinical content standards, and the information models that underpin them are primarily related to health data exchange, and so are usually document- or message-focused. In contrast, over the past 12 years, the Clinical Models program at openEHR international has gradually established a governed, coordinated, and coherent ecosystem of clinical information models, known as openEHR archetypes. Each archetype is designed as a maximal data set for a universal use-case, intended for reuse them across various health data sets, known as openEHR templates. To date, only anecdotal evidence has been available to indicate if the hypothesis of archetype reuse across templates is feasible and scalable. As a response to the COVID-19 pandemic, between February and April 2020, seven openEHR templates were independently created to represent COVID-related data sets for symptom screening, confirmed infection reporting, clinical decision support, and research. Each of the templates prioritised reuse of existing use-case agnostic archetypes found in openEHR International's online Clinical Knowledge Manager (CKM) tool as much as possible. This study is the first opportunity to investigate archetype reuse within a range of diverse, multilingual openEHR templates. OBJECTIVE To investigate the use and reuse of openEHR archetypes across the seven openEHR templates as an initial investigation about the reuse of information models across data sets used for a variety of clinical purposes. METHODS Analysis of both the number of occurrences of archetypes, and patterns of occurrence, within seven discrete templates was carried out at the archetype, or clinical concept, level. RESULTS Across all seven templates collectively, 203 instances of 58 unique archetypes were used. The most frequently used archetype occurred 24 times across four of the seven templates. Total data points per template ranged from 40 to 179. Archetype instances per template ranged from 10 to 62. Unique archetype occurrences ranged from 10 to 28. Existing archetype reuse of use-case agnostic archetypes ranged from 40% to 90%. Total reuse of use-case agnostic archetypes ranged from 40% to 100%. CONCLUSIONS Investigation of the amount of archetype reuse across the seven openEHR templates in this initial study has demonstrated significant reuse of archetypes, even across unanticipated, novel modelling challenges and multilingual deployments. While the trigger for the development of each of these templates was the COVID-19 pandemic, the templates represented a variety of types of data sets - symptom screening; infection report; clinical decision support for diagnosis and treatment; and secondary use/research. The findings support the openEHR hypothesis that it is possible to create a shared, public library of standards-based, vendor-neutral clinical information models that can be reused across a diverse range of health data sets. CLINICALTRIAL