Evidence standard practice requires the use of research results to inform the computers that can add capacity for evidence-based practice by making the information from research results, standard the summarisations searchable and re-usable without labour-intensive manual screening and repetition of data entry. Such interoperability can be achieved by Objectives: The “Extending FHIR for Evidence-Based Medicine Knowledge Assets” (EBMonFHIR) project is defining a standard for computable, interoperable expression of evidence. As part of a universal architecture for the Evidence Ecosystem that aligns with the FAIR data principles (making knowledge Findable, Accessible, Interoperable, and Reusable). The EBMonFHIR Work Group is in active development with a substantial coalition of international organisations and coordination with other standards development groups
Methods: We are using the HL7 standards development methodology, including weekly open meetings, and three Connect-a-thons per year, to extend FHIR to create resources for exchanging descriptive, statistical and certainty of the evidence
Results: The EBMonFHIR project was approved in June of 2018. As of February 2020, we have defined new Resources (Evidence Resource and EvidenceVariable Resource) and new Data Types (Statistic Data Type, OrderedDistribution Data Type) to define exchangeable interoperable evidence results entirely. The project website (https://confluence.hl7.org/display/CDS/EBMonFHIR) includes multiple examples and information on how to participate
Conclusions: Working together we can achieve interoperability for evidence in the
electronic era to realise the technological breakthroughs we see in other domains such as navigation support. Typical information architecture will also facilitate the harmonisation of 'Real World Evidence' and 'Evidence-Based Medicine' which collectively represent a clear understanding of evidence and its certainty, regardless of evidence source. Extending the solutions achieving interoperability for healthcare services provide a means to not only solve this challenge for the Evidence Ecosystem but also to keep it well connected with healthcare services delivery. Patient or healthcare consumer involvement: no patient or healthcare consumer isinvolved.