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20 Achieving evidence interoperability in the computer age: setting evidence on FHIR
  1. Brian Alper1,2,
  2. Martin Mayer1,3,
  3. Khalid Shahin1,
  4. Joshua Richardson4,
  5. Lisa Schilling5,
  6. Mario Tristan6,7,
  7. Niels Salas6
  1. 1EBSCO Health, Ipswich, MA, USA
  2. 2University of Missouri-Columbia School of Medicine, Columbia, MO, USA
  3. 3Cone Health, Greensboro, NC, USA
  4. 4RTI International, Chicago, USA
  5. 5University of Colorado, Aurora, USA
  6. 6IHCAI, San Jose, Costa Rica
  7. 7Cochrane Central America and Spanish-speaking Caribbean, San Jose, Costa Rica


Objectives Evidence-based practice requires the use of research results to inform care. Computers can add capacity for evidence-based practice by making the information from research results, appraisals, and summarizations searchable and re-usable without labor-intensive manual screening and repetition of data entry. Such interoperability can be achieved by establishing universal standards for data exchange for communicating evidence concepts in machine-interpretable formats.

Method Health Level 7 (HL7) is a standards development organization that has developed a standard for electronic exchange of healthcare information called Fast Healthcare Interoperability Resources (FHIR). We are using the HL7 standards development methodology to extend FHIR to create an Evidence Resource for exchanging descriptive, statistical and certainty concepts related to evidence.

Results The FHIR Resources for Evidence-Based Medicine Knowledge Assets (EBMonFHIR) project is in active development with a substantial coalition of international organizations and coordination with other standards development groups. The Statistic Resource currently supports explicit descriptions of the populations and subgroups (exposureBackground elements), interventions or exposures and comparators (exposureVariant elements), the outcomes (measuredVariable elements), and for each statistic the sample size, the value with unit of measure, the precision estimate, the p value, and the certainty of the statistic. The project website ( includes multiple examples and information on how to participate.

Conclusions Working together we can achieve interoperability for evidence in the electronic era to realize the technological breakthroughs we see in other domains such as navigation support. A common information architecture will also facilitate the harmonization of ‘Real World Evidence’ and ‘Evidence Based Medicine’ which collectively represent 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.

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