Achieving evidence interoperability in the computer age: setting evidence on Fast Healthcare Interoperability Resources (FHIR)

Tags: Oral
Alper B1, Munn Z2, Mayer M1, Tristan M3, Salas N3, Iorio A4, Schilling L5
1EBSCO Health, 2Joanna Briggs Institute, 3IHCAI Institute, Cochrane Central America, 4McMaster University, 5University of Colorado Health Science Center

Background: efforts to support and implement evidence-based practice are limited substantially because research findings, appraisals and summarizations are not searchable and re-usable without labour-intensive manual screening and repeated data entry. Interoperability can be achieved by establishing standards for communicating evidence concepts in machine-interpretable formats. Computable formats will provide a universal architecture for the Evidence Ecosystem.

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 labour-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.

Methods: 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 for Evidence-Based Medicine Knowledge Assets (EBMonFHIR) project is in active

development with a substantial coalition of international organizations and co-ordination 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.

Patient or healthcare consumer involvement: no patient or healthcare consumer is involved.