Making Science Computable: Introducing Evidence-Based Medicine on Fast Healthcare Interoperability Resources (EBMonFHIR) (Preprint)

Author:

Soares Andrey,Schilling Lisa M.ORCID,Richardson Joshua,Kommadi Bhagvan,Subbian Vignesh,Dehnbostel Joanne,Shahin Khalid,Robinson Karen A.,Afzal MuhammadORCID,Lehmann Harold P.,Kunnamo Ilkka,Alper Brian S.

Abstract

BACKGROUND

Evidence-Based Medicine (EBM) has the potential to improve health outcomes, but EBM has not been widely integrated into the systems used for research or clinical decision making. There has not been a scalable and reusable computer-readable standard for distributing research results and synthesized evidence among creators, implementers, and the ultimate users of that evidence. Evidence that is more rapidly updated, synthesized, disseminated, and implemented would improve both the delivery of EBM and evidence-based health care policy

OBJECTIVE

To introduce the Evidence-Based Medicine (EBM) on Fast Healthcare Interoperability Resources (FHIR®) project (EBMonFHIR), which is extending the methods and infrastructure of Health Level Seven (HL7®) FHIR to provide an interoperability standard for electronic exchange of health-related scientific knowledge.

METHODS

As an ongoing process, the project creates and refines FHIR Resources to represent evidence from clinical studies and syntheses of those studies and develops tools to assist with the creation and visualization of FHIR Resources.

RESULTS

The EBMonFHIR project created FHIR Resources (i.e., ArtifactAssessment, Citation, Evidence, EvidenceReport, EvidenceVariable) for representing evidence. The COVID-19 Knowledge Accelerator (COKA) project, now Health Evidence Knowledge Accelerator (HEvKA), furthered this work and created FHIR Resources that express EvidenceReport, Citation, and ArtifactAssessment concepts. The group are (1) continually refining FHIR Resources to support the representation of EBM, (2) developing controlled terminology related to EBM (i.e., study design, statistic type, statistical model, and risk of bias), and (3) developing tools to facilitate the visualization and data entry of EBM information into FHIR Resources, including human-readable interfaces and JavaScript Object Notation (JSON) viewers.

CONCLUSIONS

EBMonFHIR Resources in conjunction with other FHIR Resources can support relaying EBM components in a manner that is interoperable and consumable by downstream tools and health information technology systems to support users of evidence.

Publisher

JMIR Publications Inc.

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