Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Nov 3, 2023
Open Peer Review Period: Nov 3, 2023 - Dec 29, 2023
Date Accepted: Apr 6, 2024
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Making Science Computable: Introducing Evidence-Based Medicine on Fast Healthcare Interoperability Resources (EBMonFHIR)
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.
Citation
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Copyright
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