The work of producing systematic reviews is difficult and there is an intense amount of duplicate effort. This work is needed to interpret the full body of evidence for insights to inform clinical decision making and policy decision making. We were already working on computable standards for the expression of evidence and statistics to make this work more efficient. Needing this for COVID-19 knowledge to overcome the current crisis inspires us to act in days to weeks instead of months to years for the next steps in this project.

What it does

The FHIR(R) standard provides a universal standard for data exchange of electronic health information. The Evidence, EvidenceVariable, Statistic and OrderedDistribution resources added to the FHIR standard extend FHIR to be used for evidence and statistics.

How we built it

We used the HL7(R) methodologies for standards development and the FHIR syntax.

Challenges we ran into

Precise specification of evidence for an actual set of evidence requires determination of the code sets and value sets needed for each instance. Doing this for COVID-19 evidence (which is different than our preliminary areas of effort) will add challenges to scope new spaces.

Accomplishments that we're proud of

We established a foundational model for standard computable expression of evidence and statistics in less than two years.

What we learned

What's next for COVID-19 Knowledge Accelerator

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