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Overview

  • This page is a resource to help stakeholders working along the COVID-19 evidence-to guidance- to action - to data - to evidence cycle improve their work processes and results. The ultimately goal is to a soon as possible, improve COVID-19 care delivery and outcomes.
  • The tables below are designed to aggregate Collaborative participant recommendations for addressing steps in this COVID-19 knowledge ecosystem. The recommended tools and approaches are being gathered and will evolve over time as stakeholder input is received and community consensus around best practices - and the pandemic itself - evolve.

Recommendation Tables for Knowledge Ecosystem Steps

     Table List

  • Identify Studies
  • Synthesize Evidence
  • Produce Guidance
  • Make Guidance Computable
  • Implement Guidance
  • Analyze Care Results
  • Leverage Results Analysis (e.g., for Quality Improvement, Reporting, Evidence Generation)

Identify Studies


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources

Search Strategies



Output Repositories



Current Standards



Emerging Standards



Initiatives
  • Librarian Reserve Corps
    • COVID-Evidence Project - building a database to gather all the evidence around a drug (University of Basil - currently focused on hydroxychloroquine, but model could be adaptable to other targets)
    • Identification of sources to identify primary studies - validation study of specialized COVID-19 databases (systematic reviewers are going to different sources - this effort is to identify best practices)
    • Advocate for librarian representation in searches and reviews - leverage skillsets/best practices in this work
      [SLMC]: close gaps between needs that clinicians are seeing on the front line and topics covered in reviews guidelines
  • COKA Evidence/ Tools WG [Project Google Drive](work in process)



Tools/ Platforms



Other Best Practices




Synthesize Evidence


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources
Output Repositories


Current Standards


Emerging Standards



Initiatives



Tools/ Platforms


Other Best Practices
  • COVID-NMA has initiated communication with all trialists to try to ensure consistent approaches e.g. selection of outcomes, reduction of risk of bias, and to invite them to contribute missing data. 




Produce Guidance


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources
  • See Output Repositories from Synthesize Evidence table

Output Repositories


Current Standards



Emerging Standards



Initiatives



Tools/ Platforms


Other Best Practices


Make Guidance Computable


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources
  • See output repositories under Produce Guidance



Output Repositories


Current Standards


Emerging Standards


Initiatives



Tools/ Platforms


Other Best Practices

From C19HCC Digital Guideline WG:

  • Using CPG-on-FHIR standard for representing/ expressing the full intent of the Guidance in computer-interpretable artifacts (part of HL7 CPG-IG)
  • Using the Agile Approach to CPG Development (inclusive of Integrated Process) to concurrently Produce Guidance and Make Guidance Computable (part of HL7 CPG-IG)
  • Use Agile Knowledge Engineering methods, principles, and tools
    • Cross-functional Integrated team (Agile CPG Team)
    • Leverage composite nature of CPGs (e.g. can develop logic for inferences on patient information- CPG_CaseFeatures) to build incrementally and iteratively with rapid feedback
    • Pull knowledge engineers into Content design/reviews; pull domain SMEs into knowledge representation design/reviews
  • Leverage CPG-on-FHIR as a faithful expression of Guidance and its ability to create computationally derived CDS and Cognitive Support, patient-specific, practice-level digital Quality Measures/Metrics, eCaseReports, etc. to create computable artifacts used downstream in the Learning Health System and to provide closed-loop feedback/feedforward.
  • Leverage established tools and capabilities (e.g. BPM+ process and tooling, Clinical Ontology) to author computable Guidance and Open Source tooling to translated into HL7 CPG-on-FHIR to leverage derivative and native compute
  • tips:
    • Use established standards and work with standards community (to understand and evolve as needed)
    • Engage consumers/ users early and often
    • Engage downstream vendors (e.g Terminology vendor USED in the EHRs) early
    • Just because everyone everyone is using the same terminology systems doesn't mean they're agreeing how to use the actual terms- this needs to be considered and addressed to make ecosystem/supply chain work properly (feedforward from Evidence, but also feedback of data semantics back into evidence)
    • Learn from related communities of practice (e.g. Agile Software Engineering)



Implement Guidance (e.g., as CDS, eCQMs)


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources
  • See output repositories for Make Guidance Computable



Current Standards



Emerging Standards



Initiatives
  • C19 Digital Guidelines WG developing and implementation guide for COVID-19 interventions



Tools/ Platforms



Other Best Practices


Analyze Care Results


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources



Search Strategies



Output Repositories



Current Standards



Emerging Standards


Initiatives



Tools/ Platforms


Other Best Practices



Leverage Results Analysis (e.g., for Quality Improvement, Reporting, and Evidence Generation)


General RecommendationsAnticoagulationTesting/TriageOther (Long COVID, Vaccine, Steroids)
Input Sources



Output Repositories



Current Standards


Emerging Standards



Initiatives


Tools/ Platforms



Other Best Practices



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