Under ConstructionEvolving Description of ACTS Collaborative Participant's COVID-19 Knowledge Ecosystem Efforts
| Identify Studies | Review Evidence |
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Current Approach | |
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| Pearls/Tips Learned |
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| Desired Approach |
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| Needs to Achieve Desired Approach | Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:]
| Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:] |
| Support We Can Provide Other Participants |
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| Produce Guidance | Make Guidance Computable |
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Current Approach | - (Brian Fengler to edit)
- Content Team, part of C19 Digital Guideline Working Group, consisting of frontline clinicians and representatives from professional societies and evidence ecosystem participants
- Content Team identifies need, prioritizes areas of focus, and participants form and lead the use case-specific Agile CPG Teams
- Using the Agile Approach to CPG Development (inclusive of Integrated Process) to concurrently Produce Guidance and Make Guidance Computable in Agile CPG Team
| - 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
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| Pearls/Tips Learned | - Collaborate with Frontline clinicians (target users) AND Content Experts (domain and methodological) in an integrated, concurrent fashion
- Collaborate directly (integrated with as part of Agile CPG Team) with the Knowledge Engineering Team to Make Guidance Computable
- Clarify INTENT of Guidance to KE's
- Address ambiguity in narrative Guidance based on clarifications needed for KE (make content more accurate, less ambiguous)
| - 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)
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| Desired Approach |
| - Build computable artifacts/assets on Real-World data to enable better design/ specification and Test-driven Development (Agile)
- Leverage mature Knowledge Base to implement Knowledge Architecture (e.g. CPG profiles) and design, develop, test, maintain, and reuse artifacts/ assets
- Concurrent Validation and Development using above
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| Needs to Achieve Desired Approach | Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:] | Check all that apply (in process) x__Better source/input materials [Details:] Helps if Evidence is EBM-on-FHIR x__Common format/terminologies for managing/sharing data [Details: ] Complete, Accurate, Unambiguous Data Definitions __Other [Details:] To Be Continued... |
| Support We Can Provide Other Participants |
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| Implement Guidance (e.g., as CDS, eCQMs) | Analyze Results (e.g., care outcomes) | Apply Results (e.g., Quality Improvement, create evidence) |
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Current Approach | |
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| Pearls/Tips Learned |
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| Desired Approach |
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| Needs to Achieve Desired Approach | Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:] | Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:] | Check all that apply __Better source/input materials [Details: ] __Common format/terminologies for managing/sharing data [Details: ] __Other [Details:] |
| Support We Can Provide Other Participants |
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Excerpts from 9/4/20 email exchange about using computable/standards-based evidence descriptions to make developing and updating computable, evidence-based clinical recommendations more efficient/effective.
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