Korábbi változatok

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• Explore having VA/UMN teams serve as a core for addressing the goal; they each manage all facets of this supply chain and also consume its results via CDS interventions that support care for their patient populations.
  • Cultivate synergies between these 'full cycle' efforts and related Collaborative participant efforts - e.g., NACHC (testing/triage in health centers), ACEP/EvidenceCare COVID-19 Severity Classification/Triage/Disposition tool (see here), Australia Living COVID-19 Guidelines (anticoagulation), U Melbourne COVID-CARE and related efforts, etc.
  • Have teams responsible in each of these organizations for evidence surveillance/synthesis, guidance development/updating, and CDS development/updating/deployment collaborate among themselves and with other organizations in the Collaborative on this 'update notification' process and tooling.
• Consider ways to coordinate/advance current efforts:  SRDR/COKA, C19HCC Digital Guideline WG, COVID-NMA, COVID-END, AU Living Guidelines, and related efforts to produce triggering system that suggests to living CDS owners/implementers that updates should be considered.
  • see sampling below that could be leveraged
• Document how evidence/guidance changes are detected and addressed in current VA/UMN/other processes
  • exploring enhancing these approaches to include a scalable notification function that propagates supply chain updates to all pertinent stakeholders throughout the chain, including those responsible for developing/maintaining CDS interventions.  
• Phased enhancement approach
  • Synthesize a largely manual update detection and notification mechanism that runs throughout the supply chain
  • Begin automating portions of the manual process (e.g., leverage pilot 'web difff tool' to detect changes on target web pages)
  • Fully automate approach leveraging computable, standards-based, interoperable information throughout the supply chain (build on COKA/SRDR explorations)

Sampling of External Sources to Check for Updated Evidence/Guidance on Targets

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• Note from Jens Jap, SRDR Team: "my team is interested in ... the development of automated literature searches to assist in SR updates or at least signal an opportunity for one. A preliminary step to this effort was the development of a RCT classifier. I think this is similar to what you previously referred to as COKA enhanced tagging tool, at least in nature. Using these kinds of machine learning assisted tools can bring us a step closer to more automation and living SRs. " Response from David Tovey: "In terms of an RCT Classifier, you may be interested to know that a tool with exactly this name has been developed by James Thomas and his team at UCL in London. It is currently in use within Cochrane but it might be useful to reach out to James if you are interested to explore this. ... The tool is capable of assessing large bundles of citation and abstracts very quickly with an accuracy level that is at least as good as could be achieved manually."

Teams:

• Document Current State: VA/UMN/Australia/others (business-driven requirements - what works, pain points, lessons learned)
• Improve Current State/low hanging fruit - e.g., through straightforward process/tool/resource enhancements to current processes
• Improve Current State/Architecture - more computable/standards-based processing

MN Current Process:

• 100 people looking at evidence on 25 targets - EBM Team
• Librarians running searches on different databased in different intervals. Ad hoc identify important papers that generate press. [Sandy - use DocSearch to identify this new information - searches clinicaltrials.gov, health rss feeds, WHO databases, pubmed, etc.]
• EBM team reviews literature, updates recommendations. Content expert team/system ops team decides what gets implemented. Teams are separate but trying to optimize going forward.
• Going forward, plan to coordinate more closely with EPC. They set up alerts about new info. Manually update SRDR with this new information. SS has team that makes ultimate decision.
  • MN EPC looking at how to abstract information from studies better to update guideline. How to automate processes better (PICO processing). 

MN Enhanced Process:

VA Current Process:

VA Enhanced Process:

D.2: Notes on a More Comprehensive Proof of Concept Software Toolset 

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