Korábbi változatok

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• NIH anticoagulation adaptive clinical trials announced 9/20
• COVID-NMA (search for heparin)
• VA COVID Reviews (search for triage, testing, anticoagulation)
• L*VE Epistimonikos
• COVID END Best Evidence Synthesis (see testing/triage here, and others/anticoagulants here)
• NIH Guideline on Antithrombotic therapy
• CDC Phone Triage Guidance
• ACEP/EvidenceCare computable guidance on ED triage (based on this guide)
• AU Living Guidelines - see 'definition of disease severity' and 'VTE' [leaders of this effort are engaged in this exploration and they will send their processes (e.g., search tools/strategies)]
• IDSA Guideline on Serologic Testing (frequently updated)
• [other resources listed on Collaborative's evidence/guidance processing CoP page]
• 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
  • COKA WGs sorting out how to get messages from senders to receivers - could include notification that there's an update to evidence/guidance. Either sender has to decide what's important, or receiver needs express what they're looking for
  • UMN EPC thinking through process of what parts of evidence processing enhancement would be most helpful. 

COKA/SRDR

This is a draft list of the types of data that could be helpful to make the knowledge supply chain more efficient by making this data computable in ways that support automated update notification and evidence/guidance processing in the knowledge supply chain. COKA teams are working on ways to communicate these data in reusable interoperable standard form. If this ACTS exploration identifies a specific, high priority need for a standardized of version one or more of these items, the COKA teams developing these standards for data exchange and code systems can explore addressing this need as a priority in their work. The interplay in this area between the COKA and ACTS work are discussed in the COVID-19 Knowledge Accelerator (COKA) Knowledge Ecosystem Liaison Work Group, which meets Wednesday 8A ET (see here for WG details). 

• Citations that a new article exists -- Citation Resource
• Study design classifiers - Citation.classifier and Evidence.studyType but we are working on the Study Design Code System
• Population and Intervention classifiers -- Group Resource (used for Populations to harmonize with CDS artifacts from CPGonFHIR) and EvidenceVariable Resource
• Outcome classifiers - EvidenceVariable Resource
• Risk of Bias assessments -- Evidence.certainty.certaintySubcomponent but we are working on the Risk of Bias Code System
• Study Results -- Evidence Resource
• Synthesis Results -- Evidence Resource
• Summary of Findings (synthesis results plus certainty judgments) -- Evidence Resource and EvidenceReport Resource

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). 
  • What kind of tools are available to support more standard/excel data capture to speed up structuring of data pulled from reviews. Or does UMN need to create the structured file for input into SRDR. Looking at published trials and also studies underway. (3 ways to get data into SRDR: 1) abstract from studies as they are reviewed, 2) input from other systems (Distillr SR/excel) - most common).
  • interested in ML/NLP support for screening process - look at a wider set of study designs. Prioritize what will be helpful for the topic. (Abstractor builds a model to see if something is relevant to a target (deep learning/neural networks) - presents to user for screening. Being rolled into SRDR.) They are watching COVID-NMA, but not using it in their work at this point. Considering supporting anticoagulation for COVID-NMA work.

MN Enhanced Process:

For Anticoagulation - optimize work/output of people/process/technology:

DocSearch -> L*VE/Epistemonikos → Abstractor -> SRDR -> COVID-NMA > AU Living Guidelines → C19 Digital Guideline WG - UMN CDS Implementation Team → Evaluation → [back to beginning]

[How secure are funding sources for these efforts? How resilient are these. Idea is to map out a cross-cutting enhancement approach and how it's being implemented in individual sites. Provide additional information (links, descriptions, regular meetings, perhaps webinars) so everyone can learn more about the individual components and how they are being combined.]

VA Current Process/Needs:

 VA team is looking at improving screening. Here are some data points they are interested in:

• Is there a combination of symptoms on presentation that has a high correlation to PCR positive?
• Is there a combination of symptoms on presentation that has a high correlation to admission?
• Is there a combination of symptoms on presentation that has a high correlation to ICU admission?
• Is there a combination of symptoms on presentation that has a high correlation to requiring ventilation?

VA Enhanced Process: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
  • COKA WGs sorting out how to get messages from senders to receivers - could include notification that there's an update to evidence/guidance. Either sender has to decide what's important, or receiver needs express what they're looking for
  • UMN EPC thinking through process of what parts of evidence processing enhancement would be most helpful. 

Enhanced Process Template (under construction):

For Target - optimize work/output of people/process/technology:

DocSearch -> L*VE/Epistemonikos → Abstractor -> SRDR -> COVID-NMA > AU Living Guidelines → C19 Digital Guideline WG - UMN CDS Implementation Team → Evaluation → [back to beginning]

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

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