Korábbi változatok

• Quickly identify/select evidence pertinent to topic (e.g., PICO-based inclusion criteria for a study)
• Data extraction (e.g., results: numerators/ denominators, aggregate measures) from studies is labor intensive and error prone
• Identify research gaps that require additional attention

• computable expressions for PICO criteria (now working on outcome definition component); if evidence has standardized PICO tags, it will be faster to identify/select evidence.
• computable expressions for results (statistics); if evidence has standardized, structured results reported it will be faster and more accurate to extract/upload data into review authoring tool
• If evidence is in a computable form, can better understand and describe nature of research gap (so it can be filled).

• A team (e.g., at NLM?) uses a pilot COKA-enabled tool to identify and apply COKA tags to all studies (previous and emerging) related to COVID-19 and anticoagulation, triage. [e.g., leverage Doc Search, other tools on Evidence/Guidance CoP page to identify the pertinent evidence]
• EPCs (e.g., UMN for anticoagulation, ? others for other targets) use a pilot COKA-enhanced version of SRDR+ to produce living systematic reviews.
• Systematic reviewers are proactively notified when there are new studies so that updates to the systematic reviews can be considered. 

• Cochrane registry has PICO tags (as do other systems), but since these aren't standardized, info can be missed. (searching Cochrane on 'diaper rash' may not find evidence tagged as 'nappy rash' - standard disease codes would address this)
• SRDR has FHIR-based expression of outcome. COKA has outcome definition viewer coming soon. With SRDR-defined outcome tags and Cochrane-defined outcome tags mapped to the same standard, a search in one system can find evidence in the other system.  
• Identify communities that might do a test to refine AI algorithms to do these kinds of tags [Lisa Lang for more details]
• Could start with simple, higher-level structures to get things rolling, then, over time make the standards more finer grained regarding PICO details.

• Need to quickly/easily determine (e.g., within/ across systematic reviews) judgements about quality of evidence and certainty of findings. This is problematic because different systematic reviews express these in different ways, making this critical information difficult to assess within and across reviews.

• computable expression for evidence certainty (certainty assessments and reasons for these assessments); 

• Guideline developers (e.g,. SCCM/ASH for anticoag, ACEP for ED triage, ? CDC for ambulatory triage) use a pilot COKA-enabled tool to produce living, computable guidance (e.g., building on the type of functionality AU Living Guidelines has implemented with MAGICapp - see anticoagulation example)
• Guideline developers are proactively notified when there's an update to systematic reviews so that updates to the guidance can be considered. 

• C19HCC Agile Knowledge Engineering Teams use the pilot COKA-enabled tool that produces living, computable guidance to drive updating of living CDS interventions and related eCQMs
• Teams are proactively notified when there's an update to the guidance so that updates to the CDS/eCQMs can be considered. 

• Care delivery participants need mechanisms to convey priority needs for which they need guidance/support to those who are producing that information.

• Those who provide evidence (e.g., study authors) capture data using standard PICO tags so that after-publication coding isn't required. Reserach funder (NIH, PCORI could require this. Have ACEP pilot this with triage-related articles in JACEP?)

[cautionary note: getting structure into journal articles (e.g., structured abstracts) have been challenging - perhaps even more challenging for this level of standardization]