Korábbi változatok

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The HL7 CPG IG is not first and foremost CDS, its very much intended to be a computer-interpretable expression of the guideline itself; then with: 1) the means to derive highly related artifacts such as ECA-Rule-based CDS, patient-specific, practice-level metrics that *may* be rolled up into Quality Measures, eCaseReports to provide all the detail of guideline ‘execution’ at the patient-level (when they met criteria for a recommendation, when CDS notified the clinician of the proposed action, when/if clinicians took said action [order/request], when said proposal or request was fulfilled [whether evidence of request or not], any desired metrics that were captured and how they may have evolved over time [e.g. “on/off path”, “on with a history of off”], and any provider Impressions that may qualify any of the afore mentioned); and 2) lots of human consumable narrative on how to implement an HL7 CPG across its entire lifecycle (from working with Guideline Developers & the Evidence Ecosystem to working with local Practices and their informatics and EHR teams, and numerous other ecosystem touchpoints between- not the least of which is getting the data semantics as applied in point of care clinical information systems nailed- not just a bunch of terms hurled at ehr’s).  Not sure if it is the name, the specification, how we have presented it to date, or some other factor, but that the HL7 Clinical Practice Guideline Implementation Guide describes the process and patterns that afford the means to computationally express the intent of the guideline is a point oft missed.

F.  Notes from 9/18/20 Weekly Call

Pawan Goyal: ACEP has a blog where more than 4,000 Emergency Physicians participate across the globe to share their experiences. ACEP meets with CDC, CMS, NIH, and FDA on regular basis. Our Clinical Policies Committee and Clinical Practices Committee collect evidence/knowledge and review/approve them on periodic basis.

Matt Burton:  Citation analysis can give some linkage... EMB-on-FHIR and CPG-on-FHIR retain provenance (incl to citations)...  linkage analysis can ASSIST, but still need human in loop at some point there are some "semantic linkages" that can be leveraged, but just used to associate...  Sensitivity/ Specificity issue for "relevance", Motive, Stanson, and other CDS vendors live and breathe these types of approaches. Potentially with citation analysis Preston.

Sivaram Arbandi: Information can be open-world, but when it comes to knowledge it will need to be closed-world.

David Tovey:  A resource that has not been mentioned on this call is the L*VE Epistemonikos platform, which tracks all new studies and reviews and includes a very strong search facility that could be used to track new studies looking at clinical predition rules or anticoagulation interventions for example. https://app.iloveevidence.com/loves/5e6fdb9669c00e4ac072701d?utm=ile

Maria Michaels: Link to all the checklists: http://build.fhir.org/ig/HL7/cqf-recommendations/checklists.html. Link to the L4 checklist: http://build.fhir.org/ig/HL7/cqf-recommendations/L4Checklist.html.

Brian Alper: If the data to transfer for updating is put into a standard structure, then a computer can manage a "subscription service" to notify people when the data changes per some parameters.  A FHIR subscription service could be used if the data is put in FHIR on a FHIR server.  If you select a specific type of data for piloting we can explore FHIR tooling for this purpose.

Sandra Zelman Lewis: DOC Search (https://covid-search.doctorevidence.com/) is also a way to search and monoitor PubMed (31.6 million), ClinicalTrials.gov (351,984), COVID-19 Open Research Dataset (197,184), DailyMed (128,431), EPAR (1,502), WHO-ICTRP (648,473), and RSS feeds (870,546 from 491 feeds). You can set up alerts if matches to your search terms.

David Tovey: Indeed Sandy, and also DOC Analytics for automating meta-analysis.  Emails:  daviditovey@gmail.com and Gabriel Rada: radagabriel@gmail.com