Korábbi változatok

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Those providing data for these tables should consider, "What do you want those who seek to implement 'living guidance' to know about 'data-to-evidence' strategies, initiatives and tools to make their efforts more successful? Likewise, "What do you want to know about efforts of others working in the knowledge ecosystem to make your data-to-knowledge efforts more successful?"

10/23 Data to Evidence Session:

• Recording

Notes from 10/22/20 Kick-off Call for Community

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• Note from Maria in a separate email after this call as part of a different exchange, but related: "The piece that I brought up is in addition to CPG-on-FHIR. CPG-on-FHIR is about how to create a faithful representation of the guidelines/guidance in computable form (i.e., the computable guideline) and then develop derivatives (e.g., CDS, eCQMs/dQMs, case reports) from the computable guideline. Those items are used to pull together data, for example, from an EHR to meet certain business rules, etc., but there’s also the piece about having the means to exchange with other organizations (e.g., from an EHR (or multiple EHRs) to a registry). That’s the piece that MedMorph brings into the picture for research and public health (eCQMs have the DEQM which is specific to quality measures). This needs to be part of the picture otherwise we’re not moving the data from one entity to another to be able to do the kinds of multi-organizational analyses that we talked about today. All of these pieced fit together (e.g., CPG-on-FHIR, MedMorph, EBM-on-FHIR, even DEQM) because we’ve been working hard to keep them aligned everywhere it makes sense to do so and highlight complementarity where it makes sense to do so… it’s just a matter of making it clearer in this ACTS work so we’re all working off the same playbook."

Follow-up email about this meeting from Brian Alper:

If trying to develop a “tool 5” or a tool to facilitate Data-to-Evidence data exchange a next step could be to consider which of the following “tools” is most desired up front, and other tools may be added as the ecosystem develops.  In this context I used the term “study” to broadly describe the data collection and analysis to produce the evidence, regardless of study quality or whether it is called a study in common language.

1. A tool to share the “study protocol” – the definitional/instructional/guidance concepts not specific to the individual participants, similar in a structural sense to sharing the “guideline”
2. A tool to share the “research subject” – the identifying knowledge artifact that can identify the study participant and provide the links (with necessary security and anonymity) to recognizable identifiers, consent documentation if necessary, and contact information if necessary.
3. A tool to share the “research data” – data in the form needed for a usable dataset for the study
4. A tool to convert “real-world observations” (eg EHR data not captured for research purposes) to “research data”
5. A tool to facilitate “data analysis” – a tool to process the dataset and produce “evidence” (summary of analysis results)

There are multiple large efforts doing things in this area --- much still to be done but it should not be starting from scratch – but it may take a while to figure out which of the various efforts are a “good fit” and “open to collaboration”.

Notes from 10/16-19/20 email exchange

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