computing-ecqms
Compute electronic clinical quality measures (eCQMs) over structured data using CQL/QDM logic, lifting note-derived numerator and exclusion facts from OpenMed to improve measure capture. Use when the user wants to compute an eCQM, evaluate a CMS/ECQI quality measure, improve numerator capture from clinical notes, build CQL/QDM measure logic, or close documentation gaps that structured codes miss. Covers eCQM structure (IPP/denominator/numerator/exclusions), CQL v1.5 and QDM v5.6, MADiE authoring, and mapping OpenMed entities to QDM data elements. Consumes OpenMed analyze_text facts (coded via
npx skills add maziyarpanahi/openmed --skill computing-ecqms --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Computing eCQMs Electronic Clinical Quality Measures (eCQMs) are computed over structured data using **CQL** (Clinical Quality Language) logic against the **QDM** (Quality Data Model). Much of what a measure needs — a counseling note, a reason a service wasn't done, a symptom — lives only in **free text**. This skill uses OpenMed to lift those facts out of notes (on-device) and feed them into measure computation so numerators and valid exclusions aren't undercounted. ## When to use this skill When structured codes under-capture a measure population and the evidence is in notes: documented exclusions ("patient declined screening"), numerator-relevant findings, or symptoms gating a measure. Use it *alongside* a certified measure engine — OpenMed supplements capture; it does not compute or certify the measure. ## eCQM anatomy (what you're populating) | Population | Meaning | Where OpenMed helps | | --- | --- | --- | | IPP (Initial Population) | everyone the measure could apply to | usually structured (encounters, age) | | Denominator | IPP meeting base criteria | mostly structured | | Denominator Exclusion / Exception | valid reasons to remove from denom | **notes**: "declined", "me
- When to use this skill
- eCQM anatomy (what you're populating)
- Quick start
- Workflow
- Hand-off to / from OpenMed
- Edge cases & gotchas
- Standards & references
What does the computing-ecqms skill do?
Compute electronic clinical quality measures (eCQMs) over structured data using CQL/QDM logic, lifting note-derived numerator and exclusion facts from OpenMed to improve measure capture. Use when the user wants to compute an eCQM, evaluate a CMS/ECQI quality measure, improve numerator capture from clinical notes, build CQL/QDM measure logic, or close documentation gaps that structured codes miss. Covers eCQM structure (IPP/denominator/numerator/exclusions), CQL v1.5 and QDM v5.6, MADiE authoring, and mapping OpenMed entities to QDM data elements. Consumes OpenMed analyze_text facts (coded via
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill computing-ecqms --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.