reconciling-problem-lists
Deduplicate and reconcile OpenMed-extracted conditions into one clean active problem list with clinical status (active / resolved / historical). Use after NER and context resolution when the user wants a problem list, condition reconciliation, dedup of synonymous diagnosis mentions, or active-vs-resolved status from a note. Covers clustering synonymous mentions into one concept, excluding negated mentions, applying clinical context (historical / hypothetical / recent) to set status, and emitting a USCDI-Problem-shaped list. SNOMED CT concept grounding is user-supplied and out-of-process. Hand-
Profile →npx skills add maziyarpanahi/openmed --skill reconciling-problem-lists --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.
# Reconciling problem lists A single note mentions the same condition many ways — "DM2," "type 2 diabetes," "diabetes mellitus" — across PMH, HPI, and A&P, some negated, some historical. A usable **problem list** collapses those mentions into one concept per problem, drops what the patient does not have, and assigns a clinical status (active / resolved / historical). This skill turns OpenMed's per-mention entity stream plus ConText axes into that reconciled, de-duplicated list, shaped for USCDI "Problem" exchange. ## When to use - After `extracting-clinical-entities` and `resolving-clinical-context`, when the user wants a clean problem list, condition reconciliation, or dedup of repeated diagnosis mentions. - You need active-vs-resolved-vs-historical status per problem, not just raw mentions. - You are assembling a FHIR Condition list or a USCDI Problem element and need one entry per concept. ## Quick start ```python import openmed from openmed.clinical import resolve_span_context, NEGATED, HISTORICAL, HYPOTHETICAL note = ("PMH: type 2 diabetes, prior MI 2019 (resolved). " "A&P: poorly controlled DM2; denies chest pain.") ents = openmed.analyze_text(note, model_name="disease_detect
- When to use
- Quick start
- Workflow
- Hand-off to / from OpenMed
- Edge cases & gotchas
- Standards & references
What does the reconciling-problem-lists skill do?
Deduplicate and reconcile OpenMed-extracted conditions into one clean active problem list with clinical status (active / resolved / historical). Use after NER and context resolution when the user wants a problem list, condition reconciliation, dedup of synonymous diagnosis mentions, or active-vs-resolved status from a note. Covers clustering synonymous mentions into one concept, excluding negated mentions, applying clinical context (historical / hypothetical / recent) to set status, and emitting a USCDI-Problem-shaped list. SNOMED CT concept grounding is user-supplied and out-of-process. Hand-
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill reconciling-problem-lists --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.