What is langcare-quality-measures?

A workflow for calculating healthcare quality measures from electronic health-record data. HEDIS-style measures compare the patients who should receive care with those who have documented evidence of receiving it.

Use it to calculate measures such as diabetes control, blood-pressure control, cancer screening, depression screening, and statin treatment, then identify patients missing recommended care.

It shows performance rates, excluded patients, unmet care needs, and the difference between current results and a target.

langcare-quality-measures — Skill by langcare/langcare-mcp-fhir

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add langcare/langcare-mcp-fhir --skill quality-measures

Clone the repo

git clone --depth 1 https://github.com/langcare/langcare-mcp-fhir

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/quality-measures/github.svg)](https://agentmods.dev/skills/langcare/langcare-mcp-fhir/quality-measures)

Your own site

<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/quality-measures"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/quality-measures/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/langcare/langcare-mcp-fhir/quality-measures"><img src="https://agentmods.dev/badge/skills/langcare/langcare-mcp-fhir/quality-measures.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 802 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00069	$0.00802
Opus 5.5	$0.00028	$0.00321
Sonnet 5.5	$0.00014	$0.00160
Haiku 4.5	$0.00007	$0.00080

Measured 2mo ago against content hash cf550b13a4d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

langcare-quality-measures scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

cma/skills/population-health/quality-measures/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Quality Measure Dashboard

When to Use This Skill

Use when a clinician or quality team needs formal HEDIS/CMS quality measure calculations with denominator/numerator logic, benchmark comparison, and actionable gap lists.

Clinical Workflow

Select measures to calculate (default core set: A1c control, BP control, breast/colorectal cancer screening, depression screening, statin therapy)
For each measure, use fhir_search to build the denominator population from Condition/Patient resources per measure specification
Use fhir_search to identify and remove excluded patients (hospice, ESRD, bilateral mastectomy, etc.)
Use fhir_search to query numerator evidence: Observation (lab results), Procedure (screenings), DiagnosticReport (imaging)
Compute rates: Rate = Numerator / (Denominator - Exclusions) x 100
Compare against benchmarks (see references/hedis-measures.md)
Identify non-compliant patients (in denominator but not in numerator) as care gaps
Present dashboard with rates, targets, gap counts, and patient-level gap lists

FHIR Resources

Condition -- Denominator identification (diabetes, HTN diagnoses)
Patient -- Demographics for age/sex stratification
Observation -- Lab results (A1c, BP), screening scores (PHQ-9)
Procedure -- Screening procedures (colonoscopy, mammogram)
DiagnosticReport -- Screening results
MedicationRequest -- Medication-based measures (statin therapy)
Encounter -- Visit-based eligibility, hospice exclusions
Immunization -- Immunization measures

FHIR Query Examples

Pull Diabetes Patients (Denominator)

fhir_search(resourceType="Condition", queryParams="code=http://snomed.info/sct|44054006,http://snomed.info/sct|46635009&clinical-status=active&_count=500")

Pull A1c Results (Numerator)

fhir_search(resourceType="Observation", queryParams="code=http://loinc.org|4548-4&date=ge[measurement-year-start]&_sort=-date&_count=500")

Pull Mammograms (Numerator)

fhir_search(resourceType="DiagnosticReport", queryParams="code=http://loinc.org|24606-6&date=ge[27-months-ago]&_count=500")

Read the full file on GitHub · 69 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

references/hedis-measures.md 3.7 KB

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 69 lines · 69 tokens per session scan A cf550b13a4d2

Subscribe to this mod's changes

langcare-quality-measures is a skill published in the GitHub repository langcare/langcare-mcp-fhir (71 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 802 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Analytics and metrics Scientific

langcare-quality-measures next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
langcare-quality-measureslangcare/langcare-mcp-fhir	Skill	71	6mo ago	MIT	A	69	Claude Code, Codex
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