mcpbeat

Case Summary

nvidia/case-summary

Prepare a complete clinical case summary for a patient from FHIR endpoints. Use when asked to summarize a patient, compile a case, or prepare for tumor board.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
1211
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/NVIDIA/dgx-spark-playbooks --skill case-summary

The instruction itself

2 sections, as written by the author

Prepare a complete case summary for $ARGUMENTS

Use your fhir-basics skill to query the FHIR endpoints. Use your clinical-knowledge skill to flag abnormal values and identify relevant clinical context.

Steps

  • Find the patient -- Query GET /Patient?name={name}&_count=5 or GET /Patient?_count=1 for "first patient". Extract id, full name, birthDate, gender.
  • Get active conditions -- Query GET /Condition?patient={id}&clinical-status=active. Extract each condition's display name, SNOMED/ICD code, onset date, and verification status. Also query for resolved conditions and list them separately (they provide clinical history context).
  • Get recent labs -- Query GET /Observation?patient={id}&category=laboratory&_sort=-date&_count=50. "Recent" means the most recent value for each distinct LOINC code within the past 12 months. For each lab, report: name, value, unit, date, and whether it's normal/abnormal per the clinical-knowledge skill. If the Observation includes a referenceRange, use that for flagging.
  • Get recent vitals -- Query GET /Observation?patient={id}&category=vital-signs&_sort=-date&_count=20. For blood pressure, handle the component Observation format (LOINC 85354-9 panel with systolic/diastolic in component[]). Report the most recent BP, heart rate, BMI, temperature.
  • Get current medications -- Query GET /MedicationRequest?patient={id}&status=active. For each medication, report: drug name, dosage text, and drug class (per clinical-knowledge skill). Organize by drug class when possible.
  • Get recent encounters (optional but adds context) -- Query GET /Encounter?patient={id}&_sort=-date&_count=5. Report type, date, and reason if available. This shows how recently the patient was seen.
  • Compile the case summary with these sections:
  • Demographics: Name, age (calculated from birthDate), gender, address if available
  • Active Conditions: With codes and onset dates
  • Resolved Conditions (if any): Brief list for clinical history
  • Recent Labs: Grouped by category (metabolic, lipids, renal, hematology), abnormal values highlighted
  • Recent Vitals: Most recent BP, HR, BMI
  • Current Medications: With drug class annotations
  • Clinical Flags: Any abnormal values, potential care gaps (e.g., diabetic patient without A1c in 12 months, hypertensive with uncontrolled BP), or comorbidity patterns worth noting
  • Disclaimer: "This summary is auto-generated from FHIR data for research and operational use. Verify all information before clinical decision-making."

Output Format

============================================================
PATIENT CASE SUMMARY
============================================================
Generated: {date/time}
Source: {FHIR endpoint URL}

DEMOGRAPHICS
  Name:     {full name}
  Age:      {age} years (DOB: {birthDate})
  Gender:   {gender}

ACTIVE CONDITIONS ({count})
  1. {display} (SNOMED {code}) -- onset {date}
  2. ...

RESOLVED CONDITIONS ({count})
  1. {display} -- resolved

RECENT LABS (most recent per test, past 12 months)
  Metabolic:
    HbA1c:          {value}% ({date})     ⚠ ABOVE TARGET (>7.0%)
    Fasting Glucose: {value} mg/dL ({date}) -- Normal
  Renal:
    Creatinine:     {value} mg/dL ({date}) -- Normal
    eGFR:           {value} mL/min ({date}) -- Normal
  Lipids:
    LDL:            {value} mg/dL ({date})  ⚠ ELEVATED (>100)
    ...

RECENT VITALS
  Blood Pressure: {systolic}/{diastolic} mmHg ({date})
  Heart Rate:     {value} bpm ({date})

CURRENT MEDICATIONS ({count})
  Diabetes:
    - Metformin 1000mg twice daily
  Antihypertensive:
    - Lisinopril 20mg daily
  Statin:
    - Atorvastatin 40mg daily

CLINICAL FLAGS
  ⚠ HbA1c 9.2% indicates poor glycemic control (CMS122 gap)
  ⚠ LDL 165 mg/dL above target for diabetic patient
  ✓ On statin therapy (appropriate for diabetes + elevated LDL)
  ✓ On ACE inhibitor (appropriate for diabetes + hypertension)

============================================================
Disclaimer: This summary is auto-generated from FHIR data
for research and operational use. Verify all information
before clinical decision-making.
============================================================

How to use it

Copy the folder

Take nvidia/case-summary from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.