drug-interaction-checker

name	drug-interaction-checker
description	Checks active medications for drug-drug interactions by pulling all MedicationRequests and cross-referencing known interaction pairs with severity classification and CYP450 pathways. Use when user asks to "check drug interactions", "check for interactions", "are these medications safe together", mentions "drug-drug interaction", "CYP450", or needs interaction screening. Do NOT use for medication reconciliation, adherence, or single drug information lookups.
metadata	{"author":"LangCare","version":"1.0.0","mcp-server":"langcare-mcp-fhir","category":"medication-management"}

Drug Interaction Checker

Overview

Pull all active medications for a patient, cross-reference each pair against known major drug-drug interaction databases, classify by severity (contraindicated, major, moderate, minor), identify CYP450 pathway conflicts, and suggest therapeutic alternatives when significant interactions are detected.

FHIR Resources Used

Resource	Purpose	Key Fields
MedicationRequest	Active prescribed medications	status, medicationCodeableConcept, dosageInstruction
MedicationStatement	Patient-reported medications including OTC	status, medicationCodeableConcept, dosage
Patient	Patient demographics, age for risk stratification	birthDate, gender
Condition	Comorbidities affecting interaction severity	code, clinicalStatus
Observation	Renal/hepatic function affecting drug metabolism	code, valueQuantity
AllergyIntolerance	Cross-sensitivity patterns	code, reaction

Instructions

Step 1: Verify Patient and Retrieve Demographics

Tool: fhir_read
resourceType: "Patient"
id: "[patient-id]"

Extract age, gender, weight if available. Age and organ function affect CYP450 metabolism rates.

Step 2: Pull All Active Medications

2a: Prescribed medications

Tool: fhir_search
resourceType: "MedicationRequest"
queryParams: "patient=[patient-id]&status=active&_count=100"

2b: Patient-reported medications (includes OTC, supplements)

Tool: fhir_search
resourceType: "MedicationStatement"
queryParams: "patient=[patient-id]&status=active&_count=100"

Merge both lists. Deduplicate by RxNorm code (system: http://www.nlm.nih.gov/research/umls/rxnorm).

Step 3: Pull Renal and Hepatic Function

Tool: fhir_search
resourceType: "Observation"
queryParams: "patient=[patient-id]&code=33914-3,48642-3,69405-9,77147-7&_sort=-date&_count=4"

LOINC codes:

• 33914-3: eGFR (CKD-EPI)
• 48642-3: eGFR for African American
• 69405-9: Glomerular filtration rate
• 77147-7: eGFR (CKD-EPI 2021)

Impaired renal/hepatic function reduces drug clearance and increases interaction risk.

Step 4: Build Medication Pair Matrix

For N active medications, evaluate N*(N-1)/2 unique pairs. For each pair, check against the interaction reference (see references/major-drug-interactions.md) in the following order:

1. Contraindicated combinations - Never co-prescribe
2. Major interactions - Significant clinical risk, avoid or monitor closely
3. Moderate interactions - Clinical significance in certain patients
4. Minor interactions - Limited clinical significance

Step 5: Evaluate CYP450 Pathway Conflicts

For each medication, identify its CYP450 profile (see references/cyp450-pathways.md):

• Is it a substrate (metabolized by the enzyme)?
• Is it an inhibitor (blocks the enzyme, increasing substrate levels)?
• Is it an inducer (accelerates the enzyme, decreasing substrate levels)?

Flag when:

• A strong inhibitor of CYP3A4 is combined with a CYP3A4 substrate with a narrow therapeutic index
• A strong inducer is combined with a substrate where reduced levels cause treatment failure
• Multiple inhibitors of the same pathway are present (additive inhibition)

Step 6: Classify and Report Interactions

For each identified interaction, report:

Field	Content
Drug A	Name, dose, RxNorm code
Drug B	Name, dose, RxNorm code
Severity	Contraindicated / Major / Moderate / Minor
Mechanism	Pharmacokinetic (CYP450, P-gp, renal) or Pharmacodynamic (additive, synergistic, antagonistic)
Clinical Effect	What happens (e.g., "increased bleeding risk", "QT prolongation")
Evidence Level	Established / Probable / Suspected / Possible
Management	Specific recommendation (avoid, adjust dose, monitor parameter, timing separation)
Alternative	Suggested substitute medication if available

Step 7: Generate Interaction Summary

Structure output:

1. Contraindicated Pairs (if any) - RED flag, require immediate prescriber attention
2. Major Interactions - ORANGE flag, require monitoring plan or alternative
3. Moderate Interactions - YELLOW flag, clinical judgment needed
4. Minor Interactions - Informational only
5. CYP450 Summary - Table of which enzymes are affected by current regimen
6. Recommended Actions - Prioritized list of changes

Step 8: Document Interaction Check (if requested)

Tool: fhir_create
resourceType: "DetectedIssue"
resource: {
  "resourceType": "DetectedIssue",
  "status": "preliminary",
  "code": {
    "coding": [{
      "system": "http://terminology.hl7.org/CodeSystem/v3-ActCode",
      "code": "DRG",
      "display": "Drug Interaction Alert"
    }]
  },
  "severity": "high",
  "patient": {"reference": "Patient/[patient-id]"},
  "identifiedDateTime": "[current-datetime]",
  "implicated": [
    {"reference": "MedicationRequest/[drug-a-id]"},
    {"reference": "MedicationRequest/[drug-b-id]"}
  ],
  "detail": "[interaction description]",
  "mitigation": [{
    "action": {"text": "[recommended action]"},
    "date": "[date]"
  }]
}

Examples

Example 1: Checking Interactions for a New Prescription

User says: "Check drug interactions for patient 67890 - about to start amiodarone."

Actions:

1. Read Patient 67890.
2. Pull active MedicationRequests: finds warfarin 5mg daily, simvastatin 40mg daily, metformin 1000mg BID, lisinopril 20mg daily.
3. Pull renal function: eGFR 55 mL/min (Stage 3a CKD).
4. Cross-reference amiodarone against each active medication.
5. Check CYP450: amiodarone is a strong inhibitor of CYP3A4, CYP2C9, CYP2D6, and P-glycoprotein.

Result:

DRUG INTERACTION CHECK - Patient 67890
New medication: Amiodarone

CONTRAINDICATED: None

MAJOR INTERACTIONS:
1. Amiodarone + Warfarin [MAJOR]
   Mechanism: Amiodarone inhibits CYP2C9, reducing warfarin metabolism
   Effect: INR increase of 50-70%, bleeding risk
   Management: Reduce warfarin dose by 30-50%. Check INR within 3-5 days, then weekly x4.

2. Amiodarone + Simvastatin [MAJOR]
   Mechanism: Amiodarone inhibits CYP3A4, increasing simvastatin levels
   Effect: Rhabdomyolysis risk. Simvastatin max dose with amiodarone is 20mg.
   Alternative: Switch to pravastatin 40mg (not CYP3A4 metabolized) or rosuvastatin 10mg.

MODERATE INTERACTIONS:
3. Amiodarone + Metformin [MODERATE]
   Mechanism: Amiodarone may increase metformin levels via OCT transporter inhibition
   Effect: Increased metformin exposure, lactic acidosis risk (especially with eGFR 55)
   Management: Monitor renal function closely. Consider metformin dose reduction.

CYP450 IMPACT:
- CYP3A4: STRONGLY INHIBITED by amiodarone (affects simvastatin)
- CYP2C9: STRONGLY INHIBITED by amiodarone (affects warfarin)
- CYP2D6: INHIBITED by amiodarone (no current substrates affected)

RECOMMENDED ACTIONS:
1. [URGENT] Reduce warfarin dose 30-50% before starting amiodarone
2. [URGENT] Switch simvastatin to pravastatin or reduce to 20mg max
3. [MONITOR] Renal function and metformin tolerance
4. [SCHEDULE] INR check 3-5 days after amiodarone start

Example 2: Routine Polypharmacy Interaction Screen

User says: "Screen all drug interactions for patient Jane Doe, DOB 1940-07-22."

Actions:

1. Search Patient by name and DOB. Confirm identity. Age 85.
2. Pull 14 active medications (polypharmacy).
3. Evaluate 91 unique pairs (14 choose 2).
4. Identify 3 major, 5 moderate, 2 minor interactions.
5. Note elderly patient - flag CYP450 metabolism decline with age.

Result:

DRUG INTERACTION SCREEN - Jane Doe (Age 85)
Total active medications: 14
Pairs evaluated: 91

MAJOR INTERACTIONS: 3
1. Clopidogrel + Omeprazole [MAJOR]
   Mechanism: Omeprazole inhibits CYP2C19, reducing clopidogrel activation
   Alternative: Switch to pantoprazole (weaker CYP2C19 inhibitor)

2. Methotrexate + Trimethoprim [MAJOR]
   Mechanism: Both cause folate depletion, additive bone marrow suppression
   Management: Avoid combination. If unavoidable, supplement with leucovorin.

3. Fluoxetine + Tramadol [MAJOR]
   Mechanism: Serotonin syndrome risk (both serotonergic). Fluoxetine inhibits CYP2D6, reducing tramadol conversion to active metabolite.
   Alternative: Switch tramadol to acetaminophen or non-serotonergic analgesic.

MODERATE INTERACTIONS: 5
[... listed with management ...]

AGE-RELATED CONSIDERATIONS:
- CYP450 activity reduced ~30% at age 85
- Renal clearance likely reduced (check eGFR)
- Polypharmacy (14 meds) increases interaction probability
- Recommend comprehensive prescription appropriateness review

Troubleshooting

Medication codes are not in RxNorm

• Use medicationCodeableConcept.text for name-based matching against interaction tables.
• If medication is a contained reference, resolve via fhir_read on the referenced Medication resource.
• Note in output that coded interaction checking was not possible for unrecognized medications.

Patient has very large medication list (>20 medications)

• Prioritize pairs involving high-alert medications (anticoagulants, antiarrhythmics, opioids, immunosuppressants).
• Focus on contraindicated and major interactions first.
• Present interactions grouped by severity rather than listing all 190+ pairs.

Interaction found but clinical significance is unclear

• Report the interaction with its evidence level (Established/Probable/Suspected/Possible).
• Include the mechanism so the clinician can assess applicability.
• Note patient-specific factors that modify risk (renal function, age, duration of concurrent use).

Related Skills

• medication-reconciliation - Reconcile medication list before running interaction check
• prescription-appropriateness-review - Broader appropriateness review beyond interactions
• opioid-risk-assessment - Focused assessment when opioid interactions detected
• problem-list-review - Review conditions that affect interaction severity