Skills Artificial Intelligence Evidence Search for Clinical Decision Support

Evidence Search for Clinical Decision Support

v20260423
openevidence-core-workflow-a
A comprehensive workflow designed for clinical professionals to search, retrieve, and synthesize medical evidence. It allows users to query clinical literature with specialized filters (e.g., specialty, evidence level), check potential drug interactions against patient profiles, and look up the latest specialty guidelines from major health organizations (like ACC/AHA, NICE). The output provides structured citations, confidence scores, and evidence grading to support informed clinical decision-making.
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Overview

OpenEvidence — Evidence Search & Retrieval

Overview

Primary workflow for OpenEvidence clinical evidence integration. Covers the core use case: searching clinical literature with evidence-level filters, retrieving structured citations with journal and year metadata, checking drug interactions against patient context, and looking up specialty guidelines from major bodies (ACC/AHA, ESC, NICE). Responses include confidence scores and evidence grading to support clinical decision making. All queries support specialty filtering to narrow results to relevant domains.

Instructions

Step 1: Search Clinical Evidence

const result = await client.query({
  question: 'What is the recommended treatment for acute migraine in adults?',
  context: 'emergency_department',
  evidence_level: 'high',
  specialty: 'neurology',
  max_citations: 10,
});

console.log('Answer:', result.answer);
console.log(`Confidence: ${result.confidence} | Evidence grade: ${result.grade}`);
result.citations.forEach(c =>
  console.log(`  [${c.journal}] ${c.title} (${c.year}) — Level ${c.evidence_level}`)
);

Step 2: Filter by Specialty and Date

const recent = await client.search({
  keywords: 'GLP-1 receptor agonist cardiovascular outcomes',
  specialty: 'cardiology',
  year_min: 2024,
  evidence_level: 'meta-analysis',
  limit: 20,
});
console.log(`Found ${recent.total} results`);
recent.results.forEach(r => console.log(`  ${r.title} (${r.journal}, ${r.year})`));

Step 3: Check Drug Interactions

const interactions = await client.interactions.check({
  medications: ['metformin', 'lisinopril', 'atorvastatin'],
  patient_context: { age: 65, conditions: ['diabetes', 'hypertension'] },
});

interactions.forEach(i =>
  console.log(`${i.drug1} + ${i.drug2}: ${i.severity} — ${i.description}`)
);
if (interactions.some(i => i.severity === 'major')) {
  console.warn('WARNING: Major interaction detected — review before prescribing');
}

Step 4: Guideline Lookup

const guidelines = await client.guidelines.search({
  condition: 'hypertension',
  source: ['ACC/AHA', 'ESC', 'NICE'],
  year_min: 2023,
});
guidelines.forEach(g =>
  console.log(`${g.source}: ${g.title} (${g.year}) — ${g.recommendation_class}`)
);

Error Handling

Issue Cause Fix
401 Unauthorized Invalid API key Verify key in Authorization: Bearer header
404 Not Found Unknown specialty code Use standard specialty slugs from /specialties
422 Validation Conflicting filter params Remove mutually exclusive filters
429 Rate Limited Exceeds 30 queries/min Back off per Retry-After header
Empty citations array Question too narrow Broaden search terms or lower evidence level

Output

A successful run returns evidence-backed answers with citations, drug interaction severity assessments, and guideline recommendations. Each response includes a confidence score and evidence grade for clinical decision support.

Resources

Next Steps

Continue with openevidence-core-workflow-b for patient case analysis and reporting.

Info
Name openevidence-core-workflow-a
Version v20260423
Size 3.64KB
Updated At 2026-04-28
Language