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

IssueCauseFix
401 UnauthorizedInvalid API keyVerify key in Authorization: Bearer header
404 Not FoundUnknown specialty codeUse standard specialty slugs from /specialties
422 ValidationConflicting filter paramsRemove mutually exclusive filters
429 Rate LimitedExceeds 30 queries/minBack off per Retry-After header
Empty citations arrayQuestion too narrowBroaden 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