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Openevidence Core Workflow A
ASecurity'Execute OpenEvidence primary workflow: Clinical Query & Decision Support.
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- Added November 11, 2026
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[](https://www.skillsdirectory.com/skills/pauldx-openevidence-core-workflow-a)---
name: openevidence-core-workflow-a
description: 'Execute OpenEvidence primary workflow: Clinical Query & Decision Support.
Trigger: "openevidence clinical query & decision support", "primary openevidence
workflow".
'
allowed-tools: Read, Write, Edit, Bash(npm:*), Grep
version: 1.0.0
license: MIT
tags:
- saas
- openevidence
- healthcare
compatibility: Designed for Claude Code
---
# 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
```typescript
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
```typescript
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}, ${r.year})`));
```
### Step 3: Check Drug Interactions
```typescript
const interactions = await client.interactions.check({
medications: ['metformin', 'lisinopril', 'atorvastatin'],
patient_context: { age: 65, conditions: ['diabetes', 'hypertension'] },
});
interactions.forEach(i =>
console.log(`${i.drug1} + ${i.drug2}: ${i.severity} — ${i.description}`)
);
if (interactions.some(i => i.severity === 'major')) {
console.warn('WARNING: Major interaction detected — review before prescribing');
}
```
### Step 4: Guideline Lookup
```typescript
const guidelines = await client.guidelines.search({
condition: 'hypertension',
source: ['ACC/AHA', 'ESC', 'NICE'],
year_min: 2023,
});
guidelines.forEach(g =>
console.log(`${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
- [OpenEvidence Platform](https://www.openevidence.com)
- [OpenEvidence API Documentation](https://docs.openevidence.com)
## Next Steps
Continue with `openevidence-core-workflow-b` for patient case analysis and reporting.
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