---

name: openevidence-core-workflow-a description: | Execute OpenEvidence clinical query workflow for point-of-care decisions. Use when implementing real-time clinical decision support, building EHR-integrated evidence lookups, or point-of-care queries. Trigger with phrases like "openevidence clinical query", "point of care", "quick clinical lookup", "evidence search". allowed-tools: Read, Write, Edit, Bash(npm:*), Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

OpenEvidence Core Workflow A: Clinical Query

Overview

Primary workflow for real-time clinical queries at the point of care. Returns evidence-based answers in 5-10 seconds with peer-reviewed citations.

Prerequisites

• Completed openevidence-install-auth setup
• Understanding of clinical decision support patterns
• Valid API credentials configured

Use Cases

• Drug interaction checks during prescribing
• Treatment protocol lookups
• Differential diagnosis support
• Dosing verification
• Clinical guideline queries

Instructions

Step 1: Structure the Clinical Query

// src/workflows/clinical-query.ts
import { OpenEvidenceClient } from '@openevidence/sdk';

interface ClinicalQueryRequest {
  question: string;
  specialty: string;
  urgency: 'stat' | 'urgent' | 'routine';
  patientContext?: {
    age?: number;
    sex?: 'male' | 'female';
    conditions?: string[];
    medications?: string[];
  };
}

interface ClinicalQueryResponse {
  answer: string;
  citations: Citation[];
  confidence: number;
  responseTimeMs: number;
  queryId: string;
}

interface Citation {
  source: string;
  title: string;
  year: number;
  doi?: string;
  guideline?: boolean;
}

Step 2: Implement Query Service

// src/services/point-of-care-query.ts
import { OpenEvidenceClient } from '@openevidence/sdk';

const client = new OpenEvidenceClient({
  apiKey: process.env.OPENEVIDENCE_API_KEY,
  orgId: process.env.OPENEVIDENCE_ORG_ID,
  timeout: 15000, // 15 second timeout for point-of-care
});

export async function queryAtPointOfCare(
  request: ClinicalQueryRequest
): Promise<ClinicalQueryResponse> {
  const startTime = Date.now();

  const response = await client.query({
    question: request.question,
    context: {
      specialty: request.specialty,
      urgency: request.urgency,
      ...(request.patientContext && {
        patientAge: request.patientContext.age,
        patientSex: request.patientContext.sex,
        relevantConditions: request.patientContext.conditions,
        currentMedications: request.patientContext.medications,
      }),
    },
    options: {
      maxCitations: 5,
      includeGuidelines: true,
      prioritizeRecent: true, // Prefer evidence from last 3 years
    },
  });

  return {
    answer: response.answer,
    citations: response.citations.map(c => ({
      source: c.source,
      title: c.title,
      year: c.year,
      doi: c.doi,
      guideline: c.type === 'guideline',
    })),
    confidence: response.confidence,
    responseTimeMs: Date.now() - startTime,
    queryId: response.id,
  };
}

Step 3: Drug Interaction Check Example

// src/workflows/drug-interaction.ts
export async function checkDrugInteraction(
  drug1: string,
  drug2: string,
  patientContext?: { age?: number; conditions?: string[] }
): Promise<{
  hasInteraction: boolean;
  severity: 'major' | 'moderate' | 'minor' | 'none';
  details: string;
  citations: Citation[];
}> {
  const response = await queryAtPointOfCare({
    question: `What are the drug interactions between ${drug1} and ${drug2}?`,
    specialty: 'pharmacology',
    urgency: 'urgent',
    patientContext,
  });

  // Parse severity from response
  const severity = determineSeverity(response.answer);

  return {
    hasInteraction: severity !== 'none',
    severity,
    details: response.answer,
    citations: response.citations,
  };
}

function determineSeverity(answer: string): 'major' | 'moderate' | 'minor' | 'none' {
  const lower = answer.toLowerCase();
  if (lower.includes('contraindicated') || lower.includes('major interaction')) return 'major';
  if (lower.includes('moderate interaction') || lower.includes('caution')) return 'moderate';
  if (lower.includes('minor interaction')) return 'minor';
  if (lower.includes('no significant interaction') || lower.includes('no known interaction')) return 'none';
  return 'moderate'; // Default to moderate if unclear
}

Step 4: EHR Integration Pattern

// src/integrations/ehr-hook.ts
import { queryAtPointOfCare } from '../services/point-of-care-query';

// HL7 FHIR CDS Hooks integration
interface CDSRequest {
  hook: string;
  hookInstance: string;
  context: {
    patientId: string;
    encounterId?: string;
    medications?: any[];
  };
}

interface CDSResponse {
  cards: CDSCard[];
}

interface CDSCard {
  summary: string;
  detail: string;
  indicator: 'info' | 'warning' | 'critical';
  source: { label: string; url?: string };
  suggestions?: any[];
}

export async function handleCDSHook(request: CDSRequest): Promise<CDSResponse> {
  // Extract clinical context from FHIR resources
  const medications = request.context.medications?.map(m => m.medicationCodeableConcept?.text) || [];

  // Query OpenEvidence for relevant clinical information
  const evidence = await queryAtPointOfCare({
    question: buildClinicalQuestion(request.hook, medications),
    specialty: 'family-medicine',
    urgency: 'routine',
    patientContext: {
      medications,
    },
  });

  return {
    cards: [{
      summary: 'Clinical Evidence Available',
      detail: evidence.answer,
      indicator: evidence.confidence > 0.9 ? 'info' : 'warning',
      source: {
        label: 'OpenEvidence',
        url: 'https://openevidence.com',
      },
    }],
  };
}

function buildClinicalQuestion(hook: string, medications: string[]): string {
  switch (hook) {
    case 'medication-prescribe':
      return `Are there any drug interactions or contraindications for ${medications.join(', ')}?`;
    case 'order-sign':
      return `What are the clinical considerations for prescribing ${medications.join(', ')}?`;
    default:
      return `Provide clinical guidance for patient on ${medications.join(', ')}`;
  }
}

Output

• Real-time clinical query response (5-10 seconds)
• Evidence-based answer with peer-reviewed citations
• Confidence score for clinical decision support
• Query audit trail for compliance

Error Handling

Error	Cause	Solution
Timeout	Complex query or network	Increase timeout, simplify question
Low confidence	Ambiguous query	Rephrase with more specific context
No citations	Rare condition	Consider DeepConsult for deeper research
Rate limit	Too many queries	Implement request queuing

Performance Considerations

• Target response time: < 10 seconds for point-of-care
• Cache frequent queries (drug info, guidelines)
• Pre-warm connections during low-traffic periods
• Use streaming responses for faster perceived performance

Examples

Complete Point-of-Care Integration

// Example: Emergency department workflow
async function edClinicalSupport(chiefComplaint: string, vitals: any) {
  const queries = await Promise.all([
    queryAtPointOfCare({
      question: `What is the differential diagnosis for ${chiefComplaint}?`,
      specialty: 'emergency-medicine',
      urgency: 'stat',
    }),
    queryAtPointOfCare({
      question: `What workup is recommended for ${chiefComplaint}?`,
      specialty: 'emergency-medicine',
      urgency: 'stat',
    }),
  ]);

  return {
    differential: queries[0],
    workup: queries[1],
  };
}

Resources

• OpenEvidence
• HL7 CDS Hooks
• SMART on FHIR

Next Steps

For comprehensive research queries, see openevidence-core-workflow-b (DeepConsult).