Streamlining Clinical Triage with AI
How we automated clinical triage using AI, saving 120 hours/mo.
The Challenge & Solution
The Challenge
HealthConnect Inc. faced a significant operational bottleneck in their clinical triage process, which involved manually reviewing each patient's data to prioritize clinical review tasks. Each day, multiple teams sifted through incoming patient reports, categorized them by urgency, and manually recorded the outcomes in their internal CRM. This labor-intensive process led to high error rates, inherent delays, and resource exhaustion. The manual nature of data entry resulted in frequent human errors, impacting both report accuracy and follow-up timelines. The existing SaaS solutions couldn't cope with HealthConnect's personalized data requirements and integration needs, leading to further complications.
- Pain point 1: The slow manual data entry resulted in a high error rate, leading to misprioritized clinical tasks.
- Pain point 2: Coordination across teams was delayed by manual communication, causing patient care delays.
- Pain point 3: Their scalability was limited by software licensing constraints and the inability to customize existing platforms.
The Solution
We developed a custom automation solution leveraging n8n and OpenAI, forming a seamless tech stack that managed data ingestion and analysis. FastAPI was used to create endpoints for secure data exchange, while n8n orchestrated the automation workflow. OpenAI's LLMs were implemented with tailored prompts for categorizing patient reports in structured formats. This system effectively prioritized triage cases, reducing manual oversight. A human-in-the-loop system allowed critical cases to be flagged via Slack, ensuring personalized attention when applicable. The solution synchronized processed data with HealthConnect's CRM, maintaining an accurate and up-to-date database.
- Solution pillar 1: FastAPI endpoints securely handled patient data to trigger workflow orchestration via n8n.
- Solution pillar 2: Custom OpenAI prompts and schemas extracted patient information, providing high accuracy categorization.
- Solution pillar 3: Integrated Slack notifications ensured human validation for flagged cases, maintaining oversight.
Execution & Deployment
Discovery & Mapping
We analyzed the existing workflow controls, documented database schemas, and established baseline error rates for comparison.
Pipeline Integration
We constructed n8n workflows, integrated API endpoints, configured JSON schemas, and conducted deployment trials to ensure effective system communication.
Optimization & Handover
System parameters were fine-tuned, alerting mechanisms were configured, team training was conducted, and the solution was transitioned smoothly into production.
Measurable Business Value
The automation not only cut manual triage time by 85%, allowing staff to focus more on direct patient care, boosting overall efficiency.
The automation solution freed up approximately 120 hours monthly which previously was spent on manual clerical work, significantly lowering labor costs.
By removing manual steps, redundancy was eliminated, ensuring a smooth and streamlined operation that required no double entry or review.
"The automation transformed our efficiency remarkably, freeing up crucial time for patient-focused care."
Dr. Sarah Thompson
VP of OperationsSystem & UI Mockups
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Based on the operational solutions implemented in this case study, we recommend auditing your own processes using these free tools:
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