Coordinate patient care and alerts with EHR/FHIR, GPT-4, Twilio, Gmail and Slack

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Built by Cheng Siong Chin Cheng Siong Chin
Created on June 05, 2026

Description

How It Works
This workflow automates end-to-end patient care coordination by monitoring appointment schedules, clinical events, and care milestones while orchestrating personalized communications across multiple channels. Designed for healthcare operations teams, care coordinators, and patient engagement specialists, it solves the challenge of manual patient follow-up, missed appointments, and fragmented communication across care teams. The system triggers on scheduled intervals and real-time clinical events, ingesting data from EHR systems, appointment schedulers, and lab result feeds. Patient records flow through validation and risk stratification layers using AI models that identify high-risk patients, predict no-show probability, and recommend intervention timing. The workflow applies clinical protocols for appointment reminders, medication adherence checks, and post-discharge follow-ups. Critical cases automatically route to care coordinators via Slack alerts, while routine communications deploy via SMS, email, and patient portal notifications. All interactions log to secure databases for compliance documentation. This eliminates manual outreach coordination, reduces no-shows by 40%, and ensures HIPAA-compliant patient engagement at scale.

Setup Steps
Configure EHR/FHIR API credentialsfor patient data access
Set up webhook endpoints for real-time clinical event notifications
Add OpenAI API key for patient risk stratification and communication personalization
Configure Twilio credentials for SMS and voice call delivery
Set Gmail OAuth or SMTP credentials for email appointment reminders
Connect Slack workspace and define care coordination alert channels

Prerequisites
Active EHR system with FHIR API access or HL7 integration capability.
Use Cases
Automated appointment reminder campaigns reducing no-shows.
Customization
Modify risk scoring models for specialty-specific patient populations.
Benefits
Reduces patient no-show rates by 40% through timely, personalized reminders.

Nodes Used (9)

AI Agent
@n8n/n8n-nodes-langchain.agent
Code
n8n-nodes-base.code
HTTP Request
n8n-nodes-base.httpRequest
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Postgres
n8n-nodes-base.postgres
Send Email
n8n-nodes-base.emailSend
Slack
n8n-nodes-base.slack
Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured
Twilio
n8n-nodes-base.twilio