Healthcare Patient Flow Optimizer
Automate appointment scheduling, patient intake forms, and follow-up communications for multi-location clinics.
AI Readiness Score
Data scattered across systems
Non-technical team needs support
Strong budget for the scope
Clear automation targets
6-month timeline gives room
Mixed API availability
How This System Works
Architecture
The CareFirst Clinics AI deployment implements a two-agent healthcare workflow automation system designed to reduce no-shows and streamline patient intake. The No-Show Preventer operates on a daily scheduled basis, scanning Google Calendar for upcoming appointments and orchestrating multi-channel reminder campaigns through Twilio's SMS and voice services. The Intake Automator functions reactively, triggering immediately upon appointment confirmation to dispatch digital forms stored in Notion and pre-populate patient data from existing medical records. The system follows a hub-and-spoke architecture with Google Calendar serving as the central data source, Twilio providing communication channels, and Notion acting as the document management system. Both agents share common authentication layers and error handling mechanisms, with built-in redundancy for critical patient communication functions. The deployment prioritizes HIPAA compliance through encrypted data transmission and secure API authentication across all integrations.
Data Flow
Data originates from Google Calendar appointment events, which contain patient contact information, appointment details, and provider schedules. The No-Show Preventer agent queries this data daily at 8am Eastern, identifying appointments requiring 48-hour, 24-hour, and 2-hour reminders based on timestamp calculations. Patient contact preferences and reminder history are cross-referenced to determine optimal communication channels before dispatching messages through Twilio's unified communications API. The Intake Automator receives webhook notifications from Google Calendar when appointments transition to 'confirmed' status. This triggers a lookup sequence in Notion to retrieve appropriate intake forms based on appointment type and provider specialty. Patient demographic data from previous visits is automatically merged into form templates, reducing completion time and improving data accuracy. Completed forms flow back into Notion for provider review, with status updates posted to the appointment record in Google Calendar.
Implementation Phases
Establish Google Calendar and Twilio integrations with authentication, basic reminder functionality, and monitoring systems
Implement Notion integration, form automation workflows, and reactive triggering system
Add voice reminders, SMS templates, and advanced scheduling logic for both agents
Prerequisites
- -Google Workspace admin access for Calendar API setup
- -Twilio account with SMS and voice capabilities
- -Notion workspace with structured patient form templates
- -HIPAA-compliant hosting environment
- -SSL certificates for webhook endpoints
Assumptions
- -Patient phone numbers are stored in Google Calendar appointment descriptions
- -Appointment confirmations trigger status changes in Google Calendar
- -Notion databases follow consistent schema for intake forms
- -Clinic operates Monday-Friday with standard business hours
- -Patients consent to automated communications via SMS and voice
Recommended Agents (2)
How It Works
- 1Calendar Scan
Query Google Calendar API for appointments in next 48 hours, filtering by calendar IDs and extracting patient contact info from event descriptions
Google Calendar API v3 - 2Reminder Calculation
Calculate reminder timestamps (48h, 24h, 2h before) and cross-reference against reminder history database to avoid duplicates
SQLite database - 3Message Personalization
Generate personalized reminder messages using appointment details, provider name, and clinic location from calendar metadata
Jinja2 templates - 4Multi-Channel Dispatch
Send SMS via Twilio API with fallback to voice calls for patients without SMS capability, logging delivery status
Twilio REST API
Implementation
```
# Directory Structure
no_show_preventer/
├── main.py
├── config.py
├── calendar_client.py
├── twilio_client.py
├── database.py
├── templates/
│ ├── sms_48h.txt
│ ├── sms_24h.txt
│ └── voice_2h.xml
└── requirements.txt
# main.py - Core scheduler
class NoShowPreventer:
def __init__(self):
self.calendar = GoogleCalendarClient()
self.twilio = TwilioClient()
self.db = ReminderDatabase()
def run_daily_scan(self):
appointments = self.calendar.get_upcoming_appointments(hours=48)
for appt in appointments:
reminders_needed = self.calculate_reminders(appt)
for reminder in reminders_needed:
self.send_reminder(appt, reminder)
# Environment Variables Needed:
# GOOGLE_CALENDAR_CREDENTIALS_JSON
# TWILIO_ACCOUNT_SID
# TWILIO_AUTH_TOKEN
# DATABASE_URL
# Cron Setup (via crontab):
# 0 8 * * * /usr/bin/python3 /opt/carefirst/no_show_preventer/main.py
# Key Functions:
# - parse_patient_phone() - Extract phone from calendar description
# - check_reminder_sent() - Prevent duplicate reminders
# - format_appointment_time() - Handle timezone conversions
# - handle_delivery_failure() - Retry logic for failed messages
```Data Flow
Inputs
- Google Calendar — Appointment events with patient contact info in description field(JSON via Calendar API)
Outputs
- Twilio SMS — Personalized appointment reminder messages(SMS text)
- Twilio Voice — Automated voice reminders for patients without SMS(TwiML voice script)
Prerequisites
- -Google Calendar API credentials with read access
- -Twilio account with phone number provisioned
- -SQLite database for reminder tracking
- -Cron daemon configured on deployment server
Error Handling
Implement exponential backoff and retry after rate limit reset
Log error and skip reminder, notify admin via email
Queue messages for retry and switch to backup notification method
Integrations
| Source | Target | Data Flow | Method | Complexity |
|---|---|---|---|---|
| Google Calendar | Twilio | Appointment reminders | api | moderate |
Schedule
0 8 * * *Recommended Models
| Task | Recommended | Alternatives | Est. Cost | Why |
|---|---|---|---|---|
| Agent logic / orchestration | Claude Sonnet 4 | GPT-4oGemini 2.5 Pro | $0.003-0.015/call | Excellent for managing complex multi-step workflows like coordinating reminder schedules and intake form routing across healthcare systems |
| Data extraction / parsing | Claude Haiku | Gemini 2.0 FlashGPT-4o-mini | $0.0002-0.001/call | Fast and cost-effective for extracting appointment details from Google Calendar and patient information from existing records |
| Content generation | Claude Sonnet 4 | GPT-4oGemini 2.5 Pro | $0.003-0.015/call | Strong at generating personalized, compliant healthcare communications for appointment reminders and intake form messages |
| Classification / routing | Claude Haiku | Gemini 2.0 FlashGPT-4o-mini | $0.0002-0.001/call | Efficiently categorizes appointment types, patient urgency levels, and routes communications to appropriate channels |
Impact
What Changes
Quality Gains
- ✓No-show rate drops from 15-20% to 8-12% through timely multi-channel reminders
- ✓Patient intake accuracy improves—pre-populated forms reduce missing or conflicting information by ~85%
- ✓Appointment slots fill faster—fewer cancellations mean better clinic utilization and revenue per day
- ✓Patient experience improves—less time waiting for forms, faster check-in at arrival
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