Normalized claim
Staff hours saved: 300,000 hours decrease
saving over 300,000 staff hours
UC San Diego Health deploys Amazon Connect AI agents for appointment management
Use case typePatient engagementUpdated Jun 13, 2026
UC San Diego Health deployed Amazon Connect AI agents across voice, chat, and WhatsApp to manage appointment-related workflows. The solution enables patients to self-verify and schedule appointments autonomously, reducing manual contact center effort and improving access to care.
- Organization
- UC San Diego Health
- Industry
- Healthcare
- Location
- United States
- Published
- May 2026
Reported outcomes
300,000 hours
staff hours savedTime & speed
+82%patient self-verification rate−50%call abandonment rate
Strategic outcomes
New product / capabilityDeployed omnichannel appointment self-serviceCustomer experience & trustEnabled autonomous patient scheduling
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Patient self-verification rate: 82% increase
achieving an 82% patient self-verification rate
Normalized claim
Call abandonment rate: 50% decrease
cutting call abandonment by 50%
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- UC San Diego Health
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Amazon Connect Customer stories
UC San Diego Health deployed Amazon Connect AI agents across voice, chat, and WhatsApp to manage appointment-related workflows
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Customer Service
- 2Appointment Scheduling
- 3Patient Engagement
Streamline patient scheduling and reduce call abandonment while enabling more autonomous patient self-verification and appointment scheduling.
- Implemented Amazon Connect AI agents to manage appointment-related workflows across voice, chat, and WhatsApp.
- Used omnichannel self-service so patients could verify their information and schedule appointments without needing a human agent for every interaction.
Technologies
- Saved over 300,000 staff hours.
- Achieved an 82% patient self-verification rate.
- Cut call abandonment by 50%.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Customer evidence
Provider evidence
AI patterns
Browse the catalog
Was this useful?
Community
Comments
No published comments yet.