What challenges did Cleveland Clinic face before AI implementation?

Clinician workload and burnout in healthcare organizations. Need for improved patient experience and easier access to medical information. Risks of generative AI outputs in clinical contexts (fabrications, omissions, semantic errors). Need for compliance and data traceability in patient records.

What was the impact of the AI solution?

Improved traceability with clinical provenance safeguards. Established responsible, verifiable AI for healthcare.

Source

MicrosoftExpandedProductionEvidence: Low40/100

Cleveland Clinic and Galilee Medical Center Transform Patient Care with Healthcare Agents

Use case typePatient engagementUpdated Jun 13, 2026

Cleveland Clinic and Galilee Medical Center, as early adopters, implemented Microsoft's healthcare agent service within Copilot Studio to reduce staff burnout and enhance patient services. Key features include AI-powered appointment scheduling, triaging, clinical trial matching, and transforming complex radiology data into understandable patient reports. The deployment integrates Azure OpenAI Service and Clinical Safeguards APIs, ensuring compliance, data traceability, and responsible AI. Clinical provenance provides evidence mapping and anchoring to original medical records, mitigating risks of AI errors. Through these agents, clinicians have a reduced administrative workload, and patients gain easier access to medical information. The collaboration showcases responsible AI design for sensitive healthcare tasks and improved data validation. Both organizations serve as benchmarks for responsible, AI-enabled healthcare transformation.

Organization: Cleveland Clinic
Industry: Healthcare
Location: United States
Published: October 2024

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Cleveland Clinic, Galilee Medical Center
Provider: Microsoft
Maturity: Production
Linked source: microsoft.com

Deployed healthcare agent service in Microsoft Copilot Studio using Azure OpenAI Service

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

1AI-Powered Appointment Scheduling
2Clinical Trial Matching Automation
3Radiology Report Simplification for Patients

Deployed healthcare agent service in Microsoft Copilot Studio using Azure OpenAI Service.
Implemented clinical safeguards API for verification, provenance, and anchoring of AI-generated content.
Agents automate appointment scheduling, patient triage, trial matching, and patient report simplification.
Built robust, responsible AI with traceability for high-stakes medical applications.

Technologies

Azure OpenAI Copilot Studio

Improved traceability with clinical provenance safeguards.
Established responsible, verifiable AI for healthcare.

Architecture

Agents built within Copilot Studio leverage Azure OpenAI Service and Clinical Safeguards API for monitoring, validation, and provenance. Patient data and queries are processed through the healthcare agent, which accesses validated plugins and prebuilt healthcare logic, and all generative outputs are checked against safeguards to ensure traceability, accuracy, and compliance.

Sources & evidence1

Evidence: Low40/100Evidence strength