Mercy Healthcare boosts clinical workflow automation for radiology with Azure AI Foundry and UiPath

Mercy Healthcare partners with Microsoft and UiPath to operationalize AI in critical healthcare workflows, specifically targeting the challenge of managing incidental findings in radiology reports. The healthcare provider integrates Azure AI Foundry and UiPath automation to develop agents and orchestrators that review radiology and EMR data, extract important incidental findings, summarize patient context, and deliver actionable notifications to clinicians. This agentic solution automates previously time-consuming manual tasks, reducing physician workload while improving the speed and accuracy of follow-up care. Aggregated patient information is now seamlessly routed to physicians, enabling timely clinical decision support and helping to prevent more expensive downstream medical interventions. Built-in compliance with healthcare privacy and security standards is ensured, leveraging Azure's secure infrastructure. The orchestration is managed through UiPath Maestro, ensuring every step is reliably tracked, documented, and efficiently executed in the clinical workflow. This implementation demonstrates scalable automation of complex multi-agent tasks in real-world healthcare, directly improving care quality and operational efficiency.

Organization
Mercy Healthcare
Industry
Healthcare
Published
November 2025

Reported outcomes

Strategic outcomes

Speed & agilityAutomated radiology follow-up workflowCustomer experience & trustImproved timely clinical follow-upCost efficiencyPrevented downstream medical interventionsRisk & complianceImproved compliance and data security

Primary read

Use case focus

Showing 3 of 3

  • 1Automated Incidental Findings Management in Radiology
  • 2Agent-Based Clinical Decision Support
  • 3AI-Powered Workflow Automation for Healthcare
  • Manual clinical follow-up of incidental findings led to delays in care and increased physician workload.
  • Siloed information from imaging and EMR systems made comprehensive reporting difficult.
  • Timely care was impeded by the volume of data and lack of workflow automation.
  • Implemented Azure AI Foundry and UiPath to automate analysis and summarization of radiology and EMR reports.
  • Orchestrator UiPath Maestro aggregates multi-source data and automatically routes actionable follow-up items to ordering clinicians.
  • Agents extract relevant patient history, prior images, and new findings with AI; information is operationalized in the workflow.
  • Faster detection and follow-up on radiology incidental findings.
  • Reduced manual workload for clinical staff in reporting and notification.
  • Prevention of expensive downstream patient interventions.
  • Improved compliance and data security across sensitive medical records.
Architecture

Integrated AI-powered agents built on Azure AI Foundry analyze radiology and EMR data, extract and summarize incidental findings, feed data into UiPath agents, and are orchestrated by UiPath Maestro. The orchestrator manages the flow from data extraction to physician notification, automating complex cross-system processes securely within Azure.

Implementation partners1
Sources & evidence1
Groundedness: 4/5

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