What challenges did Mercy Healthcare face before AI implementation?

High employee workload and administrative burden within the health system. Patient engagement needed improvement, especially around communications and timely updates. Reactive rather than proactive/predictive care, impacting patient outcomes and costs.

What was the impact of the AI solution?

Expected to improve patient and employee experience across the Mercy network. Anticipated reduction in hospital day durations via data-driven care and monitoring. Increased efficiency by automating routine communications and internal knowledge access. Deployment of four dozen AI use cases by mid-next year.

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Source

MicrosoftExpanded

Mercy Healthcare transforms patient engagement and operational efficiency with generative AI

Use case typePatient engagementUpdated Jun 13, 2026

Mercy Healthcare, a leading US health system, partnered with Microsoft for a multiyear journey to deploy generative AI solutions and enhance both patient and employee experiences. Leveraging Microsoft's Azure OpenAI Service and secure cloud platform, Mercy is rolling out over four dozen AI-powered use cases by mid-next year. These applications include generative AI-driven patient messaging for lab results, appointment scheduling, follow-up recommendations, and internal HR support chatbots. One project utilizes smart dashboards built on a centralized Azure data platform that give care teams real-time insights to optimize care and reduce unnecessary hospital stay durations. Internally, Mercy is deploying AI chatbots to improve staff access to policies and reduce administrative workload, thereby freeing up healthcare workers for patient-facing care. The collaboration represents a proactive approach to predictive, personalized care and innovation-driven healthcare delivery.

Organization: Mercy Healthcare
Industry: Healthcare
Location: United States
Published: September 2023

Reported outcomes

Strategic outcomes

New product / capabilityDeployed AI-powered patient and staff toolsBetter decisions & insightProvided clinicians real-time care insightsCost efficiencyReduced administrative workloadCustomer experience & trustImproved patient and employee experience

Primary read

Use case focus

Showing 3 of 3

1Generative AI-driven Patient Messaging
2AI Chatbots for Employee HR and Operations
3Smart Care Dashboard for Patient Flow Optimization

High employee workload and administrative burden within the health system.
Patient engagement needed improvement, especially around communications and timely updates.
Reactive rather than proactive/predictive care, impacting patient outcomes and costs.

Partnered with Microsoft to develop and deploy a centralized Azure-based data platform.
Used Azure OpenAI Service to build generative AI-driven applications for patient and staff engagement.
Rolled out AI-powered patient messaging and chatbot workflows for appointment management and HR inquiries.
Developed smart dashboards to provide clinicians with actionable real-time insights.

Technologies

Azure OpenAI

Expected to improve patient and employee experience across the Mercy network.
Anticipated reduction in hospital day durations via data-driven care and monitoring.
Increased efficiency by automating routine communications and internal knowledge access.
Deployment of four dozen AI use cases by mid-next year.

Architecture

Centralized Azure-based platform consolidates clinical and operational data; Azure OpenAI Service powers generative AI for patient communications and staff chatbots; smart dashboards linked to the data platform provide care insights and enable efficient workflow management across clinical teams.

Sources & evidence3

ExpandedExpanded

The same organization appears in newer AI deployment evidence.