Helps care providers reach and support patients with reminders, guidance, and personalized communication.
Use cases
85
Examples
60
Industries
4
Timeline
26 mo
Data updated 1 day ago
Adoption over time
Documented cases per month
By case publish month · completed months only
65 cases documented across 37 months (Jul 23 – Jul 26), peaking at 7 in May 2026.
AI Use Cases Hub
6 earlier cases before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
3.2Innovativeness3.2/5Differentiated3.2/5 - Differentiated. Compared with recent healthcare AI deployments, this is an applied but not frontier use of Azure OpenAI: the novelty is the humanoid companion robot operating in a constrained clinical environment with safety guardrails, rather than a new model architecture or multi-agent system.
In pediatric radiation therapy, children must remain alone during treatment sessions, which can cause anxiety, distress, and emotional strain for patients, families, and care teams.Institut du Cancer de Montpellier partnered with Enchanted Tools to deploy Miroki, an AI-enabled companion robot running on Microsoft Azure and Azure OpenAI Service to provide a reassuring presence during radiation sessions in a secure, healthcare-compliant cloud environment.The initiative combines robotics, guarded conversational AI, radiation-environment validation, and clinical study work to support care without replacing clinicians.
3.1Innovativeness3.1/5Differentiated3.1/5 - Differentiated. This is a solid healthcare contact-center automation using packaged AWS services and scripted chatbot flows. It is more capable than a basic chatbot because it combines multichannel outreach, clinical scripts and human handoff, but it is still similar to other recent Amazon Connect healthcare deployments rather than a novel architecture.
NHS Midlands and Lancashire (NHS ML) migrated its patient contact center to AWS with Digital Space to automate patient communications and waiting-list validation.The platform uses Amazon Connect Customer and Amazon Lex to send SMS links, run secure web portal surveys and place chatbot calls using clinically validated scripts, with escalation to human operators when patients need to come off the list.
4.1Innovativeness4.1/5Advanced4.1/5 - Advanced. Compared with recent healthcare AI cases around 3.0-3.1, this is more advanced because it combines a custom patient app, protocol-grounded RAG, rolling-transcript intelligence, operational automation, and multiple workflow integrations in one regulated deployment.
Clixlogix delivered an eleven month engagement for a Massachusetts cardiovascular care company spanning strategic assessment, discovery, solutioning, and phased implementation.The solution replaced a vendor-locked patient application with a custom Flutter platform on existing EHR REST APIs, added an AI care companion grounded in the client’s clinical protocol using Azure OpenAI Service and Azure Health Data Services managed FHIR API, and introduced AI session intelligence, enrollment automation, billing automation, RPM anomaly detection, computer-vision lifestyle logging, and standardized partner reporting.
3.5Innovativeness3.5/5Advanced3.5/5 - Advanced. This is a solid domain-specific RAG deployment with production infrastructure and review by pharmacists, but it follows a common Bedrock-plus-RAG pattern rather than a highly novel architecture.
El Ezaby is an Egyptian pharmacy chain with more than 400 branches.Its pharmacists rely on the company academy and senior doctors for guidance on complex cases, but retrieving advice from a 500,000-file knowledge base was slow and difficult.
4Innovativeness4/5Advanced4/5 - Advanced. AI agents for omnichannel appointment management and autonomous patient self-verification is more advanced than a basic contact-center bot, though the article does not describe a novel custom architecture beyond Amazon Connect.
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.
3Innovativeness3/5Differentiated3/5 - Differentiated. Innovative use of Google Cloud's AI-driven Cloud Speech-to-Text and infrastructure to deploy a scalable, omnichannel AI virtual assistant improving patient engagement and reducing no-shows.
Eniax is a healthcare service provider operating in 7 countries across Latin America and Europe, offering services to over 350 clinics, medical centers, and hospitals.Eniax faced challenges of high patient no-shows, a shortage of physicians and specialists, and deficiencies in customer support resulting in dehumanized patient experiences.They developed and deployed an AI-powered virtual assistant Patricia using Google Cloud's Cloud Speech-to-Text and other Google Cloud infrastructure to provide humanized, omnichannel patient communication and enhanced patient engagement with seamless integration.The virtual assistant supports multiple communication channels including phone, messaging apps, SMS, and email, enabling omnichannel patient support with high satisfaction.The company centralized and improved infrastructure management and achieved scalability with local Google Cloud servers ensuring compliance with EU data requirements.Results include a 50% reduction in patient no-shows, 98% patient satisfaction with outpatient care, improved uptime, and care for over 5 million patients supported globally.
4Innovativeness4/5Advanced4/5 - Advanced. The AI medical assistant represents an advanced architecture using pre-trained reasoning models on Google Cloud TPUs, offering higher clinical insight and speed versus typical retrieval-based systems in a highly regulated pediatric care context.
The Children's Hospital of Philadelphia developed a reasoning-based AI medical assistant using Google Cloud Vertex AI, Trillium TPUs, and other advanced models to analyze pediatric patient electronic health records (EHR) securely.The AI assistant pre-learns extensive patient histories from 146 million clinical notes for over 1.6 million patients to provide deep contextual insights and support physician decision-making with improved speed and accuracy.The solution complies with HIPAA and operated in a secure Google Cloud environment to ensure patient privacy and stringent regulatory compliance.This innovative assistant surpasses conventional retrieval-augmented generation models by delivering patient-specific reasoning and understanding in a pediatric care setting.
3Innovativeness3/5Differentiated3/5 - Differentiated. Differentiated applied innovation in healthcare digital transformation by using API management to enable multi-service integration and patient empowerment.
Rush University Medical Center, an academic health system in Chicago, aimed to improve patient and caregiver experiences through digital tools providing seamless access to healthcare services.The challenge was to enable patients to access care anywhere using mobile and online tools powered by APIs, thus improving engagement and satisfaction while reducing operational costs.The solution was the MyRush app, which integrates APIs managed and secured by Google Cloud's Apigee API Management platform, enabling access to medical records, appointments, prescriptions, symptom checking, and even ride-hailing services.The implementation resulted in 20,000 API calls per month within 8 months of launch, freeing IT resources from API management to focus on delivering care-enhancing applications, and significantly improving patient interaction with healthcare.
4Innovativeness4/5Advanced4/5 - Advanced. It describes multiple specialized clinical and administrative AI agents integrated into Epic’s EHR workflow (Dragon ambient AI in AI Charting, plus generative medical event models CoMET), indicating deeper domain-specific transformation beyond generic agent use.
Epic Systems partnered with Microsoft to develop new artificial intelligence models and AI agents to improve healthcare provider operations, increase patient engagement, and reduce administrative burdens for clinicians.The solution includes AI assistants such as Art for Clinicians, a clinical assistant; Emmie, a patient-facing chatbot in the MyChart portal; and Penny, a revenue management assistant supporting billing and insurance claims.Epic also developed generative medical event models called CoMET to help doctors use real-world evidence to improve patient treatment and care decisions.
3Innovativeness3/5Differentiated3/5 - Differentiated. It implements an omnichannel, agentic-style healthcare chatbot with multilingual and voice interaction plus integrations to multiple EHR/telemedicine systems, but the evidence emphasizes deployment and integrations over a distinctly advanced orchestration or architecture.
Webify.Ai developed the Best Agentic AI Chatbot to enhance patient experience, streamline hospital and clinic workflows, and improve service accessibility.Powered by Microsoft Copilot and Enterprise GPT on Azure, the chatbot integrates with EHR, appointment, and telemedicine platforms, providing 24/7 virtual assistance and multilingual omnichannel communication.
How many patient engagement use cases are documented?
The AI Use Case Hub documents 85 real patient engagement deployments across 4 industries, with 60 detailed company examples you can browse.
Which industries adopt patient engagement the most?
Patient engagement is most common in Healthcare (88%), Pharma (7%) and Public Sector (4%).
Which countries lead in patient engagement?
United States leads documented patient engagement deployments, followed by Global and United Kingdom.
What technologies are used for patient engagement?
Teams most often build patient engagement with Azure OpenAI, Azure AI and Azure.
What AI capabilities power patient engagement?
Across the documented deployments, the most common capability patterns are Agent (47%), Multi-agent (19%) and Voice (16%).
What results do companies report from patient engagement?
Across the 85 deployments reporting outcomes, companies most often cite customer experience & trust (79%), new product / capability (65%) and speed & agility (46%). Where impact is quantified, the strongest evidence is in time & speed: a median −55% across 5 reported metrics.
