Transforming Healthcare Communication: A Generative AI Solution for Patient Engagement
Co-authored by Rishi Srivastava and Scott Reynolds from Clarus Care
Overview of Challenges in Patient Call Management
A Revolutionary Approach: AI-Powered Contact Center Prototype
Key Features of the Clarus Care Solution
Use Case: Enhancing Patient Interaction Through Conversational AI
Technical Implementation: Solution Architecture and Components
Intelligent Conversation Handling: Managing Patient Interactions
Streamlined Intent Management for Improved Communication
Scheduling: A Seamless Appointment Setting Experience
Future-Ready Capabilities: System Extensions and Scalability
Conclusion: The Impact of Generative AI on Healthcare Communication
About the Authors: Expertise Behind the Innovation
Revolutionizing Patient Communication in Healthcare with Generative AI
This post was co-written by Rishi Srivastava and Scott Reynolds from Clarus Care.
In today’s fast-paced healthcare environment, managing a high volume of patient calls efficiently has become a crucial yet challenging task. Healthcare practices must juggle appointment scheduling, prescription refills, billing inquiries, and urgent medical concerns—all while aiming to provide quality patient care. Traditional phone systems can result in long wait times, frustrated patients, and overwhelmed staff, leading to communication bottlenecks that affect patient satisfaction and the coordination of critical care.
To tackle these challenges, Clarus Care, a healthcare contact center solutions provider, has partnered with the AWS Generative AI Innovation Center (GenAIIC) to develop a groundbreaking generative AI-powered contact center prototype. This innovative solution enables conversational interactions and resolves multiple intents through an automated voicebot and chat interface. Its scalable service model tackles the growing demand for efficient patient communication, ensuring timely human transfers for urgent requests and providing valuable analytics for performance insights.
The Challenge: A Traditional Approach to Patient Communication
Many healthcare facilities still rely on menu-driven Interactive Voice Response (IVR) systems that can frustrate patients. They often face the frustrating experience of navigating through rigid options, limiting their ability to communicate complex needs efficiently. To overcome this, Clarus aimed to create a generative AI-powered contact center that can understand natural language conversation, manage multiple intents simultaneously, and ensure a seamless experience across both voice and web chat.
Key Success Criteria
To ensure a successful transformation, Clarus established several key criteria for the project:
- Natural Language Interface: The voice system should understand multiple patient intents within a single call.
- Transcription & Analysis: The capability to transcribe and analyze call information effectively.
- Smart Transfer Capabilities: Urgent calls should be smartly routed to the appropriate healthcare providers.
- Multi-Channel Support: Voice and web chat interfaces to meet diverse patient preferences.
- Scalability: A robust foundation to support the growing network of healthcare facilities.
- High Availability: A 99.99% uptime service-level agreement (SLA) for reliable communication.
The Solution: A Generative AI-Powered Contact Center
The collaboration between Clarus and GenAIIC led to the development of a generative AI-powered contact center utilizing Amazon Connect and Amazon Lex, integrated with Amazon Bedrock and Anthropic’s Claude 3.5 Sonnet foundation models. This solution architecture is designed to maintain high availability while simplifying patient interactions.
Workflow Overview
The core workflow comprises several streamlined steps:
-
Patient Initiation: A patient reaches out via phone call or web chat.
-
Routing and Processing: Amazon Connect manages the initial contact through a configured flow, while Lex maintains conversation state and transcribes dialogues.
-
Intent Processing: The system classifies urgency and intent, extracts necessary information, and generates appropriate responses.
-
Smart Transfers: Urgent cases are routed appropriately to human agents when needed.
-
Analytics Pipeline: Data from conversations is utilized for real-time monitoring and insights.
This multi-faceted approach significantly eases patient interactions, allowing healthcare providers to focus more on patient care.
Enhancing Conversation Management
At its core, the generative AI-powered contact center uses sophisticated conversation management techniques to ensure natural interactions. The system is designed to assess urgency immediately upon contact and can handle multiple intents in one interaction, eliminating rigid and frustrating menu-driven responses.
Optimizing for Intent Management
The intent management system follows a hierarchical service model, categorizing inquiries based on urgency, service type, and specific provider needs. This organization allows the system to address complex inquiries naturally, further improving patient interactions.
The Scheduling Component
The scheduling module handles appointment requests in a structured manner. With a state-machine-like approach, it not only gathers user preferences but also effectively matches these preferences against available appointment slots, streamlining the booking process and maximizing efficiency.
Future Possibilities
Looking ahead, Clarus is poised to integrate additional services like Amazon Nova Sonic for real-time, human-like voice interactions. This strategic move will enhance both the capabilities of the contact center and patient engagement, ensuring a top-notch experience.
Conclusion
This collaboration highlights how generative AI can revolutionize patient communication in healthcare settings. By moving from a traditional IVR system to an intuitive conversational interface, Clarus Care aims to enhance patient experiences while improving operational efficiencies. As the healthcare landscape continues to evolve, innovative solutions like this are vital for meeting the complex needs of patients and providers alike.
If you’re interested in implementing a similar solution within your organization, consider checking out the blog on deploying generative AI agents in your contact center using Amazon Connect, Lex, and Bedrock for comprehensive infrastructure setup.
About the Authors
Rishi Srivastava is the VP of Engineering at Clarus Care, specializing in cloud-based SaaS architecture and AI agent solutions.
Scott Reynolds is the VP of Product at Clarus Care, focusing on secure interoperable platforms in healthcare communications.
Together, they, along with the AWS Generative AI team, are transforming the patient communication experience—one phone call at a time.