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Conversational AI in Healthcare: Use Cases, Benefits & Challenges

Conversational AI in Healthcare: Use Cases, Benefits & Challenges

Healthcare providers face growing patient demands, staffing shortages, and increasing pressure to deliver faster service. Organizations are already adopting AI-driven solutions to handle high call volumes, automate routine inquiries, and improve response times.

livepro recognizes this shift, particularly in healthcare contact centers, where AI-powered knowledge management and voice assistants are improving communication and patient experience. Its quick integration with existing systems allows organizations to maintain consistent and accurate responses while reducing the burden on staff.

In this article, we explore how livepro’s conversational AI solutions improve operations and customer support at healthcare contact centers. We will also take a closer look at the broader role of conversational AI in healthcare and pharma.

Luna: livepro’s Conversational AI Agent for Healthcare

Luna is livepro’s AI voice agent, designed to improve patient interactions and contact center operations with AI-powered knowledge management. It helps healthcare providers reduce staff costs by automating routine inquiries, handling high call volumes, and providing 24/7 support without adding pressure on human agents.

Luna works by pulling responses directly from livepro’s AI-powered knowledge base, providing patients with accurate and approved answers without misinformation.

Here’s how Luna helps you: 

  • Accurate responses from your approved knowledge-base 
  • Reduces staff costs
  • Handles high call volumes
  • 24/7 availability
  • Multilingual support
  • Real-time updates
  • HIPAA-compliant security.

How Luna Helps Healthcare Contact Centers

Many contact centers struggle with high call volumes, long wait times and unresolved inquiries. 

Studies show that only 51% of patients are satisfied with their healthcare provider’s contact center service, with average hold times of 4.4 minutes and just 52% of issues resolved on the first call. 

Luna helps contact centers manage inquiries with 24/7 availability and AI-driven voice assistance, reducing staff workload and improving patient experiences.

Here’s how conversational AI can reduce costs while improving patient interactions and operations:

Virtual Health Assistance in Contact Centers

    Luna handles patient inquiries through AI-driven voice assistance, reducing the need for patients to search multiple web pages or wait on hold. Patients can ask about clinic hours, available services, or doctor availability, receiving an immediate and accurate response.

    For example, a patient calling to check a doctor’s availability can get an answer right away without waiting for a receptionist. The AI voice agent uses your knowledge base to provide context-aware answers to the patient. If a request requires human assistance, Luna transfers the call when needed, reducing the workload on staff while keeping patient interactions timely.

    Appointment Scheduling & Reminders

      Traditional appointment scheduling requires patients to call during office hours, often leading to delays, missed appointments, and long wait times. 

      Luna allows patients to book, reschedule, or cancel appointments through AI voice assistance, reducing the need for staff involvement in routine scheduling tasks. Patients can call at any time and get instant confirmation on appointment availability, cancellations, or rescheduling options.

      With 24/7 availability, Luna helps reduce missed appointments by sending reminders and answering common scheduling-related questions. This allows staff to focus on higher-priority patient interactions while reducing the need for large support teams to manage routine scheduling requests.

      Billing & Insurance Support

        Billing and insurance inquiries make up a large portion of patient calls, often involving coverage details, payment options, and claim statuses. Manually finding answers to customer queries through your knowledge management can be repetitive and mundane for your call center staff, and take up a lot of their time and call queues.

        With Luna, patients can get instant responses to common billing and insurance questions without waiting on hold. Instead of navigating complex paperwork, they receive direct, policy-approved answers on claims, outstanding balances, and payment methods.

        Pre-Procedure Guidance & Patient Education

          Patients who receive clear pre-procedure instructions are better prepared for surgery and medical tests, leading to lower anxiety and better recovery outcomes. However, many struggle to get timely information as contact center staff handle thousands of calls daily.

          Luna provides step-by-step pre-procedure guidance using your knowledge base. 

          With real-time updates, any changes to procedure guidelines are reflected immediately, allowing healthcare providers to deliver consistent and accurate information while reducing repetitive inquiries for staff.

          Prescription Refill Requests & Medication Guidance

            Patients frequently call contact centers with questions about refills, dosage instructions, and potential side effects. These inquiries take up valuable time for staff, leading to delays in medication management and missed doses.

            Luna manages refill requests, medication schedules, and safety guidelines, giving patients direct responses without needing to wait on hold. Instead of relying on manual assistance, Luna provides policy-approved information to patients.

            If a request requires pharmacist approval or verification, Luna can direct the inquiry to the right healthcare professional, reducing unnecessary escalations while allowing staff to focus on more urgent cases.

            Patient Feedback and Insights

              96% of patient complaints are related to customer service, yet traditional surveys often get low response rates, making it harder to gather useful feedback.

              With Luna, patients can share feedback on treatment experiences, staff interactions, and overall care through natural voice interactions, avoiding the hassle of text-based surveys.

              Multilingual support helps collect feedback from a diverse patient base, giving healthcare providers a clearer picture of patient concerns and areas for improvement.

              Other Use Cases of Conversational AI in Healthcare

              While the above were conversational AI use cases specifically relevant to Luna, the technology is used in various other areas to improve customer experience. 

              Here are a few examples:

              • AI-Powered Symptom Checkers & Medical Triage: Conversational AI helps assess symptoms and determine the urgency of a condition. It guides patients on whether they need immediate medical attention, should schedule a routine appointment, or can manage symptoms at home.
              • Remote Patient Monitoring: AI-driven virtual assistants check in with patients, track vitals, and send alerts to healthcare providers for potential health risks.
              • Mental Health Support: Conversational AI provides immediate mental health guidance, offering coping strategies and directing patients to relevant resources before they reach a crisis point.
              • Clinical Documentation Assistance: AI-powered notetakers transcribe and summarize doctor-patient conversations, reducing administrative work for healthcare professionals.
              • Chronic Disease Management: Conversational AI supports patients with conditions like diabetes or hypertension by sending medication reminders and tracking symptoms over time.

              How Does Conversational AI Work?

              Conversational AI allows AI voice agents, virtual assistants, and chat-based interfaces to interact naturally with patients and healthcare staff. Unlike traditional chatbots that follow predefined scripts, it understands intent, adapts to different phrasing, and improves over time.

              It works using:

              • Natural Language Processing (NLP): Understands and processes human language.
              • Machine Learning (ML): Learns from past interactions to refine responses.
              • Intent Recognition: Identifies the purpose behind a query, even when phrased differently.
              • Speech-to-Text & Text-to-Speech (STT & TTS): Converts spoken words into text and back for voice interactions.
              • Knowledge Base Integration: Pulls answers directly from your knowledge base. 

              Challenges in Implementing Conversational AI Technology in Healthcare

              While many healthcare organizations are keen to adopt conversational AI to improve service delivery, they often encounter several challenges that can complicate successful integration:

              Data Privacy and Security

              The healthcare sector operates under strict compliance standards, requiring AI solutions to follow HIPAA, GDPR, and CCPA regulations. These frameworks mandate data minimization, encryption, and controlled access to patient health information (PHI) to prevent unauthorized access and breaches. Failure to meet these standards can result in legal penalties and loss of patient trust.

              livepro’s solutions for highly regulated industries give healthcare providers confidence that patient data remains secure, access is strictly managed, and sensitive information is handled in full compliance with the latest regulatory standards.

              Data Management

              Healthcare organizations often deal with fragmented and unstructured data spread across different systems, making it difficult for AI tools to provide accurate responses. A study on data silos in healthcare found several barriers to data integration, including:

              • Incompatible record systems that cannot connect with other platforms
              • Privacy regulations that restrict data collection and sharing
              • Lack of standardization in data collection, making it difficult to organize and analyze
              • Missing or incomplete records, leading to gaps in patient information.

              Without proper data management, issues with completeness, accessibility, and consistency limit AI’s ability to support healthcare operations effectively. 

              For example, Avant Mutual centralized its knowledge into a single system, reducing handling times and improving response accuracy. With conversational AI agents like livepro’s Luna, this process could become faster by automating routine customer queries and retrieving accurate context-aware data instantly. 

              Accuracy and Reliability

              Conversational AI agents must provide accurate and verified responses, as misinformation can have serious consequences. AI tools require continuous updates, validation against medical standards, and training on high-quality data.

              Luna addresses this challenge by sourcing information directly from a company’s verified knowledge base, instead of relying on external sources.

              Integration with Existing Systems

              A study found that 73% of healthcare providers rely on legacy systems such as old electronic health records (EHR) platforms, on-premise data storage, and outdated scheduling or billing software. 

              Luna is designed for easy deployment, allowing healthcare organizations to get started with their existing knowledge by simply utilizing LightspeedAI and livepro’s new Source Documents to import policies, procedures and information in their existing format (Source Documents) or in an improved format using AI features (LightspeedAI and AI Authoring). Its API-first approach enables easy integration with other systems, ensuring that healthcare contact centers can incorporate AI-driven support without disrupting operations.

              Request a demo today and experience AI-powered assistance for your healthcare contact center.

              The Future of Conversational AI in Healthcare and Pharma

              A 2024 McKinsey survey found that over 70% of healthcare organizations are exploring or have already implemented generative AI. Among those using AI, 60% report a positive ROI or expect to see one soon, signaling its growing impact in healthcare.

              Key trends shaping the future of AI in healthcare include:

              • Automation of routine tasks like appointment scheduling and billing to free up staff.
              • Personalized AI responses based on patient history for better communication.
              • AI-driven knowledge management to help healthcare professionals access critical information faster.
              • Integration with EHRs to minimize errors caused by outdated or missing data.
              • Advancements in NLP to improve AI’s ability to interpret medical terminology.
              • Stronger AI governance to align with HIPAA, GDPR, and other compliance regulations.

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              Picture of Usama Khan
              Usama Khan

              Author

              Published
              Tue, Feb 25 2025

              5:03 AM
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