Billing administration is one of the most time-consuming parts of hospital and medical practice work. Studies show that about 97% of patient calls to healthcare providers are about billing questions. These questions include things like co-payments, deductibles, itemized statements, and payment options. Because there are so many calls and they can be complicated, patients often wait a long time, get frustrated, and call center staff get very busy trying to handle all the calls, especially during busy times or when there are fewer staff.
Hospitals spend millions each year on call centers and administrative staff to answer these routine questions. At the same time, labor shortages and rising costs make it harder for staff to keep up. When billing support is not efficient, it can hurt how much money the hospital gets, lower patient satisfaction, and reduce the quality of service.
Because of these problems, many healthcare providers are using AI-based tools to automate front-office tasks. These tools aim to make patient interactions smoother, reduce the workload on staff, and improve how billing questions are answered.
AI voice agents are advanced systems that talk with patients through phone calls or other voice channels. They are different from old Interactive Voice Response (IVR) systems because they use technologies like natural language processing (NLP), speech recognition, and sentiment analysis. This means they can understand spoken language, detect emotions in patient questions, and respond in a more human-like and caring way.
One example is Kora, Cedar’s AI voice agent made for healthcare billing. Kora works with partners like ApolloMD and is expected to handle about 30% of patient billing calls by the end of 2025. Using AI like this helps reduce wait times, lower costs, and make call center operations work better.
Patients often feel frustrated by confusing medical bills. Hard-to-understand explanations, unclear payment rules, and long waits make people unhappy or delay payments. AI voice agents help by:
Amy Katnik, COO at ApolloMD, says AI agents handle billing calls smoothly without emotional bias. This helps patients manage money better and lowers pressure on reimbursements. Patients often feel calmer when AI sounds natural and responds with care, as Cedar’s system is designed to do.
AI voice agents also help front desk work by automating routine tasks that staff used to do. These include:
Research shows AI voice agents can cut administrative work by up to 60%, which lowers staff burnout and inefficiency. They work closely with EHR and Patient Management Systems to keep data accurate and follow privacy rules like HIPAA. This helps keep patient information safe and allows personal care.
AI also handles sudden call spikes during times like flu season or vaccine drives. It adjusts to more calls without losing service quality or needing extra staff.
Healthcare providers in the U.S. face growing problems like higher labor costs, staff shortages, and the need to keep patients happy. Using AI voice agents is a cost-effective way to deal with these issues.
Cedar serves over 50 million patients and has processed more than $10 billion in payments through its platform. ApolloMD’s experience shows that AI billing support can change call centers for the better and improve patient outcomes.
AI voice agents use advances in several technology areas:
Twilio’s work with Cedar’s AI agent shows how telecom and AI combine to give personal and efficient patient care.
Healthcare leaders thinking about AI voice agents should keep in mind:
AI voice agents are no longer just ideas but are already changing healthcare billing and front desk work. They lower staff workload, cut costs, and provide quick, caring, and personal financial help for patients. Hospital leaders, medical office owners, and IT managers in the U.S. can use these tools to meet healthcare administration needs and improve patient billing experiences.
Kora is an AI voice agent purpose-built for healthcare billing, developed by Cedar in collaboration with Twilio. It automates patient billing calls to help providers resolve billing inquiries instantly, reducing manual workload and costs.
Kora autonomously addresses common billing inquiries during the first interaction, explaining charges clearly, identifying payment options, and connecting patients with financial assistance, thereby improving call resolution quality and speed.
Kora uses natural language understanding and Twilio’s ConversationRelay service, allowing for real-time streaming, speech recognition, interruption handling, and empathetic, conversational responses similar to a human agent.
Kora is designed with HIPAA privacy and security safeguards ensuring patient data protection. It maintains compliance from the ground up to securely handle sensitive healthcare billing information.
Kora is projected to automate 30% of inbound billing calls by 2025, reducing reliance on call center staff, lowering labor costs, and enabling staff to focus on complex patient interactions requiring a human touch.
Kora provides empathetic, real-time support 24/7 without hold times, supports multiple languages, detects patient sentiment and tone, and escalates to human agents when necessary, enhancing patient experience.
Kora helps mitigate rising labor costs, staffing shortages, and the pressure to improve patient experience by automating billing inquiries, reducing call volumes, and improving access to financial support outside business hours.
Kora leverages Cedar’s healthcare ecosystem and real-time data integrations to offer personalized financial pathways, intelligently responding to individual patient billing questions and needs with empathy.
Cedar emphasizes real, measurable outcomes by combining deep revenue cycle expertise with AI designed for privacy, safety, and empathy, creating trust and efficiency that patients and providers rely on.
By automating routine billing inquiries and call handling, Kora reduces operational overhead, cuts costs, improves collection rates, and allows revenue cycle teams to allocate resources efficiently toward complex cases.
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