What if AI could dramatically reduce call volume, improve patient satisfaction, and empower your call center staff? In this exclusive interview, Dugan Winkie, Head of Commercial Strategy at Cedar, sheds light on the often-overlooked opportunity of leveraging AI in healthcare call centers.
Winkie explores the unique challenges and opportunities AI presents for providers, highlighting the potential for increased efficiency, improved patient experiences, and significant financial gains. He also shares best practices for implementing AI in call centers and emphasizes the importance of a human-centered approach.
Why are call centers often overlooked when it comes to leveraging AI in healthcare finance?
Dugan Winkie, Head of Commercial Strategy at Cedar: Everyone is talking about AI, but when it comes to the revenue cycle, it can be hard to know where to invest. Call centers represent an untapped opportunity for revenue cycle leaders to thoughtfully leverage AI, but can be overlooked due to:
- Ambiguous ROI: Call centers often struggle to accurately identify the root causes of patient inquiries due to inaccurate manual call categorization. This challenge is compounded by the complexity of patient questions, which often require data from multiple entities to provide correct, comprehensive answers.
- Ethical considerations: Healthcare providers must carefully consider the ethical implications of AI implementation, especially in areas dealing with sensitive patient information and financial data.
- Need for guardrails: Organizations are cautious about implementing AI without proper safeguards, which can slow down adoption in areas like call centers that handle critical patient interactions.
But, by harnessing the transformative power of AI in this often-underestimated area, RCM leaders have the opportunity to unlock game-changing advancements in efficiency, elevate patient experiences, and drive significant financial gains. As the healthcare landscape rapidly evolves, those who recognize and seize the potential of AI in call centers will position themselves at the forefront of innovation, gaining a critical edge in the industry.
What unique challenges and opportunities do they present for providers?
Dugan Winkie: Dealing with medical bills is one of the most stressful, time-consuming, and costly parts of the patient experience. Patients are facing rising costs, causing more Americans to go bankrupt than any other sector. This can take their attention away from getting well and recovering. At the same time, providers are facing staffing shortages, rising wages/costs, and unprecedented burnout. This means there’s limited bandwidth to give patients the help they need.
While AI can improve efficiency, there’s a challenge in ensuring that the human touch and empathy are not lost in patient interactions, especially when dealing with sensitive financial matters. But, by combining human expertise with GenerativeAI and Large Language Models, we can improve efficiency while maintaining a human touch in medical billing.
What if 30% of your inbound calls simply went away? How would that help not only patients but your team? Through the power of AI, there is a future where this is possible—and at Cedar, we see an opportunity to improve servicing efficiency, without losing empathy, through three levers:
- Enhanced self-service: By leveraging AI to improve user experience, providers can encourage more patients to use self-service options for billing inquiries and payments.
- Automated responses: Virtual agents powered by AI can handle common questions and issues, freeing up human staff for more complex or sensitive matters.
- Empowered representatives: AI can equip call center representatives with real-time information and insights, enabling them to handle high-touch issues more efficiently and empathetically.
What are some of the key benefits that healthcare organizations can expect to see by implementing AI in their call centers, in terms of both efficiency and patient experience?
Dugan Winkie: We know that 40% of consumers avoid paying their bills simply because they don’t understand the complex healthcare billing process. Meanwhile, provider call centers are swamped with questions—everything from coinsurance and deductible statuses to the meaning of cryptic CPT codes like “36415: Collection of Venous Blood by Venipuncture.”
We recently partnered with a healthcare provider for a call center assessment and discovered something startling—only 3% of the calls they received were to actually make a payment. Yes, that’s right: 97% of calls were questions about their bill or routine data asks.
Now, think about the potential of AI in transforming this landscape. By strategically implementing AI in call centers, healthcare organizations can dramatically boost efficiency without sacrificing the human touch patients need during medical billing interactions. Here’s what it could look like:
- A reduction in overall call volumes, thanks to smarter routing and self-service options.
- An increased number of calls that can be automated, allowing human agents to focus on more complex, high-value interactions.
- A reduction in call duration, freeing up valuable time for both patients and staff.
These aren’t just efficiency metrics; they’re a roadmap to elevating patient satisfaction, cutting operational costs, and making billing a less confusing, more manageable experience for everyone involved. AI is more than just a tech upgrade—it’s a strategy for reshaping the patient experience in a way that leaves a lasting impact.
Can you share examples of healthcare organizations that have successfully implemented AI in their call centers to improve RCM processes? What were the key outcomes and lessons learned from these implementations?
Dugan Winkie: At this year’s HLTH conference, we announced Cedar Support, which combines advanced AI and empathetic services for a personalized, efficient support experience.
Imagine having a personal financial concierge holding your patients’ hands to coach them through questions and most importantly, provide answers. Our AI-enabled solutions are designed to optimize patient financial engagement, make your teams a little more efficient, and improve the efficacy of your call center and collections operations.
We recently launched our AI chat assistant solution in our alpha client’s service center. This product is focused on reducing the involvement of call center staff in straightforward patient interactions and empowering them to efficiently tackle more complex issues – while also empowering patients to self-serve. Some of the feedback we’ve received from staff includes:
- “I like the AI response because it gives the date of service, location. It’ll make everything more consistent.”
- “I can tell you right now, I’m going to really like this.”
- “That’s exactly what we need. I couldn’t have said it better myself.”
For us, feedback like this means that we’re assisting and delighting patients with relevant, timely, and personalized information
For example, in our first alpha client results, 7% of patients who initially started a chat chose to exit after reviewing the tailored, AI-generated responses, indicating that they found the answers they needed without agent intervention. As a result, chat volume decreased by 9%, freeing up agents to manage more involved cases. Notably, 84% of patients who used the self-service feature rated the information as highly helpful.
The AI assistant also improved the efficiency of the call center staff. By providing suggested responses, agents were able to reduce the duration of chat sessions by 17%, which amounted to a 2.5-minute decrease per interaction. Even when agents opted to craft their own replies, 56% of the time, their responses closely matched the AI-generated suggestions, demonstrating the tool’s accuracy.
We also learned that adjusting the AI interface based on user feedback significantly increased agent adoption. After refining how suggestions were presented, the rate of agents using the AI responses doubled. This highlights the importance of usability in ensuring successful AI implementation in healthcare settings.
What are some best practices would you give to healthcare leaders who are considering investing in AI for their call centers?
Dugan Winkie: At Cedar, we believe in a human-centered, empathetic, and data-driven approach to billing. So, our approach to AI is the same.
You can’t manage what you don’t measure, which is why it’s crucial for healthcare providers to fully understand the nature of call patterns and the degree of automation potential.
We want to enable call center teams to help patients and work at the top of their licenses. So as a standard practice, we perform detailed AI assessments for all potential partners, providing a clear roadmap for strategic AI integration and maximizing operational efficiency.
We also have a set of principles that inform our AI work and provide a helpful framework for healthcare leaders who are looking to invest in AI for their call centers:
- Deliver Clarity: Patients should never have to waste time with phone calls, emails, and endless research to understand their healthcare financial journey. AI should connect the dots, empowering patients to make informed decisions, tailored to their personal circumstances.
- Earn Trust: Patients should never have to worry about who has their health information and what they might do with it. Technology providers should be transparent about using AI, and be protective of the privacy and accuracy of every patient’s data.
- Scale Empathy: Emotional intelligence should be an integral part of AI, ensuring that tools are deployed with empathy to facilitate positive, productive conversations that connect team members and patients as fellow humans.
- Empower Team Members: Team members should never be bogged down by menial, low-value tasks. AI should be used to erase inefficiencies, giving teams the freedom to focus on the complex problems they are expertly trained to solve.
- Preserve Control: Team members should never feel like they’re taking a backseat to technology. AI-powered tools should let team members stay in control, giving them the information, tools, and confidence needed to determine when to trust AI outputs and when to second guess them.
About Dugan Winkie
Dugan Winkie is the Head of Commercial Strategy at Cedar, leading go-to-market for new product innovation and strategic planning for the company. He is a skilled healthcare technology executive with over 15 years of healthcare growth strategy, operations, digital, and public sec-
tor expertise, and has led over 20 end-to-end digital and operational transformation projects across multiple industries and sectors. Before Cedar, Dugan was an Associate Partner at McKinsey & Company and an Implementation Executive at Epic. He received his MBA from Yale University and BBA from the University of Wisconsin-Madison.