Scaling Population Health with AI While Preserving the Human Touch

Summary

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Episode Overview

Podcast: Becker’s Healthcare Podcast
Episode: Scaling Population Health with AI While Preserving the Human Touch
Date: May 19, 2026
Host: Grace Lynn Keller
Guest: Betsy Williamson, R.N.B.S, MHA, Vice President of Quality Performance and Population Health at Medical Mutual of Ohio

This episode explores how Medical Mutual of Ohio, a historic and member-owned health insurer, is leveraging AI—specifically their AI voice agent "Stephanie"—to scale population health efforts while retaining their core value of human connection. Betsy Williamson delves into the process, challenges, unexpected wins, and the impact on both members and frontline staff.

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Key Discussion Points & Insights

Medical Mutual's Unique Approach to Member Care

• Medical Mutual, established in 1934, serves over 1.2 million members as a "hometown insurer," focusing on member and community needs rather than Wall Street interests.

  "We are a mutual company, which means that we are owned by our members and not by Wall Street. ...We live in the same neighborhoods as our members do."
  — Betsy Williamson [00:40]

Why Incorporate AI and How "Stephanie" Augments, Not Replaces, Human Touch

• The AI agent "Stephanie" was introduced to augment existing services, not replace humans.
• Stephanie provides scalable outreach, ensuring members are connected with live humans as needed.
• Members are always notified they are interacting with AI and are given the option to speak to a person.

  "Realizing that Stephanie does not replace humans, ...she actually augments it so...we're able to expand more and reach more people and help them through their journey."
  — Betsy Williamson [01:32]

Overcoming Internal Resistance to AI

• The adoption required robust change management, clear escalation procedures, and transparency with staff.
• Staff were trained with concise scripts for each use case, and members were prepped with flyers announcing Stephanie’s outreach.

  "Letting their staff realize that we’re augmenting them, not replacing them, that they are part of the solution..."
  — Betsy Williamson [02:37]

• Openness with members and clear communication led to the highest completion rates and zero data breaches.

Member Response & Surprising Outcomes

• Contrary to fear, members were open to AI engagement, reflected in satisfaction scores.
• Stephanie matched or outperformed human agents in certain areas, scoring 9/10 in satisfaction and a 93% score of 7 or higher.

  "We did see similar acceptance rates with humans versus our AI agent... Stephanie is able to take time, she's not held to call center metrics..."
  — Betsy Williamson [04:37]

• The AI voice agent excels at motivational interviewing and identifying subtle cues, such as low health confidence, that may be overlooked by humans.

Impact on Care Team Workload and Focus

• AI enabled a 360% increase in care team capacity.
• 93% of AI-initiated calls were resolved with one touch; only 6.7% needed escalation to human staff, focusing them on high-need cases.

  "Our employees are much more satisfied in the work that they do because they're just not cold calling people... they're really making a difference."
  — Betsy Williamson [06:31]

A Defining Success Story (Diabetes Management Program)

• In their diabetes management program, Stephanie maintained high engagement rates.
• Unexpectedly, 19.1% of members disclosed issues like anxiety, loneliness, or financial hardship—crucial signals not seen in claims data—which the team could then address.

  "...19.1% of members...disclosed some things like anxiety, loneliness or even financial hardships, which were all signals that are invisible on a claim."
  — Betsy Williamson [07:56]

The Future Vision: Continuous Engagement & Relationship-Driven Health

• Medical Mutual aims to continuously deepen population and condition management, enabling earlier problem identification and better outcomes.
• The organization sees infinite use cases for AI in population health programs over the next 12 months.

  "The number of use cases, really, I believe, is infinite. ...Our vision right now is really continuous member engagement and early intervention and strong relationships."
  — Betsy Williamson [09:10]

Advice for Other Leaders Considering AI

• Start by finding the right, safety-first partner and ensure transparency across staff.
• Build trust through openness and a solid change management strategy.

  "Take the time and pick the right partner... be completely transparent with your teams. The more transparent you are... you're able to remove the fear and the stigma..."
  — Betsy Williamson [09:55]

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Notable Quotes & Takeaways

• On Human Augmentation:
  "Stephanie does not replace humans, she actually augments [our work], so we’re able to expand and reach more people."
  — Betsy Williamson [01:32]
• Staff & Member Sentiment:
  "Our employees are much more satisfied... they're really making a difference where they need to make a difference."
  — Betsy Williamson [06:31]
• The Reality of Member Engagement:
  "Members are embracing AI just the same as everyone else... The biggest thing that came forward [was] that people want to engage."
  — Betsy Williamson [04:37]
• Improved Data and Outreach:
  "...Signals that are invisible on a claim. And we were able to intervene and get some care out through there, find them resources..."
  — Betsy Williamson [07:56]
• On Getting Started with AI:
  "Pick the right partner... be completely transparent with your teams... and of course, a great change management plan."
  — Betsy Williamson [09:55]

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Timestamps for Key Segments

• Medical Mutual’s Distinctiveness – [00:40]
• Philosophy Behind AI Integration – [01:32]
• Change Management & Internal Buy-In – [02:37]
• Member Response to "Stephanie" & Satisfaction Scores – [04:37]
• Impact on Care Team Workload & Satisfaction – [06:31]
• Diabetes Program & Identifying Hidden Needs – [07:56]
• Vision for the Next 12 Months – [09:10]
• Advice for Other Healthcare Leaders – [09:55]

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Conclusion

This episode offers a real-world case study of how a regional insurer is thoughtfully leveraging AI to increase reach and impact without sacrificing its "hometown" touch. Medical Mutual’s experience illustrates the power of transparency, careful change management, and the surprising willingness of both members and staff to embrace AI when it supports—not supplants—the human experience.

Transcript

[A]

Hi everyone. This is Grace Lynn Keller with Becker's Healthcare. Thank you so much for tuning in to the Becker's Healthcare podcast series. Joining me for today's discussion is Betsy Williamson, R.N.B.S, mHA, Vice President of Quality Performance and Population Health at Medical Mutual of Ohio. So Betsy, thank you so much for being here today.

[B]

Good morning, thank you for having me.

[A]

And let's dive right into this conversation. So you lead Quality Performance and Population Health. One of the oldest health insurers in the country, Medical Mutual of Ohio was founded in 1934 and serves over 1.2 million members. For people who don't know Medical Mutual, what makes the organization different from the larger national carriers?

[B]

Yeah, that's a really great question and one we really like to talk about. So Medical Mutual, we're known as the hometown insurer. We are a mutual company, which means that we are owned by our members and not by Wall Street. And that really gives us the ability to focus on our members, our employees and our communities, which we do a lot with. We live in the same neighborhoods as our members do, we use the same providers, we are shopping in the same stores. So we really understand our members needs and what is happening within the community, which allows us to really care for our members in a better way.

[A]

And one of Medical Mutual's brand promises was you call us, you get a human. And that's almost the opposite of what most people think AI is about. So what made you decide to bring an AI healthcare agent in despite that ethos?

[B]

So we recognize that we do a really great job. And you're right, we are known for our member services and our care team and working directly with those members. But we also know that when we can work together with those members, that we can make a, a measurable impact in their lives to help them be healthier in whatever stage that is. And so in order to do that, we really need to be able to scale it. And not everybody needs to speak directly to a live human, but they do need to make that connection and be able to get directed into a live human when there is a need there. So I think realizing that Stephanie does not replace humans, and Stephanie is the name of our AI agents, but she actually augments it so, you know, we're able to expand more and reach more people and help them through their journey.

[A]

And every payer executive in this room is dealing with some version of internal resistance to AI. So how do you get your own team, especially frontline staff and leadership, to be comfortable with this?

[B]

Well, Grace, honestly, the train's already left the station. Right. You're going to either be on the train or you're going to be on the platform. And I think that it's important to recognize that one in three people today are using some type of AI to explore healthcare decisions, healthcare problems. And so if we can intervene in that piece and be available to them to help them make the final decision, that is where we really need to be. So I think the big piece that everybody, as they approach this really needs to worry about change management. So letting their staff realize that we're augmenting them, we're not replacing them, that they are part of the solution, that they understand the escalation process, the preparation that goes into it, the testing. You know, we were able to give our call center 30 second scripts for every single use case we have. And we have 12 use cases right now that are out there. And we also informed our members know anytime that Stephanie calls a member, she is in, she's letting them know that she is an AI agent that is part of medical mutual. So the members aware that they're talking to an AI agent and they also are aware that at any point they can touch a button and get a live person. We also, in addition to that, when we were first rolling it out, we sent out member flyers and let the members know that Stephanie was going to be calling them. And I think that was really the key that got us our highest completion rate was letting the members know and they're aware. So when they answer the call, they're willing to talk. So it is really a compliance first process and we've had zero data breaches by doing that.

[A]

That's wonderful. And you launched Stephanie across 13 programs covering everything from chronic disease management to medication adherence to onboarding. And I'm curious what surprised you most about how members responded?

[B]

I think that the thought out there is that people don't want to talk to AI and that they're not going to answer the phone. And I think that we really saw that that's not the case. Members are embracing AI just the same as everyone else with whether it's ChatGPT or Copilot on your phone or your devices or Alexa or any of a number of other ones that we have. But we did see similar acceptance rates with humans versus our AI agent and satisfaction rates with the call. We got 9 out of 10 satisfaction rate with Stephanie and that had 93% of those rated her a 7 or higher. So it was all very positive. And then we are seeing that Stephanie is able to take Time, she's not held to call center metrics, so she doesn't have an average handle time. So she's able to make those relationships. And she is probably the greatest expert I've ever seen in motivational interviewing. So she's able to catch on those little key points that a member might throw out there for a customer service rep that they might miss that would trigger them to need additional help. So we've really found that she's been a great addition to our team. And we did some internal studies as well that showed that members find that she's able to explain difficult, complex situations like member benefits, sometimes better than our human agents are. So overall, I think it's been a very positive experience and the. That people want to engage, probably the biggest thing that came forward.

[A]

Absolutely. And kind of on the flip side of that, there is a lot of fear that AI will replace jobs. So what actually happened to your care team's workload and focus once the AI healthcare voice agent was live?

[B]

So once the AI voice agent was live, we saw 360% capacity within our care teams, which really allowed them to work work with those members that needed their help. We had 93% of the calls that Stephanie made were resolved with just one touch with Stephanie that didn't require human intervention, but there was 6.7 that did. And those were the ones that had that low health confidence. And so they were able to connect with our nurses, our physicians, our pharmacist, our care teams customer service, and they were able to work through some of their concerns and get them where they were. And, you know, I think that this has really improved our employee satisfaction as well as member satisfaction, because we're able to touch more. So the employees are feeling more connected to us as their health insurer. And it just goes back to driving home that we are home health or hometown insurer. But it also, our employees are much more satisfied in the work that they do because they're just not cold calling people or they're not just taking calls that really doesn't work at the top of their license. So now they're really making a difference where they need to make a difference.

[A]

Absolutely. And I'd love to know, can you walk us through a specific program or moment that made this feel real for you where you thought, okay, like this is actually working for us?

[B]

Yeah. So one of our first use cases was with our chronic condition management program for diabetes, and we require them to engage with a coach and get very educated on their diabetes program. And then once they graduate from that program, we still require them to call in on a quarterly basis and do a wellness check in on how they're doing, what their hemoglobin A1C is, and if they do that, then they get their diabetic supplies for free. And so through these calls, we had very high engagement. And we also found that there was 19.1% of members who actually disclosed some things like anxiety, loneliness or even financial hardships, which were all signals that are invisible on a claim. And we were able to intervene and get some care out through there, find them resources in their community and help with that as well. So I think that's a really big win.

[A]

Absolutely. And so looking forward, you've launched with several great use cases that you've already seen success with. So what does the next 12 months look like for Medical Mutual and your AI healthcare voice agent?

[B]

Well, I think that we're still brainstorming. The number of use cases, really, I believe, is infinite. And we want to look at how do we expand our full population. If you're able to deepen the population health and the condition management activities that you do with the members, you're able to really drive that relationship. So you will know earlier when there's a problem that's arising, which will really help with driving down medical costs and improving outcomes overall for the members. So, you know, our vision right now is really continuous member engagement and early intervention and strong relationships.

[A]

And if another payer executive came up to you after this podcast and said that they were interested but said they don't know how to get started, what would you tell them?

[B]

I would say take the time and pick the right partner. You need to have somebody, especially in a situation where it's clinical, that has the priority of safety first. And then I think you need to build trust with that partner and be completely transparent with your teams. The more transparent you are with the teams, you're able to remove the fear and the stigma that they're not going to have jobs. And then, of course, a great change management plan.

[A]

Well, Betsy, thank you so much for sharing your time and these insights today. And you can tune into more Becker's Healthcare podcasts by visiting our podcast [e-mail] thank you.