Introducing OmegaHealth, Cardinal’s AI growth operating system

Announcer: Welcome to the Ignite Podcast, the only healthcare marketing podcast that digs into the digital strategies and tactics that help you accelerate growth. Each week, Cardinal experts explore innovative ways to build your digital presence and attract more patients. Buckle up for another episode of Ignite.

Lauren: Hello, everybody. Welcome back to Ignite: Healthcare Marketing Podcast. Today we have Rich Briddock, a familiar face, our chief strategy officer, and we’re going to be talking about the launch of Omega Health. I think I really want to spend today, Rich, getting into the underlying framework of what is Omega Health, the use of AI in agency world, in healthcare. Tell me a little bit about the concept of Omega Health, where it came from, and some of the problems that we’re looking to solve.

Rich Briddock: I think, obviously, AI is becoming so central to the way that everybody is working. There’s probably not very many people out there who have a desk job that aren’t using AI in some form or another.

Lauren: Might be surprised.

Rich: Whether it’s a casual glance at ChatGPT or very sophisticated systems that are enabling an entire organization. I think what we started to see is a lot of utility in leveraging AI to do two things, really. One, to make work more efficient, but also to make work more consistent, and to allow us to get to work that had previously been elusive in terms of just the amount of time, the amount of bandwidth that we had as an agency to spend on clients. Anything that we could bring Omega Health in to help us achieve and to reduce some of that busy workload—that’s more time that we can spend on planning, more time we can spend on strategy, more time proactive test-and-learn agendas.

We got to a point with AI where we felt pretty confident that we could bring a product to the market that was going to be safe, secure, compliant, but was also going to be good enough with the advancement of these models, these LLMs, where we could delegate some of the work that was previously being done by specialists to Omega Health so that those folks could then spend time doing more of that strategic work.

Lauren: I think that’s going to sound very scary. It sounded scary to me when we first talked about it. Delegating work to a generative engine sounds scary.

Rich: Yes.

Lauren: The reason why we’re not just delegating to ChatGPT, or to Claude, or to Gemini—talk about that because those tools exist, and it’s why not just go have them run this analysis or create this PowerPoint, why create something totally different?

Rich: The short answer is context is king. AI can be a 5% value add, or it can be 100% value add, depending on how much context it has. The way that we have built Omega Health is, not only is it ingesting data that is not PHI, just want to be very clear about that, but not only is it ingesting all the right data, all the historical data points from ad accounts, from data warehouse, in terms of client performance reporting, it’s ingesting creative ad libraries, it’s ingesting all the settings, all the functions that we have inside of these accounts and how we run them, but it’s also ingesting client context, communication, emails, Gong transcripts, so it knows what’s going on. It’s almost like it’s a member of an extension of the team. Unlike a human, it doesn’t forget things.

It’s very useful in terms of helping the team to tie the work that needs to be done back to the need of the client or the need of the account.

Lauren: The business.

Rich: The business, because it can always keep that front and center. The other thing that Omega Health is feeding off of, and we’re going to get to the discussion point of why healthcare-specific AI, is it’s feeding off of the knowledge base of how we operate as an agency. The way that we run accounts, our best practices, our SOPs, our methodologies—all of that is being fed in as its knowledge base, which is obviously a lot more effective than just going to Claude.

Lauren: Yes, those engines don’t have that.

Rich: They don’t have that.

Lauren: That’s why we’ve been hired, right? For that knowledge base.

Rich: Right. Then the other thing it’s doing is it’s feeding off of our partner ecosystems. We use a lot of healthcare-specific partners. On the audience building side, we may use Rango, PurpleLab, Definitive. On the tracking side, we might use LINE; there’s Freshpaint, et cetera. We’re feeding knowledge from all of those partners—how they operate, what they can track, what they can do into Omega Health. It’s not just understanding how we operate; it’s understanding how healthcare marketing, writ large, operates.

Essentially, what we’re trying to do with Omega Health is distill all of Cardinal’s secret sauce into a technology platform that can just help us be more effective at delivering the solution that we’ve already been delivering.

Lauren: Yes. Talk to me about some of that in daily practice. Take a media specialist, an SEO specialist, a creative specialist. How have their daily lives changed, and how is that ultimately benefiting the client versus the common fear or opposition statement, which is, “It’s diluting the quality; it’s watering down the delivery”? What is the ultimate gain for both parties?

Rich: To flip that last statement on its head, that AI cheapens the work or makes it—AI slop is a term you hear—makes the work less credible. I would flip that on its head, and I’d say, “With the right inputs, AI narrows the gap. Every services business, every people-driven business, the problem has always been sometimes the output of the work is dependent on how good the individual is who’s working on that account.”

What Omega Health is designed to do is, if you have someone who is more junior versus someone who’s more senior, it’s actually narrowing the gap in the work quality because it’s giving that more junior person so much more of a leg up because it’s got all the context, it’s got the knowledge, it knows how to generate the responses. It’s also increasing the speed of which we can get a response to a client.

In an old world—I’ve been using this example when I’ve been talking to our CS team—you may have a client that’s like, “Every ad with this type of creative, this hero in the image, or that uses a green background, I want to know how that’s performing on Meta compared to how my other ads are performing.” Or, “We had this creative concept; I want to know how that’s performing.”

Lauren: Multiple platform.

Rich: In the old world, that CS person is going to a media person, that media person is going into a platform, they’re downloading all the ads, then they’re having to partition out the ads that they’re speaking about, create pivot tables, create charts, push that back to the CS person.

Lauren: Compare it to the other data.

Rich: Yes, do the analysis. In the new world, you go to Omega Health, you forward that email directly into Omega Health chat, and Omega Health will do the analysis for you as a CS person. Because we have creative tagging, it will be able to pull out every ad that’s got a green background or every ad that features this woman as the hero, and it will give it to you in an HTML document with line charts, summaries, individual breakdowns, et cetera, that A, is a better deliverable, and B, is generated rapidly while the team can— You asked me what the benefit is.

Lauren: Yes, so what is the team doing when they’re not doing that report, right?

Rich: The team, they’re optimizing the account, they’re building strategic deliverables, they’re working on the test-and-learn agenda, on the roadmap. All those pieces that could be delegated are being delegated. The team can do only the things that they can do best.

Lauren: I think you said something really important there, too. The inputs are incredibly important. That report is only made possible because we have a very specific creative tagging framework that we use for multi-location, multi-brand healthcare groups, right?

Rich: Right.

Lauren: Without that, that report is not possible. There’s the underlying work and framework that has to be in place, plus the output and what the team is able to better spend their time doing.

Rich: Also, just to dispel this fallacy of “Agencies are just using AI to enrich themselves,” just something to address there, which is this isn’t cheap. The standing up of your own agentic operating system is not super cost-effective.

Lauren: Engineers, all of the actual usage.

Rich: Engineers, tools, development costs, all those things, tokens, et cetera.

Lauren: It’s a shift.

Rich: It’s about enabling the team to be more effective, but the cost center is shifting.

Lauren: Yes, it’s a shifted cost center. It’s not all salaries anymore, but it is not necessarily a cheaper solution.

Rich: Correct, that’s exactly right.

Lauren: Right now, our goal is to become an AI-native growth firm. AI native meaning it is native to how and what we do. There was no world before it. Your job does not exist without it in your daily practice. That’s not where agencies are today. Everyone’s working towards that. We are working towards it. I assume others are as well. Our team is currently using platforms like this to surface anomalies and campaigns, raise flags before a human could catch them, expedite reporting so that they can spend more time writing insights than generating the charts themselves, things like that. What is the future state? That’s just us using the tool to improve how our people operate and what they can deliver to clients? How do clients become part of this in the long term?

Rich: We’re about to build client access into Omega Health. Then again, that goes back to empowering the client to leverage the same toolset that our internal team is doing so that they can get to answers faster.

Lauren: A direct line into the collective brain of the team.

Rich: Yes.

Lauren: It doesn’t get much better than that.

Rich: I think the other thing too, which this new world is demanding, is transparency and accountability. I think gone are the days, or soon gone will be the days, of clients just not being aware of things that are happening. Every client is about to be aware.

Lauren: We’re excited about that because we’ve always felt like that transparency was key. That’s probably very scary for some situations where transparency is not part of the playbook, but we welcome it.

Rich: A lot of the tests that we’ve run in chat, chat will literally expose everything. If I want to know: “Was this setting turned on, and when was it turned on?” Chat’s going to tell me that. There really isn’t going to be anywhere—

Lauren: Chat within Omega Health.

Rich: Chat within Omega Health is going to tell me that. There isn’t really going to be anywhere to hide as an operator anymore. To your point, you can either run from that or you can embrace it. Yes, we’re very much on the embracing side.

Lauren: We’ve got some really cool healthcare-specific tools that we’re building within Omega. Talk about PulseCheck, talk about NextSpot. What are some of the tooling solutions? We’ve got Omega, the overarching framework, and then we’ve got some very specific features that we want to bring.

Rich: Ultimately, I think where AI is going, and we’ve referenced this before, is the mode is not just having an agentic OS, because a lot of agencies are out there building some version of an agentic OS. The mode is having a vertical-specific agentic OS.

Lauren: That has solved specific problems, exactly what your business is going through with a team of people who have qualified the inputs and outputs.

Rich: Exactly. You’ve got verticalized specialists putting the right inputs in; you’ve got the right partner ecosystem that’s feeding the tool; you’ve got the right knowledge base that’s sitting underneath the tool. Also, you’re building the right applications that meet the needs of your constituents.

One example, because you brought it up, NextSpot: it’s an agent that will go and it will scrape capacity for multi-location healthcare businesses and understand where there’s capacity, where there is not capacity, and then where budget needs to be shifted to support the capacity needs by location so that we’re not spending dollars in a place where the books are already full. There’s no patient to put in a chair.

Lauren: I love it. That was born out of our media team wanting more from our client partners in terms of operational data, booking data, seeing that their campaigns are performing well on the front end, but it’s just not translating on the back end, and wondering why is that happening and saying, “Let’s stop relying on our partners to have to go and find this data within their organization; let’s go find a way to get it ourselves.”

Rich: Exactly. That’s one thing that we’ve been able to do independently. The other area where, hopefully, Omega Health is going to be truly differentiated and excel is working with our partners. We have a bunch of data partners out there. One of the things that we have that is emerging, I would say right now in Omega Health, we’ve tested it for a couple of clients, is the ability to pull in claims data and to size a TAM to then build—

Lauren: In a chat, like quick chat.

Rich: In a chat, yes. Exactly right. Have a chat, understand: “Is that market increasing or decreasing in patient size? What are the relevant diagnoses? What are the relevant procedures?”

Lauren: “Where is geographic density for that patient type?”

Rich: Yes. “What do they look like from a demographic point of view?” Directly in chat, but then also being able to push that information into a media plan. “What are their consumption habits? Which channels do we need to be live on?” This is all happening in minutes.

Lauren: Versus, “Hey, let me get you a media plan next week.”

Rich: Or, “Let me reach out to this partner and hope that they get something back of us.”

Lauren: Yes, “They’ve got a two- to four-day turnaround, and then I need to ingest that information. Then I need to get on GWI and map that against usage, and then I need to build a plan.”

Rich: Certainly, that’s a great example. Another great example is: we have a lot of partners out there that are building their own MCPs. I’ll give you an example. We partnered with LINE. We’re using their MCP. Now in chat, if we have a LINE-enabled client, someone on our side or even a client could be typing in chat, “Hey, why is my CAC going up?” We’re actually going to LINE’s dataset and checking, “Well, actually, your missed call rate went from 20% to 50%.”

Lauren: “Someone at the front desk went on vacation. What’s happening?” Yes.

Rich: It’s not just marketing challenges. We’re able to unearth business challenges, operational challenges.

Lauren: Yes. With the ultimate goal of driving more patients for our clients, regardless of whether our solution set can specifically solve it or we can at least help you identify it and bring in the right partner to fix it.

Rich: The way I think about Omega Health is obviously most people, especially our age, have seen The Matrix, but it’s almost like you’re sitting in that chair and you get plugged in. I just want to learn how to fly a helicopter. It’s that amount of information that’s just getting pumped in via chat that’s way beyond what a person could just keep track of.

Lauren: Using that analogy or likening to The Matrix, it’s an operating system to enable humans.

Rich: Absolutely.

Lauren: That component is not going away. It is every marketer on our team being able to plug into a knowledge set that they otherwise would have to spend time, energy, and collecting from other people.

Rich: Yes. You still need Neo.

Lauren: Yes. It doesn’t work without it.

Rich: It doesn’t work without it.

Lauren: [crosstalk] [unintelligible 00:15:58]

Rich: [chuckles] Yes. AI is an augmentation of the expertise that already exists. It is not a replacement of those things. I think the idea of a company just going out and being like, “I don’t need my marketing team anymore. I don’t need my agency anymore”—this message may seem somewhat self-serving, but I do believe it, it’s not the correct way to look at it. It’s the 1 +1 = 3 of a fantastic team that really understands what they’re doing and can deliver these results yet leveraging smart technology. It’s nothing new. Humans have been doing this forever. We’ve always been innovating to deliver better, to deliver more, to deliver faster. This is just the next iteration of that.

Lauren: Rich, at Scaling Up, you just did the live demo of NextSpot and an overview of our PulseCheck, our health check. If you missed that session and didn’t get a chance, in that we offered early access to clients to get into the tools for free for the remainder of the year. A reminder to those listening that you still have a chance to do that. If you’re listening to this, reach out to us. Let us know. We want to get you in the tooling. Get you a chance to see how it works. Let you mess around with it. It helps you guys, and it’ll also help us pressure test the tool.

Rich: The tool is always emerging with new features, always evolving and changing.

Lauren: We need answers.

Rich: Yes. Exactly. The feedback is the most crucial piece to that. As much usage as we can get, that’s what we’re looking for right now.

Lauren: All right, guys, let us know if you want to be part of it. Thanks, Rich.

Rich: Thanks, Lauren.

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