Transcription:

Bill Klaproth: On this episode of SHSMD podcast, we are preparing you for a new generation of data and technology as we talk about the impact of artificial intelligence and machine learning on healthcare marketing with Daniel Fell, senior strategist at Optum. Artificial intelligence. People have said that about me. I got to think about that. Anyway, let's talk with Daniel and get this episode started right now.

This is the SHSMD podcast, rapid insights for healthcare strategy professionals in planning, business development, marketing, communications, and public relations. I'm your host, Bill Klaproth. And in this episode, we talk with Daniel Fell, who is the senior strategist at Optum working in the data and analytics solution group about the impact of AI, artificial intelligence, and machine learning on healthcare marketing as we prepare marketers for a new generation of data and technology.

Danny, welcome to the SHSMD podcast. And he said, I could call him Danny, because, well, because he said I could. Anyway, we start every episode of the SHSMD podcast with rapid insights. One quick tip someone can use to make the marketing communications better today. Danny, give us your rapid insight.

Daniel Fell: Bill, thanks for having me on the show. And I would say starting with the end in mind, measuring what you want to have as a final outcome. And marketing is super important. And sometimes we get going down the road before we really define that and get everybody on board with it.

Bill Klaproth: And that is your rapid insight. I love that, begin with the end in mind. That is so important. And as we launch into our topic on artificial intelligence, beginning with that end in mind, hopefully artificial intelligence can help you get there more efficiently and with less work. So how do you define artificial intelligence today? What does all of that include?

Daniel Fell: Yeah, you sort of summed it up for me. It can be a little challenging today. We use that term. It's very popular. It's been a little over-hyped in the last few years and we hear about AI showing up in everything from automobiles to refrigerators, right? But I would say a fairly straightforward definition might be something like the replication of human intelligence in machines that are programmed to think or act more human-like. So in other words, as we get more sophisticated with computer programming, the devices that we're using that program in become more intelligent or appear more human-like. And I think that term AI is a nice descriptor, but it also can be a little general. So sometimes we use the term machine learning, which is really a subset of AI. But much of what we think of as AI today is really machine learning.

Bill Klaproth: Right. So I like how you put that the replication of human intelligence. It's kind of easy to understand how AI works then. So, is that what makes this potentially so powerful and different from what we marketers have done in the past?

Daniel Fell: Sure. I think fundamentally there are two things that make machines or if you want to think of it as computer programs. Two things that make them more powerful, right? One is the speed at which they can process information and you can argue that the human brain is actually faster at processing, but the reality is we are continuing to make computers faster and faster.

The second is the sheer amount of information that computers can process at one time. And here's where I think computing power has an edge over the human brain. Computers can literally process thousands or millions of bits of information really effectively and really quickly. So if you're in a profession like marketing, which relies heavily on cognitive skills, like problem solving and thinking, computers allow us to analyze a lot of information really quickly and derive really distinct benefits from that.

So two examples might be the ability to develop marketing insights or to implement or act on those insights with lightning speed. So there's a technique of digital advertising called programmatic buying. And that's just one example of that.

Bill Klaproth: Well, those are really good examples. Can you then give us some examples of AI in marketing and specifically healthcare marketing, an example of how that would look?

Daniel Fell: Interestingly, AI or machine learning is actually being used in a lot of areas of healthcare today. But let's focus on your question, which is marketing specifically. I mentioned programmatic media buying. Over half of digital advertising today, if you look at every industry, is driven by programmatic buying and healthcare marketing probably isn't that high. Hospitals still do a lot of traditional media advertising and rely on some more basic digital media channels, but it is growing and many leading health systems are starting to use more programmatic buying through some of their digital media partners or their agency partners.

Another area that I focus on is predictive analytics. So I mentioned the unique ability for computers to process millions and millions of bits of information, or to learn from that, new things about that data, and so finding insights or finding patterns. So an application that we're working on that relates to this is taking literally tens millions or hundreds of millions of health records and healthcare data, and building highly accurate predictive models about what consumers' healthcare needs are or what healthcare conditions they might have.

So you can imagine that armed with this, marketers can now be a lot more targeted in their marketing and communications programs because you can actually identify consumers who have a high likelihood of having heart disease or a high likelihood of needing orthopedic care. So rather than sort of advertising everyone in the community or even maybe segmenting based on age ranges or gender, we have the ability to target individuals and that, to your earlier point, makes marketing much more effective and it makes it much more efficient.

So other areas might include things like the algorithms that drive Google search results or drive social media posts or marketing automation platforms. I think it's really important that marketers understand the technology behind this, because it helps them understand how to apply it, but also how to understand why it drives, what works and what doesn't in marketing today or healthcare marketing specifically.

Another really exciting area that I see growing in healthcare marketing is the use of things like chat bots and intelligent knowledge platforms where people type in a question and get an answer back. It's really interesting applications for AI in real time, relevant, effective communication with consumers and patients.

Bill Klaproth: Yeah, that's really interesting. The point you brought up about the chat boxes. I didn't think of that as AI, but now that you say that it makes perfect sense. And another benefit of this, you were talking about how you can easily target a specific market. And it does it automatically, right? You don't have to think, "Oh, I need to send an email out to somebody that might need a colonoscopy." You can set this, so it's happening in the background automatically. Is that correct?

Daniel Fell: That's right, Bill. And it's interesting too, when you really begin to learn, there's sort of two sides of AI or machine learning. One is what we think of is rule-based. So you set up sort of an if-then statement. If the person does this, then we're going to deliver this message or provide this response. That's kind of rule-based.

The other is really what gets into more of the advanced machine learning or AI, which is where the computer itself is learning from the interactions and the knowledge. And it begins to make decisions on its own. So sometimes that's referred to as deep learning or neural networks. And that takes it even to another level, right? You don't have to write all those rules out, but the computer can begin to understand and begin to make decisions around how to manage things like responses for communication or a chat bot.

Bill Klaproth: Right. So what do we need to have to put this in place? What types of resources or capabilities do marketing departments need to have in place to take advantage of this type of technology?

Daniel Fell: Great question. So one place to start in this podcast is a great example of it is simply raising the awareness of understanding of what AI is and isn't and how it's being used in healthcare, in marketing and healthcare in particular.

So broadly speaking, I think of it is there's clinical applications. There's operational applications in healthcare and there's marketing applications. And I think it's important for marketers to be familiar with all of these areas because often we're the ones charged with communicating out how we're using technology and data and things across an organization. You can create a knowledge center for your marketing team. So that's one step where you may be bringing together experts, bringing in outside experts. You may be doing cross-functional knowledge sharing, right? So working with your IT department, working with finance, other areas of the organization to sort of jointly pool your knowledge and understanding of where this technology is going.

As part of the marketing focus, I'd recommend doing an assessment of where you're currently relying on some of this AI. Some people may not even realize some of the things they're doing like the programmatic media buying truly has its roots in AI and machine learning. Understanding what knowledge and skills your team has, right? Or how you're using data and analytics today. And while data and analytics, aren't always AI specifically, they're all core to what AI is. And I think that will help organizations be better prepared as well.

Bill Klaproth: So you could do an audit of your marketing systems and then say, "You know what? AI could help us in this area or this area, or this area." Is that kind of what you're saying as well?

Daniel Fell: Yeah, exactly. You know, I liken it to sort of the early days in the late '90s when the internet was just coming along and people were trying to understand, "Okay, what is it? But also what kinds of applications exist today?" But also trying to project out, you know, what might come five years from now or six years from now that I need to be planning for, I need to be prepared for, so I'm not playing catch-up.

Bill Klaproth: So is AI at this point in time, like we were at back in the late nineties, since you mentioned the internet back then, is this kind of where we're at with it? And this is just going to continue to grow and we all know how websites and the internet has exploded the past 20 years. Do you see that same trajectory happening for AI?

Daniel Fell: Yeah, a really astute question. And I do. I think, again, it depends greatly on where you are in the world, what industry you're talking about, what specific applications you're talking about in terms of how far along they are in actual use and every day incorporations in what we do. But I think your analogy of maybe where the internet was in the early 2000s is probably a good, analogy and one that you could apply to things like artificial intelligence today.

Bill Klaproth: Right. When we all first went on Google, "What does this thing do? How does it work?"

Daniel Fell: Or Apple World or Copyserve.

Bill Klaproth: Yeah. Oh, my God. "Windows '95 is here. Windows '98 is here."

Daniel Fell: think I still have some AOL disc. I'm probably dating myself, but...

Bill Klaproth: "You have mail." Oh, gosh. We all remember that. So, Danny, are there some concerns? Because, you know, there is a flip side to this generally as well, or are there areas of caution that you would give marketers as well?

Daniel Fell: Sure. I think the most important thing is not to get too caught up in the hype. And that could either be overly persuaded by some far out tool or solution that you get introduced to, or the opposite, which is maybe you get overwhelmed or fearful or hesitant of jumping into this and realizing that when you sort of strip away that hype, it's a very real practical solution for many things today.

There are also some aspects that make AI important for marketers to be aware of. So, AI, like any technology, requires ongoing investments in learning and tools and testing and what doesn't work and what needs to change. And without that investment, AI could result in unintended consequences such as biased results.

Privacy, security are important. Those are true for any data or digital marketing that an organization is doing. But I think the more awareness and the better education and things like good data governance go long ways towards addressing those concerns a marketing group.

Bill Klaproth: Yeah, really good information and good to understand that as well. So, Danny, we're all interested in this and I think most of us realize the train is leaving the station and we all better get on board on this thing because it's definitely coming. Where can we learn more about AI so we can really understand its full potential and how we can implement it into our own systems? What would you recommend to us?

Daniel Fell: Sure. I'd start with just reading and absorbing what's happening with AI industry out there, not just healthcare today. So, if you're into cars, you might want to understand the AI behind a company like Tesla, or if you're a sports fan, you might want to understand how data and analytics are being used to predict the performance of sports teams or individual athletes. And I think you can learn a lot by just becoming more familiar with the general applications of AI and machine learning, because a lot of those base AI principles are being used across many industries.

For marketers. I know that SHSMD is expanding the content around this topic. So I'd be on the lookout for conference presentations and blogs and podcasts like this one. The American Marketing Association has some really good resources. They actually have a very cool infographic. I think it's titled What Marketers Need To Know About AI. That's on their website. You can download. They have some other good articles and resources out there as well.

Bill Klaproth: Danny, that's great information. Thank you so much for passing along those resources, because we do need to start educating ourselves on this and researching and learning kind of like the internet has transformed our day-to-day life. It sounds like AI and machine learning is going to transform what we do in 10 to 15 years and beyond.  

Daniel Fell: I think even sooner than that, but I think it's going to be really, really a big part of marketing going forward. And so it's important for marketing professionals, whether you're mid-career or just starting out, to really understand some of these technologies and principles and be able to apply them.

Bill Klaproth: Really good stuff. I'd love to have you on like for a yearly checkup. "Hey, here's where we're at."

Daniel Fell: We should it.

Bill Klaproth: Yeah, that'd be great.

Daniel Fell: It's been a pleasure. It's been a pleasure to talk with you and I hope your listeners got some good, helpful takeaways from the conversation.

Bill Klaproth: Absolutely. Danny, thank you so much. Really informative. And again, pleasure to have you on. Thank you so much for your time. We appreciate it.

Daniel Fell: Take care. Bye.

Bill Klaproth: That's Daniel Fell. And please look up those resources and lean on SHSMD to learn more about AI. This thing is coming and we all need to get on board. What a great topic and great discussion. And we thank Danny for that. And to learn more about SHSMD, please visit SHSMD.org, that's S-H-S-M-D dot org. You can also visit our education page to learn about our upcoming programs at SHSMD.org/education.

And if you found this podcast helpful and, as always, come on, how could you not? Please make sure you share it on all of your social channels and please hit the subscribe or follow button to get every episode. This has been a production of Dr. Podcasting. I'm Bill Klaproth. See you!