2024 Health Trends: Managing the Healthcare Revolution

Nervousness and uncertainty surround the question of what Artificial Intelligence (AI) may mean for the future of work. How can we deploy AI transformation—thoughtfully—across an organization and help workforces see what the new models will signify and require of us?

In the first episode in this series related to our 2024 Health Trends, host Jeff Stewart is joined by Celeste Mosby, Senior Vice President and General Manager of Syneos Health Learning Solutions, to discuss the challenges of managing this healthcare revolution, especially in terms of training and adapting to the rapidly evolving landscape.

The conversation highlights the shift in the industry over the past five years, where technology, data and AI are now shaping the healthcare landscape—requiring professionals to keep up with the dynamic changes—and explores the impact of AI on human-to-human interactions, workforce training and the importance of thought leaders staying ahead of evolving trends.

For additional insights into Revolution Management, Learning and Change in the New World of Work—as well as the year(s) of reinvention ahead for the life sciences sector—download our 2024 Health Trends report.

The views expressed in this podcast belong solely to the speakers and do not represent those of their organization. 

If you want access to more future-focused, actionable insights to help biopharmaceutical companies better execute and succeed in a constantly evolving environment, visit the Syneos Health Insights Hub. The perspectives you’ll find there are driven by dynamic research and crafted by subject matter experts focused on real answers to help guide decision-making and investment. You can find it all at https://www.syneoshealth.com/insights-hub.

Like what you’re hearing? Be sure to rate and review us! 

We want to hear from you! If there’s a topic you’d like us to cover on a future episode, contact us at podcast@syneoshealth.com. 

Transcript

Jeff Stewart:                     
Just how do you manage a revolution? I'm Jeff Stewart from Syneos Health Consulting. AI is revolutionizing the healthcare industry. How do we manage this revolution? I'm joined today by Celeste Mosby, senior vice president and general manager of Syneos Health Learning Solutions. Revolution Management, Learning and Change in the New World of Work is one of this year's top health trends published by Syneos Health. [00:00:30] Managing the healthcare revolution today on the Syneos Health podcast.

Celeste Mosby, welcome back to the Syneos Health podcast.

Celeste Mosby:               
Hey, thank you for having me today.

Jeff Stewart:                     
The world has been changing a lot and you are head of Learning Solutions at Syneos Health. You train those in the entire pharma industry over and over again and things are changing so quickly. How do you keep up?

Celeste Mosby:               
[00:01:00] Well, that's the million-dollar question. I would say about five years ago, if you had asked that question, we were keeping up quite readily because what we were doing in the industry was outpacing technology transformation data. And now, it's quite the reverse. Right? Data, and technology, and AI and all those things are impacting our world so drastically [00:01:30] and it looks one way today and another way five days from now. And so what we're trying to do in our space around training transformation and the evolution of communicating to the workforce, how they stay true to themself as human to human interaction, yet how they can use data and technology to help them on the job is definitely for those in the role of what we do, a [00:02:00] monumental task. And I would say it's just having thought leaders on your team that are staying well above and in front of the way things are evolving. So that we know what to put in place and how to be forward-thinking, I would say.

Jeff Stewart:                    
If I think myself, Celeste, on what happened in COVID and then how the business has changed in pharma today, a lot changed. But it wasn't because [00:02:30] technology was suddenly different, it's because people suddenly got a lot of experience using the darn thing. Video conference technology did get better, don't get me wrong. It did get better, but the biggest change was a social change. We got used to it, we started using it. And once we became comfortable with it, then the world changed. Is that what you're seeing or is it something different this time?

Celeste Mosby:               
Yeah, what a great question. I think, [00:03:00] yes, you're so right. I think the industry wanted to make this change in how they touch HCPs, how they touch patients. And it was, for us, back in COVID, it seemed like it was going to be another 10 years out. And so during COVID, that changed a lot for us because we all started to utilize technology to interact and engage each other and then that's including a lot of the patients that went into clinical trials and [00:03:30] a lot of the interaction with field teams and HCPs. So what that did was made people, they had to feel more comfortable with technology. They had to feel more comfortable with how that interaction was. So now, I would say it is a little easier to get in front of people and say, "You're going to do things digitally and you're going to do things virtually."

I will say that there's still some, we call it digital trust. And so what that is [00:04:00] is really the right communication, the right training, the right insights that tell people this communication virtually, digitally, or face-to-face is working. Then they're really up for it. And I see people open to change, but we can't just tell them to do it. We have to make sure that we are teaching and training them how to do it well and then we see better results.

Jeff Stewart:                     
So if we're talking about AI, which everyone's [00:04:30] talking about AI, and in a few years probably we won't be talking about AI any more than we talk about email. It's just something you use at some point. But I'm wondering and a little bit worried, Celeste, if this time it's different in a bad way. And here's the bad way, it's not the Terminator, too bad way. I'm talking about the bad way for getting adoption within a company, especially a pharma company with many of the technologies that we had, [00:05:00] things like video conferencing. Once those at the top used it, then it tended to filter down. You became comfortable at the top, and then the meetings at the top started to become distance meetings. And then other people use them and then everyone uses them. But if we're talking about doctors and people in pharma, those are the last ones I would expect to be using ChatGPT or AI. So are we [00:05:30] thinking about how we get adoption through organizations or even something like with physicians when, gosh, getting a physician to use a computer was hard?

Celeste Mosby:               
Yes, it's true. I think, right now, the pharmaceutical, and healthcare, and medical industries are so ready for this transformation. I would not have said that at all, Jeff, five years ago. But I think everyone is seeing that there's so much potential [00:06:00] for really impacting patient care. When we think about why we do what we do in all of our roles across the healthcare industry, if you think about it at the end of the day, we feel good about the impact we're having on bringing better medicine and innovative medicine to patients. So a lot of times now when I speak to these top thought leaders in medicine, I was just talking to the head of neurology at a really big [00:06:30] institution in Boston, and she also leads research at Harvard. Her point was that it's ridiculous that there's 500 patients waiting to see her, right?

And her point was her goal in life is to use technology and AI to get to some of these patients as they're waiting to see her. Their AI is converting some of the insights and helping medical [00:07:00] teams with medical practice. So that they can play a role in intersecting and treating these patients quicker while they're waiting maybe to see some of the thought leaders in medicine. It's kind of a little bit of emotive balance around people realizing that we can make a difference with technology. As long as we are accountable, we build trust with patients and healthcare provider [00:07:30] teams, and we show them results and use cases. That's why you're seeing so many healthcare providers using this.

Jeff, quite frankly, they're taking electronic health records now and they're building in these platforms, chatbots and AI chatbots to actually talk to patients about, based on what their records are saying. They're pushing them to education, they're pushing them to AI chatbots, they're pushing them to other healthcare providers like nurses and [00:08:00] PAs while they're waiting to see the physician. That's why this is so exciting.

Jeff Stewart:                     
So you're comforting me that perhaps those at the top doctors and physicians in the cases of certain healthcare systems and within pharma with the C-suite, that they're at least highly interested in AI. And in the case of physicians, they have a pain point. Their time is overwhelmed. So they would [00:08:30] like to offload some of that work, some of the work that they do to AI. So there is a clear use case. Are you seeing that clear use case in pharma? Are you being asked to train on that or is it too early yet to be asked to be training on AI?

Celeste Mosby:               
We are. And we had to really jump on that right away because what was happening across the pharma industry [00:09:00] to your question was people were doing it anyway. But if you don't train them, they're not doing it effectively, efficiently, and compliantly. They're just doing it. So if you train folks on, for instance, generative AI is the thing that gets people to some of those things that helps them get to knowledge a lot quicker. But if you are leaving some of those things out in the open AI that you shouldn't be, that's a bad thing. So if you teach people how to do [00:09:30] it, what we're finding is that when we put, say CRAs, investigators, just field teams on the medical and commercial side into practical application about how to use generative AI, people are feeling much more comfortable that they're doing it the right way, they're doing it a safe way. They're not going to get in trouble.

And quite frankly, some of the outputs are helping ease the time to proficiency [00:10:00] for what they do, right? So if they're preparing to talk to key opinion leader, they're going with information and insights that can better help. Technology is really helping them come up with immersive application to use cases quicker than they ever have before. So we're building AI into a lot of platforms. We're building AI into a lot of learning platforms to push people to recommendation engines based on what [00:10:30] insights are saying. So there is no way around not teaching people how to use AI because that adoption and that trust goes up tenfold when we do.

Jeff Stewart:                     
It does strike me, Celeste, as you're talking through this. That the C-suite, even though they may not be asking AI to answer any of their questions, they are being asked questions about AI. And the two questions that I understand they're being asked 'cause I hear it. Number one, what are you doing [00:11:00] about AI? That's a clear question being asked at every investor conferenceSo they're getting asked that question, so they're asking that question of those in their organization. And number two, how do you keep AI from letting the rest of the world know what you're doing? Essentially, how do you keep AI from doing the wrong thing? That's one example, but another [00:11:30] one would be a really important example in patient care. How do you keep AI from telling the patient to do something from doing something completely stupid, wrong, et cetera?

Celeste Mosby:               
Yeah, so one of the things as AI platforms are being built is the... When patients, or physicians, or anyone that's a healthcare provider goes out to the open AI environment, [00:12:00] there's the chance of that, right, Jeff? Because there's a term called hallucinations, like things come back because AI is picking from so many different data sources in the open AI environment. And that's why you'll see in healthcare, and in medical environments, and for patients and healthcare teams, we are refining the search features for them with AI. So [00:12:30] we're either curating the content that they should be looking at, that's within the AI platform, or we are looking at the data analogs that are on the backend. And how those need to come together to make those hallucinations either go away 100% or there's less of a chance that there's going to be a hallucination that says something crazy.

Now, on the other end of this, we have to remember [00:13:00] that human to human contact and human actually looking at the insights to say, this makes sense, cannot go away. What AI has done for us, it's lessened the time to knowledge and proficiency of getting the right insights. But it still needs the human eye to say, "Oh, this makes total sense." And checking it against other data sources and things like that. And that's why we're opening up a lot of platforms so that we're pulling [00:13:30] from many trusted data sources to validate what AI is saying. If that makes sense.

Jeff Stewart:                     
It does. And is that what we're also seeing training on? Or if we're not, shouldn't we be seeing it as where we get those who are already experienced people, those that are experts in their field that can tell hallucination is a hallucination.

Celeste Mosby:               
Mm-hmm. Yes.

Jeff Stewart:                     
Shouldn't they are the ones that need some training on how do you get the best [00:14:00] out of AI? How do you catch what's going on? Be aware of catching what's going on. We know how to do this when we're working with, I mean, consulting. If I'm working with a new associate consultant, I expect a certain error level. And I know what errors to look out for, at least from experience, I do. I don't have the same sense of how to find an error within chatbots. And when I've tested them, [00:14:30] some of them, they get things wrong, but you can tell that they're not sure that they get things wrong, and others are complete and confident idiots.

Celeste Mosby:               
Yes. So yes, if you look at the jobs that are out there right now and people are really, really nervous that they're going to lose their job to AI. That's not what they should be nervous about. [00:15:00] What's going to happen is that some of the jobs that used to do some of the things that AI is doing now, it's our job across the industry, on the medical side of the industry to teach people now how to do the jobs of that next level. To your point, you're synthesizing the data that AI is giving you now, right? So we've been able to maybe kind of lower the amount of jobs we need there, but the amount [00:15:30] of jobs that are needed at that next level to synthesize the insights is amazing. So it's up to us to build career pathing and training for those that are enrolled so they see the advantage of where they could go. If you look at the large language models that are out there right now, KOLs, payers, HCPs, they're using them already.

They're using these models, [00:16:00] they are using personalized AI tools already. And like I mentioned before, a lot of HCPs, the first thing they're going to ask people that are coming in from pharma to see how they can add value is, "How can you help us understand and train us on how to use these better? Are there models that you guys have in pharma or platforms that can help us synthesize good data?" And what are we doing when it comes to our [00:16:30] patients? How do we train our patients and educate our patients on how to rely on good generative AI research and data where they haven't had to do that before? I think one, it's like this cascade of everyone in the industry. And I got to be honest, that's what I'm most excited about. I don't know. I've been in the industry a long time, and I will tell you that this is the most fun I've ever had around. Understanding how to use data as [00:17:00] a benefit to what we're trying to do around the whole care model in the industry. It's pretty exciting.

Jeff Stewart:                    
And is it changing your job?

Celeste Mosby:               
It is, drastically. Drastically. A lot of what we deliver from a training perspective was a lot around knowledge. I would say a lot, there's about 20, 30% knowledge when you think of the things we roll out. 70% is application and getting people really immersed [00:17:30] in experiential simulated environments so that they understand how to use it effectively. Before, they just kind of believe what we said and now, it's like, "No." I mean, technology is something where people have got to get their hands a little dirty with it, I use this word a lot, they have to feel empowered, and they have to feel accountable about... And what's the ROI for me to sign up [00:18:00] and do this? Right? And so we're changing a little bit around how we measure the impact of training, and especially the training we do with more digital and data-driven tools.

AI in the last, I would say, I've never seen a topic evolve as quickly as I have with AI. And I've been in this industry, I'm going to give a little now, [00:18:30] close to 30 years. And that's a lot to say, and I've seen a lot. So I don't think it's slowing up. I think to what you said though, Jeff, I think AI, kind of the sexy term, AI is going to go away a little and it's just going to become part of our DNA and our fabric of how we run our lives, whether it's our personal lives or our professional lives as well.

Jeff Stewart:                     
Well, Celeste Mosby, it's been a pleasure talking to you again. We've learned a lot. And thank you for joining [00:19:00] us on the Syneos Health podcast.

Celeste Mosby:               
It was my pleasure. Thank you, Jeff.

Jeff Stewart:                     
Revolution Management, Learning and Change in the New World of Work can be found in the Syneos Health 2024 Health Trends. A link is in our show notes.