AI in healthcare

1. For more than 150 years, Elsevier Health has helped the work of research and healthcare communities. How has the approach evolved in response to advances in medical knowledge and technology?

When you look to the past, it started with the printing press, when documents were printed, when books were printed, moving to journals, and then journal distribution. In the late 1980s, early 1990s, Elsevier created the platform called Science Direct, which was the first database for medical insights, medical knowledge, and other domains as well. From those databases, it moved more and more into clinical decision support, into workflows, and now most recently into artificial intelligence.

2. Did you always have a passion for the healthcare industry? Where did this desire to support clinicians and other medical professionals come from?

I was born in a very small town, a village, in rural Germany just north of Frankfurt. My family comes from a background of health professionals and entrepreneurs. At the dinner table, with the family or family friends that came over, a lot of discussions were always about healthcare systems and healthcare overall. My dad is a pharmacist in Germany. It was always a big, big topic. I started to evolve that over time during school and later on, but that was where it all started.

3. How does Elsevier distinguish itself from its competitors?

4. When did you first recognize the potential impact of how AI technology might impact your products and the healthcare sector as a whole? When was the aha moment for you?

We always thought about how we can improve the search for clinicians to find the right information in this huge ocean of information that we have. When we saw this technology coming out, the aha moment was it could help us help the clinician to find the needle in the haystack. That was one of the biggest challenges we were facing. It would always take, with the current solutions for simple questions, it would take you perhaps five, 10 minutes to find an answer as a physician. If it's about medium or hard questions, 30 percent of the questions you would never find an answer, or it would take you a very long time. Now when you see this type of technology, especially vector search powered large language models, they help you find this information much, much faster. And when you have that huge content base, then it becomes extremely powerful.

5. How is Elsevier Health communicating the role of AI as a tool to complement and enhance the human work of the doctor rather than replace it?

One very good way to visualize it is to see a physician more as a detective. You have a situation and need to look at all the evidence. You need to look at the vitals of the patient. The interactions, the questions that you probe and ask the patient are critical. Next is using databases, and where I can see AI as extremely effective is in that part to help retrieve that information. But at the end of the day, you as a physician, you need to bring all of these different pieces together and assess them and then link them up. That is very, very difficult. We believe that with AI, and responsible AI specifically, you can enhance the capability of the doctor and the nurse and the overall clinician in that space to make them much better and more effective.

6. One of the most advanced products launched this past February was ClinicalKey AI. How does it help doctors and patients at the point of care?

The problem we are trying to solve is to help the physician in a moment when they have a specific question in mind and need to figure out an answer to that question quickly. Or when they have a very complex medical case. That's exactly where ClinicalKey AI shines. We have created this platform where we combine our content with a cutting-edge vector search together with a partner startup called OpenEvidence. The clinician can ask the question in normal conversational tone. We ensure that the content that has initially been indexed is only curated content, so it's not coming from public internet sources, to ensure it's trusted.

All the answers are then based on that content from these journal articles or clinical overviews that have been created. And the vector search finds these content pieces, these specific paragraphs, and places them back. Now, these are all from trusted sources that physicians would use and would've learned from over decades based on textbooks or journals.

7. Can you describe the process involved in determining when and how to innovate?

We work and we co-create everything with our partners, with our customers to really understand where are the biggest pain points they have. In that case of ClinicalKey AI, the big pain point was around the search and how quickly you find information. We would look at the problems, how big they are, and ask what is the value attached to it. We would also look at it from a global scale perspective. Is it something that only can help in one specific country in a setting or is it something that we can scale up?

 A great example is a couple of products in the education space. We launched them in 2018, from zero, and they're now in 1,600 institutions globally. That’s one of our capabilities is to scale up something when we have found a problem, when we understood that the value is there, and then working together with our customers and then with our sales and marketing teams to really scale it and bring it to all the markets across the world.

8. Elsevier launched the Scopus AI product a month prior. What functionalities does this service provide and how does it leverage the database of over 27,000 journals and close to 2 billion citations to provide accurate and relevant information?

There are multiple use cases. One very interesting one is when you are a researcher at a very early stage, you want to understand a specific problem domain. It's still something that's new to you and you can use Scopus AI to get a very quick overview of the entire domain. It would show you the most important papers, and where to really then advance your research into. It's a very powerful tool for exactly that.

9. The world's first heart education experience in spatial computing, Complete HeartX, was launched in February. How does this technology differentiate itself from traditional education tools and create a novel learning and interaction experience?

This is actually a very, very exciting technology going far beyond traditional simulations. When Apple launched the new Apple Vision Pro, we were one of the very first apps that actually were there, and in fact by enterprise customers and the press, we were considered to be actually one of the most advanced simulation products on this new device. Now, what's incredible about it is you might remember the movie The Matrix. It actually supports you with that type of learning experience. It's about understanding a concept. You go into, basically you see, let's say for example, the heart. You see it in 3D through the glasses. You're able to engage, you are able to understand it.

When you have understood it, then we push you into a simulation, completely virtual simulation where you then have to deal with the patient who has a heart situation. So you learn, in an incredible way, you actually help students to engage with specific, sometimes very challenging concepts that many years ago they were only able to look into a 2D book to see the heart or later in a 3D version. Now they can engage with it. It’s a much richer learning experience that is possible with a device that can move really from an extended or mixed reality setting into a virtual spatial relation situation.

10. As you reflect on your four years in your current role, what are your aspirations for the next four years in the future of Elsevier Health?

For us, I think the big thing is now indeed ensuring that we can leverage and identify the right use cases for artificial intelligence to bring our insights in a very responsible way to our customers and give them an alternative to offerings that are out there to really help them on their journey. That's really the number one priority. It's also about how we can then bring in these technologies to different countries and scale them. I’m very excited about technologies like spatial computing and how we can bring very cutting-edge technology into the education space, again, in a very responsible way. These are some of the key challenges and things that also excite me a lot for the next few years.