Jan Herzhoff Of Elsevier Health: How AI Is Disrupting Our Industry, and What We Can Do About It

Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path?

I love the intersection between healthcare, information systems and business. I come from a family of healthcare professionals and entrepreneurs. We always talked at the dinner table about healthcare systems and business challenges. My interest in technology started during high school where I founded a health start-up with a school friend of mine. At university, I learned about genetic algorithms, neural networks and many of the underpinning techniques of today’s AI. When I got the opportunity to join RELX and Elsevier in 2012, all of these aspects came together and shaped my career path over the past 12 years.

What do you think makes your company stand out? Can you share a story?

At Elsevier, we know the importance of innovation and efficiency within healthcare. With the recent AI boom across industries, many companies and organizations are trying to keep up with the pace and determine how to best implement AI into their products and workstreams. We’re already there. We’ve been using AI and machine learning technologies in our products and services for more than 20 years and we’ve stood as a trusted partner to healthcare professionals and an innovative leader in medical education and research for more than 150 years. We’ve developed this position by combining industry-specific human expertise, evidence-based and peer-reviewed content, high-quality data, and innovative technologies that provide clinicians and researchers with the tools and products they need. We are well-equipped to continue embracing AI responsibly and proactively to create opportunities and innovative solutions that make their jobs easier, and ultimately help improve patient outcomes.

Our long-term commitment to increasing diversity in healthcare and medical education is another area that makes us distinct from other companies. In the last two years alone, we have introduced groundbreaking advancements in medical teaching and practice, including the world’s very first 3D female model for medical students and staff. For centuries, medical students have had to learn from male models, leading to misdiagnoses in females. One year later, we came out with the world’s first and most sophisticated 3D human anatomy model featuring different skin tones and facial features to tackle racial bias in healthcare. Studies show that less than 5% of medical texts globally feature dark skin tones, leading to misdiagnoses, especially in diseases like skin cancer and Lyme disease. Both releases were by our Complete Anatomy program. And very recently we announced Complete HeartX, the world’s first heart education experience in spatial computing, which focuses first on female heart patients, who are often mis- or under-diagnosed due to more vague and transient symptoms compared to males. It is a leading spatial computing app on the Apple Vision Pro. We are very proud of these releases and have more to come in the future.

You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?

I look at the world in three defined ways: Distinctions, time and serendipity. Let me explain.

• Distinctions. One approach that forged my way of thinking has been Niklas Luhmann’s Theory of Distinction. It is a very powerful way to look at the world. It helps me guide my questions and focus and challenges my own and my team’s assumptions. It also helps me constantly switch between big picture and details where they matter. One early example in my Elsevier journey was the distinction between print and electronic. The challenge with this distinction was that you would overlook a key point in relation to books. Books content transcends this simple distinction, they are extremely valuable — powering databases and tools and even the most sophisticated AI solutions.
• Time. Part of what I enjoy most about my role is exploring new ideas in innovation and ways we can address pain points for current and future healthcare professionals. As a team, we often apply the concept of temporal pincer movement that you might know from the movie “Tenet”. It is about tackling a problem from both present and future. Elsevier is uniquely positioned here since we serve both current and future healthcare professionals. We bring the latest insights from practice into medical and nursing education and vice versa.
• Finally, serendipity mindset. I am constantly with the team looking out for the unexpected. This is most important when we work with our customers. There might be a new way they use our products that could uncover a specific need or something that we do that could help them to address a new challenge. I also apply this in internal talent conversations. For example, one of our team members reached out to me for opportunities. I knew that the person had a strong analytical background but in the conversation we found out that he had a background in e-commerce where we had an urgent need. He is now leading our global e-commerce business.

Let’s now move to the main point of our discussion about AI. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?

AI is disrupting nearly every aspect of the healthcare industry — from administrative workflows like filing and billing to diagnostic support, to medical education; we’re living in a transformative time.

Generative Artificial Intelligence (GAI) in particular, has the potential to revolutionize clinicians’ day-to-day workflow, with the ultimate goal of providing patients with the best care possible. GAI can retrieve and summarize documents across vast libraries of content in a way that makes large quantities of information quickly accessible to the end user. Conversational interfaces and large language models mean trusted information can be provided in record time to support diagnostic research and enable tailored treatment plans. With 24% of clinicians in the US considering leaving in the next two to three years, according to our Clinician of the Future 2023 report, we must do everything we can to reduce burnout and retain our current workforce. AI and other technologies, like spatial computing, are poised to catalyze vast industry improvements and increase the speed of access to trusted, evidence-based information when treating patients.

For students and educators, AI offers more personalized instruction, which has been shown to increase learning and retention dramatically. AI-powered conversational interfaces simulate the experience of working directly with a patient, providing students a tangible opportunity to practice in a more immersive real-life scenario with more representative and accurate tools.

Elsevier Health’s Clinician of the Future 2023: Education Edition found that 55% of US students are excited by the prospect of using generative AI tools like ChatGPT/Bard in their education. It also showed that 58% are considering jobs outside of direct patient treatment at a time when we need nurses and doctors more than ever. With the advancements of AI improving the doctor, patient, and student experience, we could see that number come down.

Bottom line — AI has the power to revolutionize this field and it’s just getting started. However, we need to address this change responsibly.

Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?

I have been a proponent of digital transformation in the healthcare industry for years. While I’ve seen some impressive AI-powered tools released in the healthcare industry, there hasn’t been one that I could identify as having the most significant impact on clinicians, until now.

This year, Elsevier launched ClinicalKey AI, the first and most advanced clinical decision support tool to be introduced in the US that combines the latest and most trusted medical content from the largest library of scientific content in the world, with generative AI to help clinicians at the point of care. ClinicalKey AI is optimized for natural language queries, so clinicians can use conversational search to access the most up-to-date evidence-based clinical content, including scientific journals, books, medical and clinical reference content. Doctors can now access precise and trusted information on any number of topics in seconds rather than hours or days even.

More than 30,000 physicians across the US have tested the underlying technology and the feedback has been overwhelmingly positive. As we’ve seen since the pandemic, there has been an increase in patient visits and fewer nurses and doctors to treat them. ClinicalKey AI is a valuable tool that can reduce time clinicians spend searching for information giving them more time back to treat patients. It’s a much-needed game-changer for the medical field.

For me, the moment was when I first saw generative AI’s potential as part of a retrieval-augmented-generative architecture (RAG) to address search in a way I had not seen before. We have the opportunity to reduce the time for a new clinical discovery to reach the point of care from 15+ years to 24h. This is what truly excites me!

How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?

To prepare our workforce for AI integration, we must invest in continuous learning programs to upskill our current and future workforce — ensuring they understand basic AI algorithms, how to interpret results, and the ethical considerations. That’s why we abide by a responsible AI code. As AI matures, we must constantly revisit what is considered responsible AI. Then, we must encourage collaboration with external AI experts to keep our finger on the pulse of the latest AI capabilities and inform guidelines for our industry. For example, for ClinicalKey AI, we partnered with OpenEvidence a leading start-up focused on AI for the medical field. Our combined expertise creates the ability to have a larger, faster impact on our customers.

As we enter an AI-enhanced future, clinicians must be engaged with critical thinking and adaptability. While AI is a useful tool to streamline and create efficiencies — clinicians and experts will remain at the center of decision-making, interpretation of data, and validation of results. Critical thinking skills are necessary to analyze AI-generated outputs, double-check accuracy, and discern relevance and potential bias. AI is a tool to complement and improve human work, not to replace it.

What are the biggest challenges in upskilling your workforce for an AI-centric future?

The Elsevier workforce has been using AI and machine learning technologies in our products and services for more than 20 years. With this time and experience comes a natural ability to be nimble and adapt to the changing landscape. I’m confident that our teams are ready to embrace an AI-centric future.

However, as we introduce new AI tools to the healthcare industry, one of the biggest challenges is addressing the doubts and concerns around AI and building trust. Misinformation and bias in AI tools are a significant concern. There’s valid hesitation in engaging with tools that may pull and promote inaccurate, harmful information, which is why it is so important that AI is learning from evidence-based sources.

This is where Elsevier comes in. Elsevier has a deep heritage in trusted medical information and our strengths in technology and analytics can ensure clinicians, faculty, and students receive the highest quality research and information when using our products.

Though it will take time for the workforce to familiarize themselves with all AI has to offer, we know where to start. Medical students are the lifeline of our future — so educating them with the tools they have at their disposal is crucial to ensuring a smooth transition into the working world. The more experience they gain early on, the more trust they will feel as they continue to utilize the tools in their daily work.

What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?

AI-powered tools give users access to thousands of pieces of data instantly, and while these capabilities give us space to imagine products and services we could never have before, we must act responsibly to prevent negative outcomes. AI tools need rigorous guardrails to minimize hallucination and bias and ensure that they are beneficial for everyone involved. Models must be limited to extracting information from trusted content, instead of generating answers itself, and we must be transparent about the limitations of systems. This way, we can ensure that AI is used to enhance human activity, bring out improvements, and exponentially improve efficiencies.

We will always need to balance AI’s benefits with the risks and maintain human oversight, to ensure we are harnessing it in an ethical way that protects the information that powers it, as well as people’s personal information.

At Elsevier Health, we pride ourselves on our responsible use of these technologies, and all our work in the generative AI space adheres to our RELX Responsible AI principles. These include:

1. We consider the real-world impact of our solutions on people.
2. We take action to prevent the creation or reinforcement of unfair bias.
3. We can explain how our solutions work.
4. We create accountability through human oversight.
5. We respect privacy and champion robust data governance.