Cheryl Martin (Host): Welcome to the Health Care Executive Podcast, providing you with insightful commentary and developments in the world of healthcare leadership. To learn more, visit ache.Org. I'm your host today, Cheryl Martin. And in this podcast episode, our topic, Healthcare Quality and AI. Our guest is Rich Greenhill, Program Director and Assistant Professor at Texas Tech University Health Sciences Center. He's an internationally recognized healthcare quality leader. Rich Greenhill will be co-presenting the Leading for Quality as a Business Strategy Boot Camp and moderating the panel, Leadership Insights ChatGPT and Generative AI Implementation and Lessons Learned at the 2024 Congress on Healthcare Leadership, March 25 through 28 in Chicago. Rich, you were on this podcast in 2022. Welcome back.

Richard Greenhill: Thank you so much, Cheryl, and a very happy 2024 to you and to our listeners. And it's good to be here.

Host: Now, you have an interesting background in both healthcare quality and the data science and artificial intelligence space. Tell us about the early years in your healthcare career journey and how you became involved in these areas.

Richard Greenhill: First, again, it's a pleasure to speak with you and to be here. You know, my career began in the Navy more than 30 years ago. And I would say that I likely stumbled into Quali, because it was just what I did every day in the medical laboratory to really ensure that the results we put out were the most accurate for our patients. And then, fast forward to my involvement in Six Sigma, lean, TeamSTEPPS, and all those other dimensions of quality, it became just a natural fit for me to roll right into quality and performance improvement. Now, data science was a natural progression of sort of the strategy and analytics aspects of my former quality roles.

So when you think about the key methods in data science under the umbrella of artificial intelligence, such as deep learning, large language models and machine learning, the principal component of all these is data and data governance. So, data is also the focal point in healthcare quality. Obviously, you can't improve what you don't measure. So, it's also the foundation for any artificial intelligence methods. So, no data, no quality; no data, no AI. So, the synergies were really strong between these two areas, while on the surface they seem divergent. So, that's sort of a high-level view of my career and how I got started and really involved in these areas.

Host: So, congratulations are in order on your recent appointment to a new role as Director of the Industry Advancement Technology Accelerator. What will you do in this role and what is the accelerator all about?

Richard Greenhill: Well, thank you. It's really an honor to be part of a very smart group of folks at the Texas Tech University Innovation Hub at Research Park. So, the hub is an ecosystem of innovation that's focused on cultivating and nurturing entrepreneurs who are interested in creating value towards a social or commercial type idea. And the key for this is really value creation that results in some type of impact. So, the role that I have taken on to lead the Industry Advancement Technology Accelerator will align to the same mission of really entrepreneurial nurturing, but with the explicit focus on launching startups or cultivating licensing opportunities for advanced technologies in the spaces of machine learning or AI, as well as advanced manufacturing. And we'll do this for and in the West Texas region.

A key accountability for me will be to lead a team in selecting, funding, and mentoring cohorts through the program and making sure that they leave with a minimum viable product that they can then go out and seek venture capital for, patents, or launch a business with. So, it's very exciting because we are also interested very much in healthcare as well as industry. So, what a wonderful opportunity it is.

Host: Yes, it is. Now, your organization, Texas Tech University Health Sciences Center, established the Institute of Telehealth and Digital Innovation in September 2023. Tell us about the purpose and goals of the Institute.

Richard Greenhill: Sure. You know, our university cares for patients in approximately 108 counties in West Texas. Many of our patients face unique challenges related to being in primarily rural areas. So, the Institute has three main goals towards serving patients, and they include being a digital front door, which includes remote patient monitoring and virtual visits, focusing on appropriate uses of artificial intelligence in terms of large language model development.

And then, the final goal is exploration of an AI Model Validation Laboratory. And these goals support care delivery with an emphasis on three pillars: access to care through focusing on collaboration, to expand specialty care and chronic disease management, research to really analyze and examine clinical efficiency, as well as care outcomes, and then finally academics to ensure that the next generation of our healthcare workforce is trained in specifics and aspects of digital health.

Host: Now, Rich, as I mentioned, you'll be co-presenting the Leading for Quality as a Business Strategy Bootcamp at Congress. Can you give us just a short preview of the session? What can attendees expect?

Richard Greenhill: This is an exciting and the first offering of its kind as a partnership between the National Association for Healthcare Quality, NAHQ, and ACHE. And so, I'll be co-presenting with two colleagues, April Taylor from the John Hopkins Hospital and Robin Betts from Kaiser Foundation Health Plans and Hospitals. And we're going to cover various topics of how healthcare leaders can leverage quality as a business strategy. Some of the areas we're going to talk about and have activities around include leadership, population health, emergent technologies, as well as board engagement. So, attendees can expect our team to share our expertise, best practices, as well as have them work through activities such as case studies and so forth to help with practical thought and application around these topics. This is a pre-Congress session on Sunday. And so, it's going to be a full day of activities and learning before the Congress really kicks off.

Host: Now, artificial intelligence can change the way healthcare organizations deliver care, and I know that this is an area you have a lot of interest and experience in. Healthcare Executive Magazine talked to you about this for the cover story of its March-April issue. So, how can providers balance the benefits of AI while ensuring quality care?

Richard Greenhill: The answer to this evolving really on a weekly basis as businesses, entrepreneurs, and researchers find novel ways to help with some of the issues in our care processes, whether it be the workforce or discovering new treatments. So, my answer to that is really twofold. First, in order to really balance the benefits of AI while ensuring quality, our organizations need to ensure that within our strategic frameworks, there is an enterprise emphasis on AI and where it fits in the delivery of care.

I recall a survey that was done by Bain & Company from last fall 2023, where health system leaders were asked about their thoughts on the usefulness of generative AI. And three-quarters of the respondents believe that AI was useful in care delivery, but only 6% had an in place strategy for the technology. So when we think about benefits of this tech and quality, we have to ensure that we're clear about what we want to use it for. And we also have to ensure that implementation doesn't exacerbate existing issues related to poor access or equity in research utilization. It's important to remember that AI methods and algorithms are tools that are created by people. So, we have to be very careful to ensure we don't plug and play this technology into current processes that themselves are in need of updating. In other words, still need to think innovatively, even as we are implementing innovative tools and technology.

And next, we need to be technologically nimble, as well as prepare our workforce to be tech savvy, while embracing a mental model of continuous innovation, because the technology is going to continue to evolve and become more robust. I feel like our industry is being pushed by the business community to innovate, which in and of itself is not a bad thing. But I heard Mark Cuban say at the 2024 CES Digital Conference recently, related to AI, and I quote, "There are two types of people in the world today." He said, "Those who are great at AI and everybody else. And either you know how to use it to your advantage or you're in trouble." End quote. Right now, his statement is true for probably 90% of the business world outside of healthcare delivery. I think that his statement will be true for us in healthcare delivery in the next two to five years. So to achieve quality and balance in AI in an environment where the regulatory apparatus has not caught up with the tech, we need to really focus on issues of ethics, equity, efficiency, and patient safety through ensuring that we have robust data governance strategies.

Host: That is some great information. Why do you think the strategy, the percentage there was so low? Do you think because AI is so new?

Richard Greenhill: Well, AI itself has been around a long time. I wrote a paper about this in 2021. Did some research, where I looked at the competencies for healthcare leaders and enterprise adoption of emerging technologies, and the competencies are just not there. And so, that's part of it. But the other part is that the technology advancing so quickly. And in healthcare, we are a regulatory sort of constrained industry where we have to go through processes before we can implement large scale technology that will impact patient care. So, we have to go through a process where the business world can just do what they do. Also, our data was not in great shape. So, we have these sort of three things that are limiting us as far what we can do, and how quickly we can form a strategy, I think. But it doesn't mean that we don't need to think about it.

Host: Now, you've touched on this a little bit, but what are some other challenges that AI can cause in an organization dedicated to quality, and how can healthcare leaders overcome them?

Richard Greenhill: The biggest issue I think we face in healthcare around the uses of artificial intelligence is related to biases associated with several areas. The National Institutes for Standards and Technology outlines in a working document three key types of bias that can impact organizations that are implementing AI, and they include systemic bias that's related to how the organization uses data and functions. There's human bias related to how we present data, how we interpret results from these models to fit our business needs, and then computational bias, which points to the condition of our data and how we select the AI models, as well as how the population is represented or the lack thereof.

So, these biases, if they're not adequately addressed, can have a negative effect on patients in terms of equity and outcomes. So, how do we overcome these biases? I think focusing on ethical data governance and ensuring that we have a broad group of stakeholders at the strategy table from frontline caregivers to developers, ethicists, as well as the general public, that's really what's going to help us craft an AI-centric organization that includes the right representation, the appropriate representation, and allow us to collect the appropriate data to treat our patients. Demographic representation and inclusion is absolutely necessary as it relates to ensuring that we have robust AI-centric strategies.

Host: So, Rich, let's look into the future. As technologies like AI become more dispersed in care delivery, what will quality in healthcare look like a decade from now?

Richard Greenhill: If I had a crystal ball, I would say that I think we will gain robust efficiencies in our administrative processes, as well as diagnostic precision treatments are going to sort of explode and be wonderful. And then, we'll also have a lot of gains in certain venues of chronic disease management. You know, as an industry, we really have no choice, but to change and improve because, you know, AI is here and it's not going anywhere.

I believe the journey from here in early 2024 to a future state where AI-enabled processes dominate is around the corner. And it has great potential to make care safer while reducing burnout of our caregivers. So, I think the future is bright, but there's a lot of work and new thinking that's required between now and a future where AI is actively and robustly part of our daily workflows. So, it's going to help us improve quality, but we have to get these things around bias and around operational uses correct.

Host: Rich, thanks so much for coming on and sharing your expertise with us.

Richard Greenhill: It's a pleasure to be here and always love speaking to colleagues in our industry and doing what I can to push innovation and change.

Host: Once again, Rich Greenhill will be co-presenting the Leading for Quality as a Business Strategy Bootcamp and moderating the panel, Leadership Insights, ChatGPT and Generative AI, Implementation and Lessons Learned at the 2024 Congress on Healthcare Leadership, March 25 through 28 in Chicago. To learn more and to register, visit ache.org/congress.

Cheryl Martin (Host): If you found this podcast helpful, please share it on your social channels and subscribe to the Healthcare Executive Podcast from American College of Healthcare Executives. Thanks for listening.