“Notes from the Field” is a special newsroom feature highlighting industry professionals working to transform healthcare. In this edition, we spoke with Ben Cleveland, MSHS, Principal Data Scientist at UnityPoint Health.
1. Tell us about your role.
Reflecting on the early days of the nationwide adoption of Electronic Medical Records (EMRs), I recall the immense interest in data utilization and the integration of machine learning applications.
As the sole data scientist at the time, I designed our initial portfolio of predictive models and oversaw their deployment to various clinical, operational, and financial departments over the years. During this time, I've witnessed our team's evolution as we grew from just myself to three additional data scientists. Together, we manage a diverse range of data science products and provide statistical consultation across different use cases, such as clinical services and finance.
Our work extends to 12 major hospitals and multiple community healthcare facilities across Iowa and Illinois, serving a network of 2.7 million patients within our integrated system. As a team of four, we prioritize efficiency by focusing on tasks that yield substantial value. We remain vigilant in managing technical debt, ensuring our solutions are always at the forefront of innovation. Our dedication to efficiency and innovation is driven by the understanding of the significant impact our work has on our organization.
2. What inspired you to pursue a career in healthcare?
I spent my childhood in Iowa, where my father worked as a doctor in our small town. Growing up, I often assisted in the office by managing paper charts. The transition from that manual system to today's electronic medical record (EMR) systems is like night and day.
My father, who had a keen sense of foresight, emphasized the importance of combining skills in statistics and informatics for the future. He believed mastering this intersection between technology and statistics would pave the way for analytics and data science expertise and a career. As I progressed through school, I was naturally drawn to healthcare due to its profound impact and challenging nature. The work felt meaningful to me.
3. What is one thing you’ve learned in the past year?
I lead our organization's first AI strategy. My role involves managing risks, educating others on the benefits, and identifying high-value opportunities. Over the past year, I’ve kept pace with the rapid emergence of technology, including exploring ChatGPT and advanced language models that push boundaries. This journey has forced us to rethink the possibilities of how this technology could improve our work while balancing unknown risks. Throughout this period, I have delved deep into multiple dimensions of AI, understanding the multi-faceted risks and ethical concerns while discovering ways to mitigate them and where we can integrate AI in healthcare to maximize its benefits.
4. What do you see as the biggest opportunity to improve healthcare?
The widespread impact of chronic illnesses in America strains both individuals and our healthcare systems. We as a nation must prioritize preventative health and explore the integration of technology in preventing and managing these conditions. Technology plays a pivotal role in enhancing health education, supporting healthcare teams, and fostering patient involvement in early prevention. We also must view healthcare providers as collaborative partners in promoting health and empowering patients to address their chronic health concerns.
5. What is the greatest challenge facing healthcare?
I believe the US healthcare financing system is a root cause for many of our country’s health problems because it limits the positive effects of free market economics on price and access. Costs continue to soar despite technological advancements, and outcomes aren’t improving. Nobody owns the lifetime risk of any one person, so revenue is being micro-optimized in each sector as opposed to solving for the system.
6. How do you envision technology playing a role in addressing this challenge in healthcare?
Using data to make decisions at scale was challenging in the healthcare space until the advent of EMRs. While digitizing healthcare delivery has helped in this regard within single health entities, we now have data silos across the health continuum that cross organizations. Technology and policy can help integrate and share these data more holistically so that better decision-making can be made for each patient, no matter where they get their care.
7. How are you leveraging new technologies, such as augmented intelligence, to enhance productivity/efficiency, quality, and outcomes?
We are targeting augmented intelligence to help alleviate the administrative burdens within healthcare services, leading to enhanced efficiency and cost-effectiveness while also tackling the issue of provider burnout. We also believe augmented intelligence has a prominent role in enhancing decision-making by minimizing the variance of data interpretation across multiple stakeholders. Instead of spending valuable time deciding what the data mean, we can focus on what actions we need to take to make the most impact.
