Within the constantly evolving domain of healthcare delivery, innovation isn’t merely a buzzword, but a crucial element in the effort to enhance patient outcomes and operational efficiency. Recently, we had the privilege of talking with Jason Hill, MD, Innovation Officer and hospitalist at Ochsner Health, to discuss some of his AI philosophies and guiding principles as well as how it has impacted his experience in care delivery. Our conversation covered varying aspects of AI, including AI adoption, the focus on workflows and people, regulation, safety and ethics and patient care. This post dives into some of our favorite insights with Dr. Hill, highlighting the current and potential future state of AI in healthcare.
Learning Innovation Through Success (and Shortcomings)
Dr. Hill began addressing the multifaceted nature of healthcare innovation. “At a super high level, we think of innovation as introducing novel technologies and systems into our healthcare environment to enhance patient care and improve the efficiency of providers and support staff,” he explained. Innovation, he noted, operates much like a mini startup within the hospital itself, involving extensive use case testing, piloting and learning from failures.
Discussing the inevitability of failure in the innovation process, Dr. Hill shared a valuable perspective: “Failure is the path to learning and getting it right. For our team, failure is viewed through the lens of growth achieved.” He quoted Thomas Edison, saying “I didn’t learn one way to make a light bulb; I learned 99 ways not to make a light bulb.”
This mindset is crucial as it prepares the team to navigate unknown challenges when introducing new technologies into real patient care environments. Being ready to pivot or cut losses is essential to ultimately achieving success and significant improvements.
Defining Innovation
When asked to define innovation, Dr. Hill emphasized the role of AI in 2024. “Innovation in healthcare often equals AI. Most of the technologies we’re piloting or scaling have some AI component,” he stated. At Ochsner, they have established an AI center of Excellence in collaboration with their Chief Data and Analytics Offers, Shashi Vangala. This meta-department encompasses multiple disciplines, ensuring proper governance to address AI safety, equity and bias. By integrating AI at various stages, whether buying, building or partnering for technology, they are able to maintain a balanced and supervised approach to AI innovation.
Driving Behavior Change With AI
Dr. Hill highlighted the challenges intrinsic to such fundamental workflow shifts such as AI, noting that AI itself is not transformative–it’s the workflow integration that makes the difference. “You need the right people, the right processes and the right technology integration,” he said. Their AI Center of Excellence focuses on ensuring these three elements operate harmoniously. Moreover, they’re prudent in selecting the appropriate teams for piloting and scaling AI initiatives, recognizing that change-averse or fatigued departments are less likely to succeed.
Importance of a Multidisciplinary Approach for AI Governance
Dr. Hill underscored the unique risks associated with AI, particularly generative AI and neural networks, which necessitate specialized governance bodies with deep subject matter expertise. “AI is trained like an employee, not programmed like a computer. Ensuring ethical training from the start is critical,” he said. He provided an example about self-driving cars, where autopilot systems began running stop signs because they were trained on real driver behavior. This anecdote illustrates the unexpected challenges that can arise with AI and the importance of rigorous testing and governance to prevent patient safety concerns.
How AI Can Help With Patient Care
On the topic of AI’s impact on patient care, Dr. Hill shared his insights as a practicing hospitalist. He pointed out that while AI’s direct impact on patients may not always be evident, its role in behind-the-scenes processes like revenue cycle management and supply chain logistics significantly enhances patient care. “AI helps in capturing and coding patient documentation accurately, which leads to better standardized, evidence-based care.” Additionally, AI’s potential in areas like pathology, radiology and ambient conversations between doctors and patients can unlock valuable data, streamlining workflows and improving clinical encounters.
Conclusion
Our conversation with Dr. Hill provided a comprehensive look into the transformative potential of clinical AI. From learning through failures to defining and implementing innovative solutions and driving behavior change, the role of AI is pivotal and continually evolving. Governance and ethical considerations are paramount, ensuring that AI enhances rather than hinders patient care and clinical workflows. As healthcare continues to evolve, the insights shared by Dr. Hill serve as a guide for integrating AI effectively and responsibly.
To dive deeper into these insights and learn more from industry experts like Dr. Hill, we encourage you to watch the latest segments of “Lessons From the Inside.”
