HEALTHTECH: How has healthcare’s AI outlook evolved in the past few years? What capabilities do organizations expect now that weren’t available a year or two ago?
UDAYAKUMAR: Initially, AI was limited to very simple tasks, such as automating workflows, but with recent advancements in algorithms, AI has become more sophisticated. In healthcare, AI is valued for its potential to analyze diagnostic data and to allow us to make faster and more accurate decisions. Overall, the evolution of our outlook on AI has opened up possibilities for improving patient outcomes and efficiency.
HEALTHTECH: What are some key concerns that clinicians have about growing AI adoption in healthcare?
UDAYAKUMAR: Our clinicians are asking important ethical questions. Ensuring data privacy, maintaining transparency around the algorithms and addressing potential bias are all very valid concerns. There is some mistrust and concern related to control of medical decision-making. This is where collaborative AI is very important. Across industries, organizations achieve the greatest benefit when humans leverage technology correctly so that they complement each other. We need to understand how clinicians and AI can amplify each other in healthcare. Each brings different strengths. No clinician is ever going to be able to compete with the speed or accuracy of AI, while AI cannot replicate the creativity that a clinician might have. We need to identify the best roles for the clinician and the best tasks for AI. If we can do that, it should mitigate the fear of competition.
HEALTHTECH: How do you think the workforce shortage is influencing AI deployment? What other considerations are driving interest in AI?
UDAYAKUMAR: AI can help reduce workloads by automating routine tasks and providing clinical decision support so that clinicians can focus on the most cognitively demanding or high-risk tasks. AI can also be used to optimize resource allocation. For example, staffing schedules and supplies are two challenging topics nowadays; perhaps we can use AI to optimize those schedules or identify locations that will have high resource or supply needs so that we can respond more proactively. AI can also address the shortage of healthcare professionals in specific specialties and geographical areas, which is where telemedicine and remote patient monitoring powered by AI come in.
HEALTHTECH: What are some lessons from your organization’s approach to AI that you can share with other healthcare systems?
UDAYAKUMAR: There’s a lot of excitement within UNC Health around the possibilities that AI will bring to the healthcare industry. Early on, UNC Health developed a responsible AI framework, which is based on four components: fairness, which means we ensure that we’re training our models on the correct population and identifying potential bias; accountability, meaning we track performance and establish an evaluation process; transparency, meaning we’re very clear on the usage and the limitations of AI; and trustworthiness, which means we need to educate others about AI. It was very important to us to have that framework established early on.