AI as a Thought Partner: Reframing Innovation in Medicine and Practice Management
At the Clinical Pathways Congress and Cancer Care Business Exchange (CPC+CBEx), the session titled “Beyond the Hype Part 2: Real-World Impact of AI-Powered Operational Support” centered on the evolving role of artificial intelligence (AI) in medical practice, exploring both its opportunities and challenges from two distinct leadership perspectives.
Panelist Barry Russo, MBA, CEO of the Center for Cancer and Blood Disorders, framed AI as a necessary response to workforce shortages and rising complexity in health care operations. He emphasized that staff often fear AI as a job threat, particularly in areas such as coding or pre-authorization, but urged reframing it as a “thought partner” rather than a replacement. He noted that practices cannot hire enough staff to meet growing demands, and AI provides critical support in managing coding intricacies, payer updates, and administrative burdens. By positioning AI as an augmentation tool, leadership can reassure staff while improving efficiency and patient care. He also shared a personal case in which AI-assisted radiology identified a cancerous nodule overlooked by a human radiologist, underscoring AI’s potential to directly improve outcomes.
The second presenter, San Banerjee, MBA, chief technology officer at Navista, contextualized AI within broader industry challenges—escalating drug costs, reimbursement pressures, and increasingly complex clinical care. He outlined four types of AI in health care: descriptive (dashboards and retrospective analyses), predictive (forecasting outcomes), prescriptive (optimizing treatment decisions), and generative (streamlining communication and documentation). He argued that AI is vital for both clinical and business functions, from precision medicine and clinical trial matching to billing and denial management. Importantly, he stressed the need for thoughtful integration, as fragmentation across tools and vendors can undermine value if systems do not work seamlessly with electronic health records (EHRs).
Both speakers highlighted practical use cases of AI in their organizations. These included AI-assisted overreads in radiology, documentation support tools such as DeepScribe and Notex AI, medical record management platforms such as Doc Fluid, and pre-authorization assistance integrated with eligibility systems such as Experian. They acknowledged adoption hurdles, noting that physicians and staff want tools tailored to their workflows, and that full trust in AI systems requires time and evidence. Piloting tools with small groups of clinicians was described as an effective strategy to manage resistance and refine implementation before broader rollout.
The discussion extended to future applications, including AI in drug discovery, radiation planning, and value-based care models. Both presenters agreed that AI can help practices navigate reimbursement complexity, stratify patient risk, and track outcomes more effectively, thereby supporting sustainable care models. Still, they cautioned that successful adoption depends on integration, change management, transparency, and continuous education. Building staff trust, engaging stakeholders early, and maintaining open feedback loops were described as essential for long-term success.
Ultimately, the presenters framed AI not as a replacement for the human touch but as a pathway to free clinicians for more meaningful patient interactions, while ensuring that practices remain viable amid increasing clinical and operational complexity.
Reference
Banerjee S, Russo B. Beyond the hype part 2: real-world impact of AI-powered operational support. Presented at the Clinical Pathways Congress; September 6, 2024; Boston, MA.
