AI and the Future of Community Oncology: Debra Patt, MD, PhD, MBA, MPH

Debra Patt, MD, PhD, MBA, MPH, discussed how artificial intelligence (AI) can help community oncology practices manage prior authorization and revenue cycle challenges in part 2 of an interview with The American Journal of Managed Care^® at the 2026 Community Oncology Alliance (COA) Payer Exchange & Innovation Summit.

Patt is the executive vice president at Texas Oncology, president of COA, and a member of the American Society of Clinical Oncology Board of Directors.

She noted that prior authorization creates persistent challenges for practices and patients alike, including delays to timely treatment, information gaps, and denials or down-coding. Automation is one of the most important ways AI can support the prior authorization process, Patt said, particularly through automated reporting and dashboards that make key performance indicators easier to track and act on.

She also pointed to several tools practices are using to streamline prior authorization workflows, from patient assistance programs to automated denial tracking and claims-editing software designed to ensure claims go out clean the first time. Refiling or managing a denial or a letter of medical necessity remains a highly manual process in many practices, Patt said, making automation and templating central to any effective software solution. As with broader AI adoption, she reiterated that oncology-specific tools capable of managing an entire channel or sphere of the revenue cycle tend to be more valuable than narrow, single-purpose solutions.

Beyond the technology itself, Patt stressed that practices need to better manage staff efficiency as they implement these tools, tracking how quickly team members resolve denials, manage test edits, and move issues through the process loop. She cautioned that highly manual processes are prone to variability in compliance that can undermine their effectiveness, making clearly structured operations and consistent key performance indicator tracking essential to any AI-supported system.

To conclude, Patt framed AI and innovation as central to the future of community oncology, highlighting COA’s ongoing efforts to help practices navigate these challenges.

“Being able to have open discourse and discussions with people about what's working for them, what's not working for them, and how we can solve our problems differently has been really critical, and I think [it] will be critical to the success of community oncology moving forward,” she said. “We're in it together, and if you too struggle with this, come join us.”