Drowning in Data: How Oncologists Are Coping with Information Overload in the AI Era

In this episode of Treating Together, host Dr Pallav Mehta sits down with Dr Kurt Demel and Dr Yan Ji, 2 community-based medical oncologists practicing in the Twin Cities, to tackle a problem every oncologist feels but few have named clearly: information overload.

The conversation opens with a deceptively simple question: When does learning become overload? The group traces the line from the genuine joy of working in a constantly evolving field to the point where the sheer volume of trial data, survival end points, and subgroup analyses makes it hard to land on a clear recommendation for the patient in the room. Dr Ji offers a memorable framing for this: the "memory battery" that drains over the course of a clinic day, leaving even thorough research feeling unresolved when conflicting trials point in different directions.

From there, the discussion moves into how oncologists actually cope by leaning on colleagues through email threads and group chats, the growing divide between generalist and subspecialist practice, and how increasingly informed patients (armed with their own ChatGPT printouts) are reshaping the visit itself. The back half of the episode digs into AI's expanding role in oncology: ambient note-taking, evidence-summarization tools like OpenEvidence, and AI-assisted clinical trial matching, alongside real concerns about hallucinated summaries, erosion of foundational clinical reasoning in trainees, and the risk of applying trial data to patients who don't resemble the trial population. The episode closes on a note of cautious optimism—AI as a tool to clear away noise, not a replacement for the clinical judgment and human connection that the panel agrees remains the real value an oncologist brings to a patient.