Original Article: Editorial Spotlight: Implications of Using Artificial Intelligence as a Tool for Summarizing New Evidence

“Editorial Spotlight: Implications of Using Artificial Intelligence as a Tool for Summarizing New Evidence.”

September 2026

JABFM

Caroline Tietbohl, PhD, MA, Assistant Professor of Family Medicine at CU Anschutz, is first-author of a recent article titled “Editorial Spotlight: Implications of Using Artificial Intelligence as a Tool for Summarizing New Evidence,” published in the Journal of the American Board of Family Medicine (JABFM).

When asked about the impact this study will have on patient care, Dr. Tieibohl said, “This research suggests that while AI can help us summarize evidence, human expertise remains essential for interpreting what that evidence means for patients. The real value of medical evidence is not simply knowing what a study found, but understanding how those findings should inform patient care, and that's where human judgment continues to matter.”

From the article:

“Family physicians must be timely consumers and translators of medical science. They make dozens of medical decisions per day, and medical science is rapidly changing. This includes a recent shift that we have observed in our own experiences: a shift away from interacting with primary research studies and a reliance on expert-written tertiary content like UpToDate, Dynamed, or Essential Evidence. A second shift has already begun: away from these sources toward AI-generated products (among them, medically-targeted products like DoxGPT and Open Evidence, in addition to broad LLMs like Gemini, chatGPT, or Claude). Little research has investigated the reasons for this shift. One reason may be that physicians prefer the writing that LLMs produce, which could potentially lead readers to conflate writing style with information quality. For example, one study found that healthcare professionals viewed AI-generated responses to patient questions as higher quality and more empathetic. Does this preference translate to the context of evidence-based summaries as well? Guthmann et al found that study evaluators who scored the POEMs and LLM summaries identified fewer errors in the LLM summaries and preferred the LLM versions overall.”

Read more of this article.