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“We are so hell-bent on simplifying our work, reducing our EHR burden, we sometimes forget that this work is more than just pointing, clicking, and typing.” In this piece, CT Lin, MD, CMIO at UCHealth, examines the downside of inserting GPT assistants into the EHR and suggests a different strategy for leveraging digital tools.
A recent success story with an FQHC provides further evidence that AI-driven tools can aid in decision-making, reduce human error, and enhance patient care, according to Chani Cordero. However, it also “raises important questions about the ethical implications of AI use in healthcare.”
Large language models and GPT may not be the apocalyptic nightmare some critics fear, but they certainly require due diligence by thought leaders, health care professionals, and the general public, wrote John Halamka, MD, and Paul Serrato. “We need a framework to manage them responsively.”
The problem with digital health adoption? Developers (especially startups) want to move quickly, whereas physicians want to see evidence, which can be “time-consuming and expensive to obtain,” according to Joseph Kvedar, MD.
Cognitive errors challenge clinicians and technologists alike, according to John Halamka, MD, and Paul Cerrato of Mayo Clinic Platform. Being aware of the types of mistakes that can occur is the first step toward fixing them.
