What is it about?
When doctors evaluate patients using asynchronous telemedicine, they are highly vulnerable to "anchoring bias"—the tendency to rely too heavily on the first piece of information they see, even if it leads to the wrong diagnosis. This study looked at how a medical student's personal cognitive style, brainpower, and the sheer amount of information they receive affect this bias. We tested a specific "composite debiasing strategy" (a multi-step mental checklist) to see if we could break this habit. The results showed that having too much broad information actually makes people more prone to bias, but our debiasing strategy successfully reduced errors—especially for fast, intuitive thinkers who have high cognitive ability.
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Why is it important?
Telemedicine is revolutionizing healthcare, but it changes how doctors think. In a fast-paced virtual environment, cognitive biases can easily creep in and harm patient safety. This paper provides a concrete, validated roadmap for reducing anchoring bias in telemedicine. It proves that simply dumping more information on a clinician doesn't help—it actually worsens bias. Instead, healthcare organizations and health-tech developers need to implement structured debiasing tools. Our findings help medical schools and digital health platforms tailor their training and user interfaces to match the specific cognitive styles of doctors, ultimately leading to more accurate virtual diagnoses and safer patient care.
Perspectives
Diagnostic errors are incredibly costly—both financially and in human lives. We wanted to move beyond just pointing out the flaws in virtual care and actually test a practical, psychological shield that clinicians can use to protect themselves from mental traps. This research is a step toward making digital healthcare just as safe and reliable as an in-person hospital visit.
Prof Snehasish Banerjee
University of York
Read the Original
This page is a summary of: Debiasing anchoring bias in the context of telemedicine, Behaviour and Information Technology, January 2025, Taylor & Francis,
DOI: 10.1080/0144929x.2024.2444548.
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