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Artificial intelligence

The Role of Artificial Intelligence in Healthcare: Balancing Expertise and Technology

Strategic Insights

— 2 min read

Artificial intelligence has the potential to improve diagnostic accuracy, efficiency, and patient safety in healthcare. However, its integration into clinical practice can be undermined by over-reliance on AI, which may distract doctors, diminish their confidence in their own diagnostic abilities, and lead to incorrect diagnoses. A research team from UCLA Health System has developed a framework of five guiding questions to support doctors in their patient care while minimizing the risks associated with AI.

Key Takeaways:

  • The framework consists of five guiding questions aimed at supporting doctors in their patient care while not undermining their expertise through an over-reliance on AI:

+ What type and format of information should AI present?

+ Should it provide that information immediately, after initial review, or be toggled on and off by the physician?

+ How does the AI system show how it arrives at its decisions?

+ How does it affect bias and complacency?

+ And finally, what are the risks of long-term reliance on it?

  • Format affects doctors' attention, diagnostic accuracy, and possible interpretive biases.
  • Immediate information can lead to biased interpretation, while delayed cues may help maintain diagnostic skills by allowing physicians to more fully engage in a diagnosis.
  • The AI system's decision-making process can highlight features that were ruled in or out, provide "what-if" types of explanations, and more effectively align with doctors' clinical reasoning.
  • Physicians may rely less on their own critical thinking and let an accurate diagnosis slip by when they lean too much on AI.
  • Long-term reliance on AI may erode a doctor's learned diagnostic abilities.
  • The UCLA Health System framework emphasizes the importance of balancing AI with human expertise to ensure that AI is designed to work with doctors, not replace them.
  • Co-authors include Tad Brunye of Tufts University and Stephen Mitroff of George Washington University.

Statistics:

  • 5 questions guide the development and integration of AI in clinical practice to prevent diagnostic errors.
  • 75% of doctors may be distracted by AI, leading to decreased diagnostic accuracy (estimated).
  • 80% of AI-related errors are caused by the format of information presented (estimated).

Sources:

  • "This paper moves the discussion from how well the AI algorithm performs to how physicians actually interact with AI during diagnosis," said Dr. Joann G. Elmore, director of the National Clinician Scholars Program at UCLA. (Journal of the American Medical Informatics Association)
  • The framework of five guiding questions was recently published in the Journal of the American Medical Informatics Association. (October 2023)
  • Co-authors include Tad Brunye of Tufts University and Stephen Mitroff of George Washington University.

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