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Related Experiment Video

Updated: Jan 15, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Determinants of Physicians' Referrals for Suspected Cancer Given a Risk-Prediction Algorithm: Linking Signal

Olga Kostopoulou1, Bence Pálfi2, Kavleen Arora1

  • 1Imperial College London, UK.

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|October 16, 2025
PubMed
Summary
This summary is machine-generated.

Physician referral decisions for suspected cancer are influenced by patient benefits and the seriousness of missing a diagnosis. A risk prediction algorithm reduced referrals but did not override these core physician values.

Keywords:
algorithmsdecision makinggistprimary carerisk assessmentrisk prediction

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Area of Science:

  • Medical Decision Making
  • Health Psychology
  • Clinical Risk Assessment

Background:

  • Physician referral decisions for suspected cancer are considered stable traits.
  • Psychological determinants of these decisions, especially with risk-prediction algorithms, require investigation.

Purpose of the Study:

  • To identify the psychological factors influencing general practitioners' (GPs) decisions to refer patients for suspected colorectal cancer.
  • To assess the impact of a risk-prediction algorithm on these decisions and underlying physician values.

Main Methods:

  • 200 UK GPs evaluated online vignettes of patients with possible colorectal cancer.
  • GPs indicated referral likelihood and perceived cancer risk before and after receiving an algorithmic risk estimate.
  • Post-vignette, GPs answered questions on values regarding referral harms/benefits, error severity, and uncertainty.

Main Results:

  • The algorithm significantly decreased referral likelihood and perceived risk.
  • Physician values, particularly patient benefits and perceived severity of missing cancer, were the strongest predictors of referral.
  • The algorithm did not significantly diminish the influence of these core values on referral decisions.

Conclusions:

  • Physician referral decisions are shaped by perceived benefits/harms of referral and the moral weight of missing a cancer diagnosis versus over-referring.
  • These values establish an internal threshold for action, persisting even when algorithmic risk assessments are provided.
  • Understanding these physician values is crucial for optimizing cancer referral pathways and integrating decision-support tools effectively.