Using cancer risk algorithms to improve risk estimates and referral decisions
Olga Kostopoulou1, Kavleen Arora1, Bence Pálfi1
1Imperial College London, Department of Surgery & Cancer, London, UK.
Communications Medicine
|May 23, 2022
Summary
General Practitioners (GPs) changed referral decisions when using an unnamed cancer risk algorithm, improving consistency with guidelines. The algorithm also enhanced GPs' risk estimation accuracy over time.
Area of Science:
- Medical Informatics
- Clinical Decision Support
- Health Services Research
Background:
- Cancer risk algorithms are underutilized in clinical practice despite their introduction.
- General Practitioners (GPs) face challenges in accurately assessing cancer risk and making timely referral decisions.
Purpose of the Study:
- To investigate how General Practitioners (GPs) alter their referral decisions when presented with an unnamed cancer risk algorithm.
- To determine if algorithm use improves referral decision quality and if this is influenced by algorithm information or pre-existing risk under/overestimation.
- To assess the impact of an algorithm on GPs' risk estimation calibration.
Main Methods:
- 157 UK GPs evaluated 20 colorectal cancer vignettes, providing initial risk estimates and referral intentions.
- GPs then received an unnamed algorithm's risk score and could update their responses; half received algorithm details.
- Multilevel regressions analyzed changes in referral decisions and risk estimates, comparing them to NICE guidelines.
Main Results:
- GPs' referral inclination changed in 26% of cases after algorithm use, with 3% switching decisions entirely.
- Referral decisions became more aligned with the NICE 3% threshold (OR 1.45).
- Algorithm impact was greatest for underestimated risks; algorithm information did not affect decisions but improved GP disposition.
Conclusions:
- Cancer risk algorithms show potential for enhancing cancer referral decisions and improving diagnostic accuracy.
- Algorithms may serve as valuable learning tools for GPs to refine their risk assessment capabilities.
- Further research into the optimal implementation and utilization of cancer risk algorithms in primary care is warranted.
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