Intervention to reduce age bias in medical students' decision making for the treatment of older women with breast cancer: A novel approach to bias training.

Despite NICE guidelines to 'treat people with invasive breast cancer, irrespective of age, with surgery and appropriate systemic therapy, rather than endocrine therapy alone', older patients receive differential treatment and experience worse outcomes. Research has evidenced the prevalence of ageism and identified the role of implicit bias in reflecting and potentially perpetuating disparities across society, including in healthcare. Yet age bias has rarely been considered as an explanatory factor in poorer outcomes for older breast cancer patients nor, consequentially, has removing age bias been considered as an approach to improving outcomes. Many organizations carry out bias training with the aim of reducing negative impacts from biased decision making, yet the few evaluations of these interventions have mostly seen small or negative effects. This study explores whether a novel intervention to address age bias leads to better quality decision making for the treatment of older women with breast cancer. An online study compared medical students' treatment recommendations for older breast cancer patients and the reasoning for their decision making before and after a novel bias training intervention. Thirty-one medical students participated in the study. The results show that the bias training intervention led medical students to make better quality decisions for older breast cancer patients. The quality of decision making was measured by decreases in age-based decision making and increased efforts to include patients in decision making. These results suggest there is value in exploring whether if anti-bias training interventions could usefully be applied in other areas of practice where older patients experience poorer outcomes. This study evidences that bias training improves the quality of decision making by medical students in respect of older breast cancer patients. The study findings show promise that this novel approach to bias training might usefully be applied to all medical practitioners making treatment recommendations for older patients.