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.

Objectives: 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.Methods: 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.Results: 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.Conclusions: 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.

Is there evidence of age bias in breast cancer health care professionals' treatment of older patients?

OBJECTIVES: Despite NICE (2009; 2018) guidelines to treat breast cancer patients 'irrespective of age', older women experience differential treatment and worse outcomes beyond that which can be explained by patient health or patient choice. Research has evidenced the prevalence of ageism and identified the role of implicit bias in reflecting and perhaps 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. METHODS: This mixed methods study explored age bias amongst breast cancer HCPs through four components: 1) An implicit associations test (31 HCPs) 2) A treatment recommendations questionnaire (46 HCPs). 3) An attitudes about older patients questionnaire (31 HCPs). 4) A treatment recommendations interview (20 HCPs). RESULTS: This study showed that breast cancer HCPs held negative implicit associations towards older women; HCPs were less likely to recommend surgery for older patients; some HCPs held assumptions that older patients are more afraid, less willing and able to be involved in decision-making, and are less willing and able to cope with being informed of a poor treatment prognosis; and conditions which disproportionately affect older patients, such as dementia, are not always well understood by breast cancer HCPs. CONCLUSIONS: These results indicate that there are elements of age bias present amongst breast cancer HCPs. The study's findings of age-based assumptions and a poorer understanding of conditions which disproportionately affect older patients align with patterns of differential treatment towards older breast cancer patients suggesting that age bias may be, at least in part, driving differential treatment.