Implicit Gender Bias and the Use of Cardiovascular Tests Among Cardiologists. Issue 12 (29th November 2017) - Daugherty, Stacie L.; Blair, Irene V.; Havranek, Edward P.; Furniss, Anna; Dickinson, L. Miriam; Karimkhani, Elhum; Main, Deborah S.; Masoudi, Frederick A.
Abstract : Background: Physicians' gender bias may contribute to gender disparities in cardiovascular testing. We used the Implicit Association Test to examine the association of implicit gender biases with decisions to use cardiovascular tests. Methods and Results: In 2014, cardiologists completed Implicit Association Tests and a clinical vignette with patient gender randomly assigned. The Implicit Association Tests measured implicit gender bias for the characteristics of strength and risk taking. The vignette represented an intermediate likelihood of coronary artery disease regardless of patient gender: chest pain (part 1) followed by an abnormal exercise treadmill test (part 2). Cardiologists rated the likelihood of coronary artery disease and the usefulness of stress testing and angiography for the assigned patient. Of the 503 respondents (9.3% of eligible; 87% male, median age of 45 years, 58% in private practice), the majority associated strength or risk taking implicitly with male more than female patients. The estimated likelihood of coronary artery disease for both parts of the vignette was similar by patient gender. The utility of secondary stress testing after an abnormal exercise treadmill test was rated as "high" more often for female than male patients (32.8% versus 24.3%, P =0.04); this difference did not vary with implicit bias. Angiography was more consistently rated as having "high" utility for male versus female patients (part 1: 19.7% versus 9.8%; part 2: 73.7% versus 64.3%; P <0.05 for both); this difference was larger for cardiologists with higher implicit gender bias on risk taking ( P =0.01). Conclusions: Cardiologists have varying degrees of implicit gender bias. This bias explained some, but not all, of the gender variability in simulated clinical decision‐making for suspected coronary artery disease.