How Clinical and Personal Information Shape Physicians' Risk Judgments

Physicians often form quick judgments about the risk for serious disease when interacting with patients. Underestimating risk can lead to underuse of diagnostic testing and untreated illness, which can worsen patient outcomes. On the other hand, overestimating risk can lead to overuse of diagnostic testing, which is costly for health systems. To form judgments of risk, physicians should attend to a host of validated factors that are predictive of disease. However, research suggests that physicians may rely on demographic factors-such as race and gender. Physicians' judgments could also be influenced by non-health-related, personal information about their patients (e.g., hobbies, nicknames), which may moderate the impact of demographics on those judgments. The investigators examine these dynamics in the context of heart disease. The History, Electrocardiogram, Age, Risk factors and Troponin (HEART) Score is a validated model that specifies a correspondence between certain risk factors and the likelihood of Major Adverse Cardiac Event (MACE). Importantly, there are substantially different diagnostic tests (e.g., noninvasive stress test versus coronary angiogram) that should be used depending on a patient's MACE likelihood. Specifically, the investigators have three research questions: * Research Question 1 (RQ1): How accurate are physicians relative to the benchmarks from the HEART score model? * Research Question 2 (RQ2): How do clinically-relevant risk factors (e.g., smoking history), race, gender, and personal information disclosure influence risk judgments? * Research Question 3 (RQ3): Does personal information disclosure moderate the effects of race and gender on risk judgments? Note that when the investigators discuss accuracy and error, they are referring to the comparison of physician judgments to the HEART score model benchmarks.