Despite extensive research into patterns of health disparities and the specific contributions of physicians’ clinical decision making to observed differences, much remains to be investigated about the cognitive processes that underlie such associations. Efforts to understand social psychological sources of bias in decision making have proliferated in recent years and made important contributions to our understanding of how stereotyping, prejudice, and uncertainty operate in a medical context. However, this type of work is often constrained by difficulty in making unconfounded causal estimates (particularly disentangling the effects of patient race and SES), as well as inability to determine the extent to which physicians purposely discount the risk faced by certain types of patients. As a result, it remains ambiguous whether variation arise because physicians tend not to consider CHD diagnoses for some types of patients (especially women and younger patients), or if they consider it and then discount it.
Our study addresses these questions by using an experimental priming manipulation to determine the extent to which physicians discount CHD risk in their clinical decision making for some types of patients even when prompted to deliberately consider CHD. The results illustrated in suggest that priming had the desired effect of leading physicians to more fully consider CHD as a diagnostic possibility. The lack of interaction between this variable and patient characteristics suggests that the extent to which CHD is considered a diagnosis worth acting upon is directly influenced by the patient and physician characteristics rather than that CHD does not come to mind as readily with certain demographic groups. Despite the main effect of priming, the priming manipulation did not eliminate disparities in how patients from different groups were diagnosed and treated—that is, gender and age based differences remained. This result suggests that physicians treated the demographic variables of age and gender as diagnostic features that amounted to lower risk of CHD despite identical presentation of CHD symptoms. Despite extensive literature on race and SES differences, we did not observe significant results for these patient characteristics, either as main effects or in interactions with priming. This result suggests that physicians did not rely on these characteristics as diagnostic features, a pattern consistent with existing epidemiologic information about CHD prevalence. It may be that those characteristics would be significant for a condition with larger race and SES differentials, such as diabetes.
Beyond the priming effects, our results corroborate previous work showing that physician gender and level of experience influence clinical decision making. Both women and less experienced physicians tend to ask more questions, and while their diagnostic certainty for CHD is comparable to their male and more experienced counterparts respectively, they are more likely to consider mental health diagnoses and allow more time to pass before seeing the patient for follow-up. By contrast, male and more experienced physicians appear more focused on CHD than alternative candidate diagnoses, and requested a shorter period to follow-up. These differences persisted regardless of patient characteristics and whether the physician was primed.
While patient and physician attributes predicted some expected differences in diagnostic certainty and some types of clinical actions, these factors were not associated with differences in CHD-related test or medication ordering. At the same time, priming led to differences for both of these outcomes, but not for diagnostic certainty (for CHD, GI, or mental health diagnoses). Previous work shows that diagnostic certainty is highly predictive of test and medication ordering, yet these results suggest that (net of the gender and age effects outlined above) a physician’s consideration of a CHD diagnosis may be more important than having high certainty about it in terms of a patient receiving treatment.
We took four precautionary steps in an attempt to minimize possible threats to external validity. First, considerable effort was devoted to ensuring the clinical authenticity of the videotaped presentation. This was achieved by basing the scripts on clinical experience, filming with experienced clinicians present, and by using professional actors/actresses. Second, the subjects (doctors) were specifically asked how typical the patient viewed on the videotape was compared with patients they encounter in everyday practice (89.8% considered them either very typical or reasonably typical). Third, the doctors viewed the vignette in the context of their practice day (not at a professional meeting, a course update, or in their home) so that it was likely they encountered real patients before and after they viewed the patient in the videotape. Fourth, the doctors were specifically instructed at the outset to view the patient as one of their own patients and to respond as they would typically respond in their own practice.
The clinical and policy implications of these results are significant and far-reaching, yet highlight the need for a nuanced approach. On one hand, encouraging physicians to more fully and routinely consider CHD diagnoses may result in greater CHD-relevant testing and prescriptions, while at the same time limiting the pursuit of unnecessary testing and treatment for alternative possibilities (such gastrointestinal conditions). On the other hand, this type of approach will not solve the problem for all types of patients. Specifically, the observed gender and age disparities will not be resolved by training doctors to more thoroughly consider CHD for these populations given physicians appear to discount CHD diagnoses in these types of patients even when prompted to consider a CHD diagnosis. If CHD is under-valued in certain patient populations (and by certain physician populations) as a result of explicit and analytically applied decision rules, the most effective policy strategy will need to address inaccuracies in those decision rules, which could include either clarifying the real distribution of the clinical phenomenon of interest (if, for example, the perceived CHD risk for women was lower than actual epidemiologic base rates) or discouraging over-reliance on prior probabilities to determine risk when the presenting symptoms suggest the risk is higher. If, in contrast, the biases in diagnostic rates are the result of implicit (i.e., non-analytic) discounting of particular diagnoses, the optimal public policy strategy is more likely to involve an emphasis on patient-specific feedback that will allow physicians to be more aware of the discrepancies between their expectations about disease distribution and reality. These principles could be practically implemented through a range of media, including revised clinical practice guidelines for CHD, physician education and training, or increased use of some types of information technology.
While this study answers so me important questions regarding physicians’ cognitive reasoning processes, it also points to additional opportunities for future research. For example, to what extent are physicians accurate in their perceptions of published CHD base rates? In the absence of this information, it is difficult to disentangle the extent to which physicians’ analytic decisions result from inaccurate knowledge of existing base rates versus accurate knowledge of rates accompanied by inappropriate weighting of prior probabilities in determining the likelihood of a condition for a given type of patient. Similarly, to what extent are observed gender and age patterns a function of discounting based on demographic characteristics versus other types of assessments for which demographics act as proxy indicators? Policy interventions of the sort described above will have limited utility if, for example, the demographic characteristic of gender is interpreted by physicians less a marker of biologic difference and more as a proxy for gendered social behaviors that are seen as relevant for health behavior and medical treatment (Lutfey et al. 2008). Finally, we expect that these results may vary by condition, so that conditions that are less life-threatening than CHD, less “silent,” or whose treatments are more reliant on lifestyle change may involve different cognitive processing (such as depression or diabetes). Considered in conjunction with policy reports calling for increased attention to the role of clinical decision making in health disparities (Institute of Medicine 2001
; Institute of Medicine 2003
), these results underscore the importance of examining the social and psychological processes embedded in clinical decision making and the ways those results are related to epidemiologic rates of disease. To the extent that prior assumptions about likelihood of risk override presenting symptoms, physicians remain at increased risk for not only missing potentially life-threatening diagnoses with individual patients, but also for contributing to the reification of bias in some types of health statistics. In a decision making environment largely dominated by Bayesian models (Ashby 2006
), there is a continued and pressing need for sociological and social science perspectives to unravel these associations.