Abstract

DATA AND METHODS

We conducted a factorial experiment to simultaneously measure the effects of: (a) patient attributes (age, gender, race and socioeconomic status); (b) physician characteristics (gender and years of clinical experience); and (c) cognitive priming status on medical decision making for an actor “patient” presenting with coronary heart disease in a videotaped vignette. A full factorial of 2⁴ = 16 combinations of patient age (55 vs. 75), gender, race (black vs. white) and socioeconomic status (SES) (lower vs. higher, depicted by current or former employment as a janitor or school teacher) were used for the video scenarios. One of the 16 combinations was shown to each physician.

We employed an availability sample to equally fill four design cells (gender by level of experience). To be eligible for selection, physicians had to: (a) be internists or family/general practitioners with M.D. degrees (international medical graduates were included); (b) have graduated from medical school between 1996–2001 or 1960–87 (to obtain clear separation between higher and lower levels of experience); and (c) be currently working in primary care in North or South Carolina more than half-time. Due to constraints on study size and cost, physician race was not included as an experimental factor and physicians were recruited without regard for race/ethnicity. A letter of introduction was mailed to prospective participants and screening telephone calls were conducted to identify eligible physicians. An appointment was scheduled with each eligible participant at his/her office for a one-on-one, structured interview, lasting one hour. No deception was used in the study: the experiment was introduced to the physicians as a study of medical decision making (without reference to CHD) and the vignettes were referred to such and without suggestion that they were real patient cases.

Half of all physicians were primed (i.e., explicitly directed) to consider a CHD diagnosis. For those who were designated to be primed, the interviewer read the following cover story in addition to the regular introduction heard by all participants prior to viewing the vignette: “The patient in the video was recently on vacation and sought medical advice for her/his symptoms. The physician mentioned the possibility of coronary heart disease and suggested s/he see her/his primarycarephysicianuponreturninghome.”Primingstatuswasassignedatrandomwhenthe physician was enrolled in the study and the interview appointment scheduled (vignettes were randomly assigned to participants at the same time).

After viewing the videotaped vignette, physicians were asked to identify “the most likely condition” and to list additional candidate diagnoses they were considering. For each diagnostic possibility participants were asked to assign a number indicating their level of certainty on a scale of 0–100 with 0 indicating no certainty and 100 indicating complete certainty. They were also asked a series of structured interview questions regarding how they would treat the patient, with responses being recorded verbatim and coded in-house after the interview was completed (see Table 1).

The required 256 interviews (16 vignettes x 4 combinations of physician attributes x 2 priming conditions x 2 replications) were conducted over a period of ten months in 2006–7. IRB approval for the study was obtained and signed informed consents were collected from each participating physician. Each physician subject was provided a stipend ($200) to partially offset lost revenue and to acknowledge their participation.

The medical condition (CHD) was selected because: a) it is among the most common and costly problems presented by older patients to primary care providers (Cohen and Krauss 2003); b) it represents an example of a well-defined organic medical condition; c) it admits a range of diagnostic, therapeutic and lifestyle actions; and d) it is an extensively studied condition in which variations in diagnostic and treatment decisions have been repeatedly demonstrated. The script was developed from several tape-recorded role-playing sessions with experienced clinical advisors. Patients in the vignette presented with signs and symptoms suggestive of CHD, including chest pain worsening with exertion, pain in the back between the shoulder blades, stress, and elevated blood pressure. The vignette scripts, including non-verbal gestures, were identical for each vignette condition. Because live patients do not typically present as clear-cut textbook cases of specific conditions, the vignette also built in several red herring symptoms potentially indicative of a gastrointestinal (GI) diagnosis. To this end, the patient also complained of indigestion, feeling worse after a large or spicy meal, having pain similar to heart burn but unresponsive to antacids, and feeling full and “gassy.” This was done not specifically to make the physicians’ diagnostic task more difficult, but to more accurately represent how actual patients present, based on advice from our clinical advisors. The vignette also incorporates references to the patient’s mood, including the spouse’s report that the patient has been difficult to be around and the patient’s self -report of feeling irritated and having decreased energy.

Professional actors were trained under experienced physician supervision to realistically and consistently portray a patient presenting with these signs/symptoms to a primary care provider. An advantage of videotapes (over written scenarios) is that potentially relevant nonverbal indicators (e.g., the “Levine fist” as an indicator of cardiac pain) can be embedded in the presentation. In a direct comparison of vignettes, standardized patients, and chart abstraction, Peabody and colleagues (2000) found that vignettes were a valid and comprehensive method for measuring quality of outpatient care, and that vignettes consistently produced results that were closer to standardized patients than were chart abstraction results.

RESULTS

Mean scores and descriptive information for each variable are reported in Table 1. As expected, based on the presentation of key symptoms in the vignette, the vast majority of physicians correctly identified CHD (98.8%) somewhere in their differential diagnosis, with an average of 6.3 total diagnoses generated by each physician. However, diagnostic certainty for CHD was much more varied, with an average of 57.4 on a scale of 0–100 and a standard deviation of 23.0. Similarly, most physicians (98.0%) identified a gastrointestinal (GI) diagnosis, with an average diagnostic certainty of 54.7 out of 100 (standard deviation of 26.7); mental health diagnoses were also common, identified by 76.6% of physicians with an average diagnostic certainty of 43.1 (standard deviation of 33.0).

DISCUSSION

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 Table 4 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.

Acknowledgments

Contributor Information

Karen E. Lutfey, New England Research Institutes.

Kevin W. Eva, McMaster University.

Eric Gerstenberger, New England Research Institutes.

Carol L. Link, New England Research Institutes.

John B. McKinlay, New England Research Institutes.

References