Race-Based Bias in Physician Decision Making

1. Race-Based Bias in Physician Decision Making Hal R. Arkes, Ohio State University Neal V. Dawson, MetroHealth Medical Center Society for Judgment and Decision Making November 2008

2. Green et al. (2007). Journal of General Internal Medicine, 22, 1231-1238. • The authors claim to have provided evidence that unconscious (implicit) race bias among physicians is causally associated with fewer recommendations for appropriate thrombolytic therapy for African-American male patients who present with symptoms suggestive of acute coronary symptoms. • This finding represents an attempt to help explain some of the “disparities research” documenting poorer health outcomes for minorities. This is a very important and active research topic. • We contend that Green et al.’s claim is not supported by their data.

3. #1: Details of the Study • From a sample of 776 internal medicine and emergency department (ED) physicians in training (residents) Green et al. obtained data from 220 who were unaware of the purpose of the study or who were not otherwise excluded. • The residents were shown a vignette of a 50-year old male who presented to the ED with chest pain. • With the vignette was randomly paired the face of either a white or black male. • The EKG was “suggestive of anterior myocardial infarction.” • Residents were told that • they didn’t have access to a catheterization lab, and • the patient had no contraindications to thrombolysis.

4. #2: Details of the Study • Subjects were asked to: • Assess the likelihood that the patient’s pain was due to coronary artery disease (5-point scale) • Indicate (yes/no) whether “you would recommend thrombolysis” for this person • Indicate the strength of this recommendation (5-point scale) • Indicate their opinion concerning the effectiveness of thrombolysis for acute myocardial infarction (5-point scale) • Complete 3 Implicit Association Tests (IATs) “to measure bias that may not be consciously recognized.”

5. Quick Tutorial on the IAT • The “IAT measures the time it takes subjects to match members of social groups (e.g., blacks and whites) to particular attributes (e.g., good, bad, cooperative, stubborn).” • A difference in reaction times to associate good or bad concepts with black or white faces is the measure of “implicit bias.” • If you can associate “good” with a white face and “bad” with a black face some milliseconds faster than you can associate “good” with a black face and “bad” with a white face, to that extent you harbor “implicit bias.” • (The IAT is popular and quite controversial.)

6. Which Result Suggests Bias?

7. Our concern #1: Green et al. obtained the data on the left. They assert this is indicative of the “implicit prejudice” of white doctors.

8. Basis for Our Concern #1 • Those with the lowest levels of IAT implicit bias treat the races differently. • Those with the highest levels of IAT bias treat the races equivalently. • This generally is not what we mean by “racial bias.” Such bias implies that those with high levels of it should treat the races differently. • Green et al. base their conclusion on the significant “decrease” in the thrombolytic treatment of black patients and the “increase” (p < .11) in such treatment of white patients as IAT scores rise.

9. Concern #2: No Competing Hypotheses • There is no criterion from which to declare the treatment choice (thrombolysis) to be appropriate or not. • African-Americans are more likely than whites to present with symptoms that strongly mimic coronary disease even in the absence of significant coronary obstruction on angiography (Clark et al. 2001. Heart Disease, 3, 97-108).

10. Our Physician Survey: Procedure • 9 attending-level internists and 2 disparities researchers reviewed the Green et al. study scenario (no patient face present). • Physicians’ tasks: • State the top 5 diseases in their differential diagnosis. • Estimate the probability of each disease. • State whether thrombolysis would be beneficial, neutral, or harmful for each of these 5 diseases.

11. Our Physician Survey: Results • Our physicians indicated that thrombolysis would be harmful if pericarditis or aortic dissection were the actual disease entity. • African-Americans who have a higher probability of being deemed false positive for coronary disease and who actually have pericarditis or aortic dissection would be harmed if they received thrombolysis. • Thus African-Americans who are not given thrombolysis are not necessarily receiving poor medical care.

12. Our Physician Survey: Conclusion • The Green et al. physicians were asked to provide only the likelihood of chronic heart disease rather than provide a differential diagnosis. • But a diagnostician must consider whether the therapy for one possible diagnosis would cause harm if the true diagnosis were an entity other than the favored one. • Even if CHD were the most likely diagnosis, thrombolysis should be avoided if it would result in a high probability of a fatality if the patient had an aortic dissection, for example.

13. Concern #3: The Presence of a Black or White Face Provides Relevant Epidemiological Information • Rates of coronary heart disease (CHD) are lower for black men (NHANES data: Gillum et al. 1997. Annals of Internal Medicine, 127, 111-118). • However higher CHD mortality exists for African-Americans (Clark et al. 2001. Heart Disease, 3, 97-108). • We suggest that Green et al. did not randomize a variable that would be attended to only by prejudiced persons.

14. Concern #3: The Presence of a Black or White Face Provides Relevant Clinical Information: “Spectrum” • A given symptom can be related to different diagnostic outcomes in various subsets of patients. • Races differ in: • renal and cardiovascular damage due to high BP. • proportion who smoke. • # cigarettes/day. • plaque instability. • microembolization. • lots more . . . • Again, we suggest that Green et al. did not randomize a variable that would be attended to only by prejudiced persons.

15. Concern #3: Conclusion • Green et al. suggest that physicians may harbor “unconscious . . . Stereotypes that influence clinical decisions.” • Webster’s definition of stereotype: “Something conforming to a fixed or general pattern, especially a standardized mental picture that is held in common by members of a group that represents an over-simplified opinion, affective attitude, or uncritical judgment.” • A prior probability, on the other hand, is a dynamic feature that is based on the information available at a given point in time. It will change depending on the availability of clinically important information. • Race is one such piece of information. That’s why spectrum effects are important. Such information will be useful even to non-bigots.

16. Concern #4: Causal Attribution • Black/white face was randomized, but subjects were partitioned into low/high IAT scorers. • We don’t know if these two groups are comparable on other covariates. • The high IAT scorers treated the races equivalently, which leads us to suspect that if the IAT had any validity at all, there must be some other factor that appears to mitigate the high-IAT group’s “implicit bias.” • The data are cross-sectional. There are thus no “increases” or “decreases” in one’s IAT score. Cross-sectional data support associations but not causal claims.

17. Relation to Typical JDM Research • JDM researchers often vary a factor that is supposed to be irrelevant in making a judgment or decision. For example, the attractiveness of a defendant should not influence the jury’s verdict. • We deem it an error when this factor is used by mock jurors. • Race is not an irrelevant factor whose use denotes a judgment error. Race is relevant to prior probabilities; it is relevant to spectrum effects.

18. Thus we respectfully disagree with the claim by Green et al. that they have shown that unconscious race bias among physicians is causally associated with fewer recommendations for appropriate thrombolytic treatment for African-American male patients who present with symptoms suggestive of acute coronary syndromes.

19. Thank you. Questions?