The Interaction of Patient Race, Provider Bias, and Clinical Ambiguity on Pain Management Decisions

Abstract

Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and non-opioid analgesics) decisions for 12 virtual patients with acute pain. Race (Black/White) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers’ decisions, such that decisions varied as a function of ambiguity for White but not Black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however providers’ implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between White and Black patients are, in part, attributable to the nature (i.e., ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors.

Differential Effect of Patient Weight on Pain-Related Judgements About Male and Female Chronic Low Back Pain Patients

“…Most previous studies examining pain judgments have asked participants to make ratings of text vignettes, 6,9,10,11 still images of patients, 8 or videos of computer-simulated patients. 30,31,56 Likewise, studies examining weight bias have tended to use text vignettes, 53,60 figure drawings, 24,28,72 or still images. 29,50,62,73,75 In contrast, participants in the current study rated videos of actual patients completing a standardized and highly relevant functional task.…”

“…Additionally, because all patients were White, it is unknown how patient race may influence these judgments. Given evidence that racial bias affects pain treatment recommendations, 31 future studies should also investigate whether and how patient race interacts with patient gender and weight in this context. Although previous research examined the independent effects of patient gender and weight on pain-related judgments, to our knowledge, this is the first study to investigate the interaction of patient gender and weight on pain assessment, pain attributions, and pain treatment recommendations.…”

Treating without Seeing: Pain Management Practice in a Thai Context

“…The differing cultures found within different wards in existing healthcare organizations have also been shown to have a significant influence on the nursing culture and how the organizational culture influences nurses' thinking and decisions [13]. Professional ambitions for sustainable improvement in postoperative care related to pain management, such as those of the Joint Commission for Accreditation of Healthcare Organizations (JCAHO) [22], are valuable resources for health care organizations when changing their pain assessment and management processes to meet the new standards [23, 24].…”

“…Understanding the impact of the nurse-patient relationship within the nursing culture on effective pain management is a key issue in improving and optimizing pain management [1, 7–10]. The ethnonursing method has been in development since the mid-1940s and can help nurses to better understand the effects of differences in cultural beliefs, care structures, and other extramedical factors as well as the presence and effects of biases about gender, religion, and national origin [11–13]. …”

Shared Decision Making With Vulnerable Populations in the Emergency Department

“…Such work should focus not only on the population of interest, but also on the clinical scenario, as there is some suggestion that decision ambiguity interacts with race and bias in determining optimal decision-making strategy. 65,66 Whether all patients should be asked about decision-making preferences and best practices for standardization of information sharing and for deliberation and decision making remain to be described. Consideration of the special needs and challenges of vulnerable populations should inform such investigations and researchers should make every effort to foster interest in promoting SDM with community representatives.…”