563 - Implementing a "Bias Check" Intervention on Academic Rounds and its Impact on Implicit Bias in Patient Care

Poster Number: 563
Publication Number: 563.23

Mackenzie Heywood, University of Maryland Children's Hospital, Baltimore, MD, United States; Steven Gercken, University of Maryland School of Medicine, Baltimore, MD, United States; Rebecca Carter, University of Maryland School of Medicine, Baltimore, MD, United States

Background: Implicit bias refers to attitudes or stereotypes that unconsciously affect individual understanding, actions, and decisions, leading to the formation of assumptions about groups based on race, ethnicity, gender, or appearance. Multiple studies demonstrate the existence of implicit bias in healthcare providers, influencing clinical decision-making, patient care, and health disparities. Current proposed interventions to mitigate implicit bias in healthcare primarily aim to promote long-term personal reflection or institutional culture change. The lack of practical daily interventions in the clinical environment necessitates the development of tools to reduce implicit bias’s potential negative impact.

Objective: The objective of this study was to formulate practical, day-to-day interventions in the clinical environment to reduce implicit bias’s potential negative impact on patient-provider interactions by making provider’s more aware of their own biases.

Design/Methods: A short “bias check,” consisting of a team discussion of areas of bias influencing care of each patient, was designed to occur following each patient presentation in daily rounds on a pediatric hospitalist service. Participants in an urban, academic pediatric residency were included in the study. A deidentified, 24-item, validated questionnaire on implicit bias was adapted and administered to PGY-1 residents following the conclusion of each study block. Residents who did not participate in the intervention were included as control samples. Incoming PGY-1 residents were also surveyed during orientation to serve as an additional control group.

Results:
A linear regression analysis evaluated the survey item questioning if individuals can eliminate their implicit bias. Statistically significant differences were found for the following: increasing the number of rotations was positively associated with the belief that implicit bias can be eliminated (p = 0.04), and participation in bias checks decreased the belief that individuals can eliminate implicit bias (p = 0.01).


Conclusion(s): Implicit bias has been demonstrated to influence clinical decision-making and patient care. One proposed step in minimizing the effect of these biases is to increase one’s self-awareness of them. Our pilot study demonstrated that more clinical time increased the belief that one could eliminate their own biases, yet participating in “bias checks” had decreased association with this belief. Future steps include continuing these checks on further clinical rotations to elucidate a possible Dunning-Kruger effect for implicit bias awareness.