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Evaluation of Implicit Bias Training in Continuing Medical and Nursing Education to Address Racial Bias in Maternity Health Care Settings.

Public Health Reports 2024 April 23
OBJECTIVES: Implicit bias can affect clinical decisions that influence the care received by patients whose ancestors had been subjected to unfair medical and social practices. However, literature describing the effects of implicit bias training as part of continuing medical and nursing education is scarce. We conducted a longitudinal evaluation of a training for maternal health care clinical and nonclinical staff.

METHODS: A total of 80 staff members at 2 clinical sites in Cleveland, Ohio, participated in the training and evaluation in 2020 and 2021. We used a mixed-methods evaluation to capture changes in knowledge, awareness of bias, and application of strategies to reduce biased behavior by conducting pre- and posttraining surveys immediately after training and interviews at 3 and 6 months posttraining. We conducted univariate and bivariate analyses of the surveys and recorded, transcribed, and analyzed interviews for themes.

RESULTS: Using a threshold of answering 3 of 5 knowledge questions correctly, 50 of 80 (62.5%) trainees who engaged in the evaluation passed the pretraining knowledge questions and 67 (83.8%) passed the posttraining knowledge questions. Of the 80 participants, 75 (93.8%) were women. Interviewees (n = 11) said that low staff-to-patient ratios, lack of racial and ethnic diversity in leadership, inadequate training on implicit bias, and lack of institutional consequences for poor behavior exacerbated bias in maternity care. Interviewees reported having heightened awareness of bias and feeling more empowered after the training to advocate for themselves and patients to prevent and mitigate bias in the hospital.

CONCLUSION: Additional study describing the effect of implicit bias training as part of continuing medical education should be conducted, and administrative and management changes should also be made to prevent bias and improve quality of care.

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