The Ladder of Inference as a Tool to Reduce Implicit Bias in Neonatal Intensive Care Unit (NICU) Clinical Practice

Abstract: Healthcare professional implicit bias is a widespread phenomenon that leads to worse healthcare outcomes for marginalized populations. In neonatal intensive care, studies have found significantly higher morbidity and mortality in minoritized and marginalized newborns. The “Ladder of Inference” (LOI) tool can help healthcare providers identify implicit biases impacting the clinical care they are providing and enable them to take corrective action. This instrument elucidates the process by which we take in information about another person, filter that data through our own perspectives and biases, and then use it to draw conclusions. These conclusions are often profoundly inaccurate, yet they impact our behaviors toward others. In this session, we will propose the LOI as an “implicit bias detection tool” to improve NICU clinical practice. Using two example NICU cases, we will demonstrate how the LOI can uncover mechanisms by which positive and negative feedback loops fueled by unregulated implicit bias lead to a stepwise increase or decrease in quality of care. Subtle differences in individual steps up the ladder result in large magnitude care differences for patients and families. We argue that this shift in the quality of care likely contributes to the significant neonatal outcome disparities in minoritized infants, but that this can be counteracted by using the LOI as a practical tool to detect and mitigate implicit biases and inferences. We will also engage the audience in elucidating complimentary strategies to decrease exposure to implicit bias in healthcare for marginalized families in neonatal care and other patient populations.

Stephanie Kukora – Children's Mercy Hospital; Autumn Fiester – University of Pennsylvania