Evaluating Bias-Mitigated Predictive Models of Perinatal Mood and Anxiety Disorders

In this diagnostic study of predictive models of postpartum depression, clinical prediction models trained to predict psychometric screening results from commonly available EHRs achieved modest performance and were less likely to widen existing health disparities in PMAD diagnosis and potentially treatment. These findings suggest that is critical for researchers and physicians to consider their model design (eg, desired target and predictor variables) and evaluate model bias to minimize health disparities.