Bias and fairness assessment of a natural language processing opioid misuse classifier: Detection and mitigation of electronic health record data disadvantages across racial subgroups

To assess fairness and bias of a previously validated machine learning opioid misuse classifier. The Black FNR subgroup had the greatest severity of disease and risk for poor outcomes. Similar features were present between subgroups for predicting opioid misuse, but inequities were present.