Negative Patient Descriptors: Documenting Racial Bias In The Electronic Health Record (1 credit hour)
Program Summary: This course explores potential implicit bias in healthcare by looking at stigmatizing language in the healthcare record. The course highlights a study using machine learning to analyze electronic health records using 15 different patient descriptors: (non-) adherent, aggressive, agitated, angry, challenging, combative, (non-)compliant, confront, (non-) cooperative, defensive, exaggerate, hysterical, (un-)pleasant, refuse, and resist. A discussion of results and recommendations are given.
This course is recommended for social workers, counselors, and therapists.