Differences in Tone of AI and Care Team Responses to Patient Messages by Patient Demographics

The use of artificial intelligence (AI) to draft responses to patient portal messages has been proposed to reduce provider in-basket burden. However, little is known about its effects on patient–provider communication. In this retrospective observational study, we evaluated demographic differences in the tone of AI-generated draft replies (AI-GDRs) and care team responses to patient messages. Our study included 12,202 message triads comprising patient messages, AI-GDRs, and care team responses from three internal and family medicine practices in New York City. We found differences in tone across patient demographics. AI-GDRs had lower odds of including polite language in responses to Hispanic patients, compared to White patients. AI-GDRs also had lower odds of conveying positive affect in responses to patients who were Hispanic, preferred a non-English language, assigned female sex at birth, or lived in an area with a lower average income. Some of these tone differences were also found in care team responses. Physicians and advanced practice providers had lower odds of conveying positive affect when responding to patients who were Hispanic or preferred a non-English language. Our findings highlight that careful implementation of AI drafting is needed to ensure that this technology does not introduce or amplify inequities in patient–provider communication.