Patient-facing chatbots: Enhancing healthcare accessibility while navigating digital literacy challenges and...

Area of Science:

• Digital Health
• Health Informatics
• Patient Engagement

Background:

• Digital communication in healthcare is growing, yet digital isolation remains a significant social determinant of health.
• Patient-facing chatbots are emerging as a new tool for healthcare interaction.
• Understanding patient attitudes towards these chatbots is essential for equitable access.

Purpose of the Study:

• To investigate patient attitudes toward healthcare chatbots.
• To explore patient perceptions of chatbot use in relation to healthcare access.
• To identify factors influencing patient satisfaction and understanding of chatbot interactions.

Main Methods:

• A mixed-methods study was conducted with users of a healthcare system's chatbot integrated into an electronic health record.
• Online surveys (n=617) and semi-structured interviews (n=46) were employed, with oversampling for racial and ethnic diversity.
• Data collection occurred between November 2022 and May 2024.

Main Results:

• A significant portion of users (35.0%) felt they could not understand the chatbot, and a majority (61.2%) felt the chatbot did not understand them.
• Users who felt completely understood were more likely to perceive the chatbot's intent as facilitating healthcare access (74.8% vs. 41%, p < 0.001).
• Black, Hispanic, less educated, younger, and lower-income participants reported more positive views on chatbots aiding access due to convenience and perceived lack of judgment.

Conclusions:

• Patient experience with chatbots influences their perception of the technology's purpose.
• Chatbot adeptness and historical trust factors may shape preferences for non-judgmental digital interactions.
• Designing inclusive chatbots that address diverse patient needs, especially for those at risk of digital isolation, is critical for expanding digital health equity.