Association between AI-driven conversational agents and physician-patient interaction quality during outpatient consultations: A propensity score matching study in China.
Artificial intelligence conversational agents linked to higher physician-patient interaction quality scores in outpatient visits
Association between AI-driven conversational agents and physician-patient interaction quality during outpatient consultations: A propensity score matching study in China.
This study aimed to use a propensity score matching (propensity score matching) design to examine the association between artificial intelligence (artificial intelligence)-driven conversational agents (conversational agents) and physician-patient interaction quality during outpatient consultations.
We used the Chinese version of the Consultation and Relational Empathy Measure to survey the patients' perceived quality of physician-patient interactions during outpatient consultations, involving 419 adult residents who received outpatient services from China's tertiary public hospitals.
Overall, the propensity score matching results showed a positive causal association of the artificial intelligence-driven conversational agents with the physician-patient interaction quality.
The sensitivity analysis results further showed that when the γ increased to greater than 2, the ATT estimate results remained significant ( P <0.001), indicating the ATT estimate results were not sensitive to the hidden bias.
Our findings will help to confirm the association between the artificial intelligence-driven conversational agents and physician-patient interaction quality, and also offer valuable guidance for policy makers and hospital managers in promoting the adoption of the artificial intelligence-driven conversational agents to continuously improve the physician-patient interaction quality during outpatient consultations.