Increasing clinical medical service satisfaction: An investigation into the impacts of Physicians’ use of clinical decision-making support AI on patients’ service satisfaction

The medical industry is one of the key industries for the application of artificial intelligence (AI). Although it is believed that the combination of CDSS and physicians could improve the medical service, there are still many concerns about the usage of CDSS. Based on these concerns, limited studies have answered the question that when a physician makes decision independently or with AI’s help, will there be any differences in patients’ satisfaction with the medical service? This study uses the service fairness theory as a theoretical lens and employs three vignette experiments to address this research gap. There are totally 740 subjects recruited to participate into the three experiments. Group comparison methods and structural equation model are used to verify the hypotheses. The experimental results reveal that: (1) physicians using AI can reduce patients’ service satisfaction (Mdifference=0.404,p=0.004); (2) the negative relationship between AI usage and service satisfaction can partially be mediated through distributive fairness and procedural fairness; (3) physicians actively informing their patients about the usage of AI can help mitigate the reduction in service satisfaction (Mdifference=0.400,p=0.003) and three types of fairness Mdifferencedistributive=0.307,p=0.042;Mdifferenceprocedural=0.483,p<0.001;Mdifferenceinteractional=0.253,p=0.027. This study investigates the effect of physicians using decision-making support AI on their patients’ service satisfaction. These results contribute to the existing literature pertaining to AI and fairness theory, and also help in formulating some practical suggestions for medical staff and AI development companies.