医疗领域人机协同双刃剑效应及其影响因素OA

Objective To clarify the connotation,characteristics,application value and key influencing factors of human-machine collaboration in healthcare,so as to provide scientific support for optimizing clinical practice.Methods Taking artificial intelligence(AI)and human-machine collaboration("artificial-intelligence"OR"AI",OR"human-machine")as the keywords,relevant literature published from January 2010 to October 2024 was retrieved from the databases of PubMed and Web of Science.The connotations,positive effects and potential risks of human-machine collaboration in healthcare were summarized,and its influencing factors were analyzed based on the TOE theory.Results A total of 93 articles were included,covering application scenarios of AI,the connotation of human-machine collaboration,as well as its influencing factors and functions.It was clarified that the connotation of human-machine collaboration in healthcare is an interactive process where clinicians and AI systems can achieve complementary advantages through dynamic coordination,thereby improving the quality and efficiency of medical services.The results showed that human-machine collaboration in healthcare have four positive effects,including improving diagnosis and treatment efficiency,enhancing diagnostic accuracy,optimizing clinical processes,and promoting healthcare accessibility.Meanwhile,five types of potential risks were identified,such as ambiguous responsibility attribution,clinical deskilling,patient privacy leakage,exacerbation of health inequity,and alienation of the doctor-patient relationship.Additionally,15 key influencing factors were identified within a four-dimensional analysis framework from technology,organization,environment and individuals.Conclusion The review elaborates the connotation of medical human-machine collaboration,reveals its"double-edged sword"characteristics,and constructs a four-dimensional analysis framework of influencing factors,thus providing some reference for the practical application of medical human-machine collaboration and formulation of health policies.