Abstract
BACKGROUND: AI chatbots are proliferating in healthcare systems. It is essential to explore how physicians use these tools in order to understand their influence on clinical care and outcomes. Our goal was to understand how physicians conceive of and incorporate AI into clinical decision-making. METHODS: We conducted semistructured interviews with generalist physicians from inpatient and outpatient settings in the USA. Prior to the interview, participants were asked to use an AI chatbot, ChatGPT-4, to complete three mock clinical cases. Physicians were interviewed regarding their perspectives on the AI chatbot. Interviews were analyzed using reflexive thematic analysis and conducted via video conference meeting, where they were recorded and transcribed. RESULTS: We interviewed 22 physicians with 2-32 years of experience (median = 3 years). We identified a central organizing concept of "physician as filter" defining how physicians used the AI chatbot. This idea was composed of four themes. Theme 1: Physicians perceive clinical decision-making as a problem-solving activity, applying internally held knowledge to externally gathered information. Theme 2: AI chatbot systems are part of a continuum of information resources. Theme 3: Trust in the AI chatbot's outputs depends on the user's own clinical knowledge. Theme 4: Clinical decision-making is understood as the personalization of clinical knowledge and context. CONCLUSIONS: AI chatbots may help physicians with formulating a clinical problem and generating a hypothesis by expanding their repertoire of possible cases. Despite the "wealth of information" provided by AI chatbots, physician trust in the outputs is limited, especially when AI chatbots do not provide references. Physician users described filtering chatbot outputs, using their own clinical knowledge and experience, to determine what information is relevant. In describing how providers perceive AI chatbots, we hope to guide further investigation of physician AI interaction and chatbot development that facilitates improved clinical reasoning.