The workload of clinical documentation contributes to health care costs and professional burnout. The advent of generative artificial intelligence language models presents a promising solution. The perspective of clinicians may contribute to effective and responsible implementation of such tools. This study sought to evaluate 3 uses for generative artificial intelligence for clinical documentation in pediatric emergency medicine, measuring time savings, effort reduction, and physician attitudes and identifying potential risks and barriers. This mixed-methods study was performed with 10 pediatric emergency medicine attending physicians from a single pediatric emergency department. Participants were asked to write a supervisory note for 4 clinical scenarios, with varying levels of complexity, twice without any assistance and twice with the assistance of ChatGPT Version 4.0. Participants evaluated 2 additional ChatGPT-generated clinical summaries: a structured handoff and a visit summary for a family written at an 8th grade reading level. Finally, a semistructured interview was performed to assess physicians’ perspective on the use of ChatGPT in pediatric emergency medicine. Main outcomes and measures included between subjects’ comparisons of the effort and time taken to complete the supervisory note with and without ChatGPT assistance. Effort was measured using a self-reported Likert scale of 0 to 10. Physicians’ scoring of and attitude toward the ChatGPT-generated summaries were measured using a 0 to 10 Likert scale and open-ended questions. Summaries were scored for completeness, accuracy, efficiency, readability, and overall satisfaction. A thematic analysis was performed to analyze the content of the open-ended questions and to identify key themes. ChatGPT yielded a 40% reduction in time and a 33% decrease in effort for supervisory notes in intricate cases, with no discernible effect on simpler notes. ChatGPT-generated summaries for structured handoffs and family letters were highly rated, ranging from 7.0 to 9.0 out of 10, and most participants favored their inclusion in clinical practice. However, there were several critical reservations, out of which a set of general recommendations for applying ChatGPT to clinical summaries was formulated. Pediatric emergency medicine attendings in our study perceived that ChatGPT can deliver high-quality summaries while saving time and effort in many scenarios, but not all.

中文翻译：

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利用生成式人工智能的力量进行临床总结：急诊医生的观点

临床文件的工作量会增加医疗保健成本和职业倦怠。生成人工智能语言模型的出现提供了一个有前途的解决方案。临床医生的观点可能有助于有效和负责任地实施这些工具。本研究旨在评估生成人工智能在儿科急诊医学临床记录中的 3 种用途，衡量节省的时间、减少的精力和医生的态度，并识别潜在的风险和障碍。这项混合方法研究是由来自一个儿科急诊科的 10 名儿科急诊医学主治医生进行的。参与者被要求为 4 个复杂程度不同的临床场景撰写监督记录，其中两次没有任何帮助，两次在 ChatGPT 4.0 版的帮助下。参与者评估了 ChatGPT 生成的另外 2 份临床摘要：结构化交接和以 8 年级阅读水平编写的家庭访问摘要。最后，进行了半结构化访谈，以评估医生对 ChatGPT 在儿科急诊医学中使用的看法。主要结果和测量包括受试者在有和没有 ChatGPT 协助的情况下完成监督记录所花费的努力和时间之间的比较。使用 0 到 10 的自我报告李克特量表来衡量努力程度。使用 0 到 10 的李克特量表和开放式问题来衡量医生对 ChatGPT 生成的摘要的评分和态度。对摘要的完整性、准确性、效率、可读性和总体满意度进行评分。进行主题分析以分析开放式问题的内容并确定关键主题。在复杂情况下，ChatGPT 的监督记录时间减少了 40%，工作量减少了 33%，而对简单记录没有明显影响。 ChatGPT 生成的结构化交接和家庭信件摘要得到了高度评​​价，从 7.0 到 9.0（满分 10 分）不等，大多数参与者赞成将其纳入临床实践。然而，存在一些关键的保留意见，其中制定了一套将 ChatGPT 应用于临床总结的一般建议。我们研究中的儿科急诊医学主治人员认为，ChatGPT 可以提供高质量的摘要，同时在许多情况下（但并非全部）节省时间和精力。