Viewpoint
观点
Utility of ChatGPT in Clinical Practice
ChatGPT在临床实践中的应用价值
Jialin Liu1,2,3, MD; Changyu Wang1,4, BSc; Siru Liu5, PhD
Jialin Liu1,2,3, MD; Changyu Wang1,4, BSc; Siru Liu5, PhD
Corresponding Author:
通讯作者:
Abstract
摘要
ChatGPT is receiving increasing attention and has a variety of application scenarios in clinical practice. In clinical decision support, ChatGPT has been used to generate accurate differential diagnosis lists, support clinical decision-making, optimize clinical decision support, and provide insights for cancer screening decisions. In addition, ChatGPT has been used for intelligent question-answering to provide reliable information about diseases and medical queries. In terms of medical documentation, ChatGPT has proven effective in generating patient clinical letters, radiology reports, medical notes, and discharge summaries, improving efficiency and accuracy for health care providers. Future research directions include real-time monitoring and predictive analytics, precision medicine and personalized treatment, the role of ChatGPT in tele medicine and remote health care, and integration with existing health care systems. Overall, ChatGPT is a valuable tool that complements the expertise of health care providers and improves clinical decision-making and patient care. However, ChatGPT is a double-edged sword. We need to carefully consider and study the benefits and potential dangers of ChatGPT. In this viewpoint, we discuss recent advances in ChatGPT research in clinical practice and suggest possible risks and challenges of using ChatGPT in clinical practice. It will help guide and support future artificial intelligence research similar to ChatGPT in health.
ChatGPT正受到越来越多的关注，并在临床实践中拥有多样化的应用场景。在临床决策支持方面，ChatGPT已被用于生成准确的鉴别诊断列表、辅助临床决策、优化临床决策支持系统，并为癌症筛查决策提供参考。此外，ChatGPT还应用于智能问答系统，为疾病和医疗咨询提供可靠信息。在医疗文书方面，ChatGPT能高效生成患者临床信函、放射学报告、医疗记录和出院小结，提升了医护人员的效率与准确性。未来研究方向包括实时监测与预测分析、精准医疗与个性化治疗、ChatGPT在远程医疗中的作用，以及与现有医疗系统的整合。总体而言，ChatGPT是辅助医疗专业人员、改善临床决策和患者护理的有力工具。但ChatGPT是一把双刃剑，我们需要审慎考量其益处与潜在风险。本文探讨了ChatGPT在临床实践中的最新研究进展，并提出其在临床应用中的潜在风险与挑战，这将为未来类似ChatGPT的医疗人工智能研究提供指导与支持。
(J Med Internet Res 2023;25:e48568) doi: 10.2196/48568
(J Med Internet Res 2023;25:e48568) doi: 10.2196/48568
KEYWORDS
关键词
ChatGPT; artificial intelligence; large language models; clinical practice; large language model; natural language processing; NLP; doctor-patient; patient-physician; communication; challenges; barriers; recommendations; guidance; guidelines; best practices; risks
ChatGPT；人工智能；大语言模型；临床实践；大语言模型；自然语言处理；NLP；医患；患者-医生；沟通；挑战；障碍；建议；指导；指南；最佳实践；风险
Introduction
引言
ChatGPT is a large language model developed by OpenAI. It is based on the GPT architecture and uses deep learning techniques to generate natural language text [1,2]. The model has been developed using supervised and reinforcement learning strategies [3]. ChatGPT can generate coherent, grammatically correct text, which is an important development in artificial intelligence (AI) [4]. It shows great potential for using large language models and reinforcement learning from human feedback to improve clinical decision support (CDS) alert logic and potentially other medical areas involving complex clinical logic, a key step in the development of an advanced learning health care system. ChatGPT has quickly gained worldwide attention for its accurate well-formulated responses to various topics. As physicians, we have the opportunity to help guide and develop new ways of using this powerful tool. It can be used in research and development to analyze large amounts of medical data, identify trends, and provide insights into best clinical practices. Physicians need to consider using ChatGPT in their clinical practice. Furthermore, we are using ChatGPT as a tool to support physicians’ clinical practice, not to replace them.
ChatGPT是由OpenAI开发的大语言模型。它基于GPT架构，采用深度学习技术生成自然语言文本[1,2]。该模型通过监督学习和强化学习策略进行训练[3]。ChatGPT能生成连贯、语法正确的文本，这是人工智能(AI)领域的重要进展[4]。它展现出利用大语言模型和人类反馈强化学习改进临床决策支持(CDS)警报逻辑的巨大潜力，并可能应用于其他涉及复杂临床逻辑的医疗领域，这是发展高级学习型医疗系统的关键一步。ChatGPT因能对各种话题给出准确规范的答复而迅速获得全球关注。作为医生，我们有责任引导并开发这一强大工具的新应用方式。它可用于研发领域分析海量医疗数据、识别趋势并提供最佳临床实践建议。医生应考虑将ChatGPT应用于临床实践。需强调的是，我们是将ChatGPT作为辅助医生临床实践的工具，而非替代品。
Despite the increasing popularity and performance of ChatGPT, there is still a lack of studies evaluating its use in clinical practice. At the same time, we should be aware that ChatGPT is a double-edged sword, with powerful functions and potential dangers. To better understand the application of ChatGPT in clinical practice, we introduced the recent progress of ChatGPT in clinical practice to help interested researchers effectively grasp the key aspects of this topic and to provide possible future research directions. The purpose of this viewpoint is to provide an overview of the recent advances in ChatGPT in clinical practice (Multimedia Appendix 1 [5-16]), to explore the future direction of ChatGPT in clinical practice, to highlight the risks and challenges of its use in clinical practice, and to propose appropriate mitigation strategies. Although ChatGPT has demonstrated promising prospects in clinical practice, further research is needed to refine and improve its capabilities. Integrating ChatGPT into existing electronic health record (EHR) systems has the potential to improve diagnostic accuracy, treatment planning, and patient outcomes. However, it is essential to regard ChatGPT as a valuable tool that supplements the expertise of health care professionals rather than replacing them.
尽管ChatGPT日益普及且性能不断提升，但目前仍缺乏对其在临床实践中应用效果的研究评估。与此同时，我们应认识到ChatGPT是把双刃剑，既具备强大功能又存在潜在风险。为更好地理解ChatGPT在临床实践中的应用，本文介绍了ChatGPT在临床领域的最新进展，旨在帮助相关研究者有效把握该主题的核心要点，并提供未来可能的研究方向。本文旨在：(1) 综述ChatGPT在临床实践中的最新进展（多媒体附录1 [5-16]）；(2) 探讨ChatGPT在临床实践中的未来发展方向；(3) 强调其在临床应用中存在的风险与挑战；(4) 提出相应的缓解策略。虽然ChatGPT在临床实践中展现出良好前景，但仍需进一步研究以完善其功能。将ChatGPT整合至现有电子健康档案(EHR)系统，有望提升诊断准确性、治疗方案制定和患者预后效果。但必须明确：ChatGPT应作为补充医疗专业人员专业知识的辅助工具，而非替代者。
Clinical Decision Support
临床决策支持
Clinical decision-making is a complex process. It involves many factors, such as the physician’s clinical thinking, clinical reasoning, individual judgement, and the patient’s condition [17]. These factors can lead to cognitive biases, errors in reasoning, and preventable harm. AI-based CDS can effectively support physicians’ clinical decisions and improve treatment outcomes [18]. Current applications of ChatGPT in CDS include the following:
临床决策是一个复杂的过程，涉及诸多因素，例如医生的临床思维、临床推理、个人判断以及患者病情 [17]。这些因素可能导致认知偏差、推理错误和可预防的伤害。基于AI的临床决策支持(CDS)能有效辅助医生临床决策并改善治疗结果 [18]。当前ChatGPT在CDS中的应用主要包括：
Differential-diagnosis lists: Hirosawa et al [5] evaluated ChatGPT-3 and general internal medicine physicians to generate clinical cases, correct diagnoses, and five differential diagnoses for 10 common chief complaints. In the 10 differential diagnosis lists, the correct diagnosis rate of ChatGPT-3 was 28 out of 30 $(93.3%)$ . In the 5 differential diagnosis lists, the correct diagnosis rate of physicians was superior to ChatGPT-3 $98.3%$ vs $83.3%$ ; $P{=}.03,$ . In the 10 differential diagnosis lists generated by ChatGPT-3, the consistent differential diagnosis rate of the doctors was 62 out of 88 $(70.5%)$ . This study shows that the differential diagnosis list generated by ChatGPT-3 has high diagnostic accuracy for clinical cases with common chief complaints. Clinical decision-making: Rao et al [6] entered all 36 published clinical vignettes from the Merck Sharp & Dohme (MSD) Clinical Manual into ChatGPT and compared the accuracy of differential diagnosis, diagnostic tests, final diagnosis, and management according to the patient age and gender, and the sensitivity of the case. ChatGPT achieved an overall accuracy rate of $71.7%$ $95%$ CI $69.3%-74.1%$ ) across all 36 clinical cases.
鉴别诊断列表：Hirosawa等人[5]评估了ChatGPT-3和普通内科医生针对10种常见主诉生成临床病例、正确诊断及五项鉴别诊断的能力。在10项鉴别诊断列表中，ChatGPT-3的正确诊断率为30例中的28例$(93.3%)$。在5项鉴别诊断列表中，医生的正确诊断率优于ChatGPT-3($98.3%$ vs $83.3%$；$P{=}.03$)。在ChatGPT-3生成的10项鉴别诊断列表中，医生的一致性鉴别诊断率为88例中的62例$(70.5%)$。该研究表明，ChatGPT-3生成的鉴别诊断列表对常见主诉的临床病例具有较高诊断准确性。临床决策：Rao等人[6]将《默克诊疗手册》(MSD Manual)中全部36个已发表临床案例输入ChatGPT，根据患者年龄、性别及病例敏感度，对比分析了鉴别诊断、诊断检查、最终诊断和治疗方案的准确性。ChatGPT在36个临床案例中的总体准确率为$71.7%$($95%$ CI $69.3%-74.1%$)。
Cancer screening: Rao et al [7] compared ChatGPT responses with the American College of Radiology appropriateness criteria for breast pain and breast cancer screening. The ChatGPT prompt formats were open-ended (OE) and select all that apply (SATA). The results of the study showed that breast cancer screening achieved an average OE score of 1.83 out of 2, with an average correct rate of $88.9%$ for SATA; breast pain achieved an average OE score of 1.125 out of 2, with an average correct rate of $58.3%$ for SATA. The results show the feasibility of using ChatGPT for radiological decision-making and have the potential to improve clinical workflow.
癌症筛查：Rao等[7]将ChatGPT的回答与美国放射学会(ACR)关于乳房疼痛和乳腺癌筛查的适用性标准进行了比较。ChatGPT的提示格式分为开放式(OE)和"全选适用项"(SATA)两种。研究结果显示，在乳腺癌筛查方面，OE平均得分为1.83分(满分2分)，SATA平均正确率为$88.9%$；在乳房疼痛方面，OE平均得分为1.125分(满分2分)，SATA平均正确率为$58.3%$。结果表明使用ChatGPT进行放射学决策的可行性，并具有改善临床工作流程的潜力。
CDS optimization: Liu et al [8] studied 5 clinicians’ ratings of $36\mathrm{CDS}$ recommendations generated by ChatGPT and 29 recommendations generated by experts. The research results revealed that 9 of the top 20 recommendations in the survey were generated by ChatGPT. The study found that recommendations generated by ChatGPT provided a unique perspective and were rated as highly understandable and relevant, moderately useful but with low acceptability, bias, inversion, and redundancy. These recommendations can be an important complementary part of optimizing CDS alerts, identifying potential improvements to alert logic and supporting their implementation or even helping experts to develop their recommendations for CDS improvements.
CDS优化：Liu等人[8]研究了5位临床医生对ChatGPT生成的36条CDS建议和专家生成的29条建议的评分。研究结果显示，调查中排名前20的建议中有9条由ChatGPT生成。研究发现，ChatGPT生成的建议提供了独特视角，被评为高度可理解且相关，中等有用但接受度较低，存在偏见、反转和冗余问题。这些建议可作为优化CDS警报的重要补充，帮助识别警报逻辑的潜在改进点，支持其实施，甚至协助专家制定CDS改进建议。
ChatGPT has been evaluated for CDS applications. It has been shown to generate accurate lists of differential diagnoses, clinical decision making, optimize CDS, and provide insights for cancer screening decisions. Further research could focus on developing advanced models that integrate ChatGPT with existing CDS systems. These models can leverage the extensive medical literature, clinical guidelines, and patient data to support physicians in making accurate diagnoses, formulating treatment plans, and predicting patient outcomes. By combining the expertise of health care professionals with the capabilities of ChatGPT, comprehensive and personalized decision support is provided.
ChatGPT已针对临床决策支持(CDS)应用进行评估。研究表明，它能生成准确的鉴别诊断列表、辅助临床决策、优化CDS系统，并为癌症筛查决策提供见解。未来研究可重点开发将ChatGPT与现有CDS系统整合的进阶模型。这些模型能利用海量医学文献、临床指南和患者数据，辅助医生进行精准诊断、制定治疗方案及预测患者预后。通过结合医疗专业人员的经验与ChatGPT的能力，可提供全面且个性化的决策支持。
Question-Answer (Medical Queries)
问答 (医学查询)
Intelligent question-answering is often used to provide information about diseases or to discuss the results of clinical tests. The use of intelligent question-answering in clinical practice has various benefits for health care systems, such as support for health care professionals and patients, triage, disease screening, health management, consultation, and training of health care professionals [19]. ChatGPT can be used for intelligent question-answering in health care. However, it should be noted that the answers may change over time and with different question prompts and that harmful biases in answers may occur [9]. It is important to use ChatGPT responsibly to ensure that they can help and not harm users seeking disease knowledge and information. Below are some examples of ChatGPT’s application in medical queries, demonstrating its potential in generating intelligent questions and answer prompts for various diseases:
智能问答常用于提供疾病相关信息或讨论临床检测结果。在临床实践中使用智能问答可为医疗保健系统带来多重益处，例如为医护人员和患者提供支持、分诊、疾病筛查、健康管理、咨询以及医护人员培训 [19]。ChatGPT可用于医疗保健领域的智能问答。但需注意，答案可能随时间推移和不同提问方式而变化，且回答中可能出现有害偏见 [9]。负责任地使用ChatGPT至关重要，以确保其能帮助而非伤害寻求疾病知识的用户。以下是ChatGPT在医学查询中的应用示例，展示其为各类疾病生成智能问答提示的潜力：
Common retinal diseases: Potapenko et al [10] conducted a study to evaluate the accuracy of ChatGPT in providing information on common retinal diseases: age-related macular degeneration, diabetic ret in opa thy, retinal vein occlusion, retinal artery occlusion, and central serous c horio ret in opa thy. A total of 100 responses were obtained through a series of questions that included the disease summary, prevention, treatment options, and prognosis for each disease. The results indicate that ChatGPT provides highly accurate general information (median score 5, IQR 4-5, range 3-5), disease prevention information (median 4, IQR 4-5, range 4-5), prognosis information (median 5, IQR 4-5, range 3-5), and treatment options (median 3, IQR 2-3, range 2-5). Reliability statistics showed a Cronbach $\alpha$ of .910 ( $95%$ CI .867-.940). Of the 100 responses evaluated, 45 were rated as very good with no inaccuracies, 26 had minor harmless inaccuracies, 17 were marked as potentially misinterpreted inaccuracies, and 12 had potentially harmful errors.
常见视网膜疾病：Potapenko等人[10]开展了一项研究，评估ChatGPT在提供常见视网膜疾病信息时的准确性，包括年龄相关性黄斑变性、糖尿病视网膜病变、视网膜静脉阻塞、视网膜动脉阻塞和中心性浆液性脉络膜视网膜病变。通过一系列涉及疾病概述、预防措施、治疗方案及预后的提问，共获得100条回答。结果显示，ChatGPT在提供疾病概述（中位数评分5，四分位距4-5，范围3-5）、预防信息（中位数4，四分位距4-5，范围4-5）、预后信息（中位数5，四分位距4-5，范围3-5）和治疗方案（中位数3，四分位距2-3，范围2-5）方面具有较高准确性。信度分析显示Cronbach $\alpha$ 系数为.910（95%置信区间.867-.940）。在评估的100条回答中，45条被评为优秀且无错误，26条存在无害微小错误，17条存在可能被误解的错误，12条包含潜在有害错误。
Obstetrics and gynecology: Grünebaum et al [9] presented a series of questions (14 questions) on obstetrics and gynecology to ChatGPT, and evaluated the answers to each question. The study shows that ChatGPT is valuable for users seeking preliminary information on almost any topic in the field. The answers are generally convincing and informative. They do not contain a significant number of errors or misinformation. A major drawback is that the data on which the model is trained does not appear to be easily updatable.
妇产科：Grünebaum等人[9]向ChatGPT提出了一系列妇产科相关问题(14个问题)，并对每个问题的回答进行了评估。研究表明，ChatGPT对于寻求该领域几乎所有主题初步信息的用户具有重要价值。这些回答通常具有说服力且信息丰富，不包含大量错误或误导性信息。主要缺陷在于模型训练所依据的数据似乎不易更新。
Hepatic disease: Yeo et al [11] investigated the accuracy and reproducibility of the ChatGPT in answering questions about knowledge, management, and emotional support for cirrhosis and hepatocellular carcinoma (HCC). The responses to the 164 questions in ChatGPT were independently assessed by two transplant he pato logi sts and reviewed by a third reviewer. The results of the study showed that ChatGPT had extensive knowledge of cirrhosis $(79.1%$ correct) and HCC $74%$ correct). However, only a small proportion ( $47.3%$ for cirrhosis and $41.1%$ for HCC) was rated as comprehensive. Performance was better in basic knowledge, lifestyle, and treatment than in diagnosis and prevention. Regarding quality measures, the model answered $76.9%$ of questions correctly but failed to provide specific decision cutoff points and treatment duration. ChatGPT may have a role as a supplementary information tool for patients and physicians to improve outcomes.
肝脏疾病：Yeo等[11]研究了ChatGPT在回答肝硬化与肝细胞癌(HCC)相关知识、管理和情感支持问题时的准确性与可重复性。两位移植肝病学家对ChatGPT回答的164个问题进行了独立评估，并由第三位评审人复核。研究结果显示，ChatGPT对肝硬化$(79.1%$正确率)和HCC$(74%$正确率)具有广泛认知，但仅少部分回答(肝硬化$47.3%$，HCC$41.1%$)被评为全面覆盖。该模型在基础知识、生活方式和治疗方面表现优于诊断和预防领域。在质量指标方面，模型正确回答了$76.9%$的问题，但未能提供具体的决策临界点和治疗周期。ChatGPT可能作为辅助信息工具帮助医患改善诊疗结果。
Cancer: Johnson et al [12] used questions from the “Common Cancer Myths and Misconceptions” web page to assess the accuracy of ChatGPT and National Cancer Institute (NCI) answers to the questions. The results showed an overall accuracy of $100%$ for NCI answers and $96.9%$ for questions 1 to 13 output by ChatGPT $(\mathrm{k}{=}-0.03$ , SE 0.08). There was no significant difference in word count and readability between NCI and ChatGPT answers. ChatGPT provided accurate information about common cancer myths and misconceptions.
癌症：Johnson 等人 [12] 使用"常见癌症谣言与误解"网页中的问题评估了 ChatGPT 和美国国家癌症研究所 (NCI) 的回答准确性。结果显示 NCI 答案的总体准确率为 $100%$，ChatGPT 对问题 1 至 13 的输出准确率为 $96.9%$ $(\mathrm{k}{=}-0.03$，SE 0.08)。NCI 与 ChatGPT 回答的字数和可读性无显著差异。ChatGPT 提供了关于常见癌症谣言与误解的准确信息。
The use of ChatGPT in answering medical queries has shown promise in assisting health care professionals by providing reliable information and guidance. However, ChatGPT’s responses are generated based on patterns and knowledge learned from training data, and it does not currently have up-to-date medical information or take into account specific patient situations. Therefore, health care providers should exercise caution and independently verify key information obtained from ChatGPT to ensure accuracy and appropriateness for individual patients. Careful and responsible use, as well as continued research and development, are necessary to maximize its benefits and minimize potential limitations.
ChatGPT在回答医疗咨询方面的应用已显示出为医疗专业人员提供可靠信息和指导的潜力。然而，ChatGPT的回复是基于训练数据中学到的模式和知识生成的，目前不具备最新医疗信息，也无法考虑特定患者情况。因此，医疗提供者应谨慎行事，并独立验证从ChatGPT获取的关键信息，以确保其准确性和对个体患者的适用性。为最大化其效益并减少潜在局限，有必要进行负责任的使用以及持续研发。
Medical Document
医疗文档
Overview
概述
Writing medical documents is a tedious and time-consuming process for health care providers. At the same time, errors in medical documentation are common [20,21]. Correctly documenting and exchanging clinical information between physician and patient is paramount. Medical documentation requires a high level of accuracy, so recorders should be able to capture and accurately record all medical information discussed during the interview. ChatGPT is an effective tool for medical documentation [13,22]. Using ChatGPT as a language assistant or providing templates can significantly reduce the time and improve the accuracy of medical documentation for clinicians [2]. The following four subsections illustrate specific areas where ChatGPT can be effectively applied, including the generation of patient clinic letters, radiology reports, medical notes, and discharge summaries, demonstrating its potential to simplify medical documentation and improve clinician efficiency.
撰写医疗文书对医护人员而言是一项繁琐且耗时的任务。与此同时，医疗文档中的错误屡见不鲜 [20,21]。在医患之间准确记录并交换临床信息至关重要。医疗文档需要极高的精确度，因此记录者必须能够完整捕捉并准确记载问诊过程中讨论的所有医疗信息。ChatGPT已被证明是医疗文档记录的有效工具 [13,22]。将其作为语言助手或模板生成器使用，可显著减少临床医生的文书时间并提升记录准确性 [2]。以下四个小节将具体展示ChatGPT的高效应用场景，包括生成患者门诊信函、放射学报告、医疗记录和出院小结，这些应用证明了其简化医疗文书流程、提升临床工作效率的潜力。
Patient Clinic Letters
患者临床信函
Using skin cancer as an example, Ali et al [14] evaluated the readability, factual accuracy, and humanization of clinical letters to patients generated by ChatGPT. Of the 38 hypothetical clinical scenarios created, 7 involved basal cell carcinoma, 11 to squamous cell carcinoma, and 20 to malignant melanoma. The overall median accuracy of the clinical information in the letter was 7 (range 1-9). The overall median humanness of the writing style was 7 (5-9). The weighting for accuracy κ was 0.80 $(P{<}.001)$ and for humanness 0.77 $(P{<}.001)$ . This assessment demonstrates that ChatGPT can generate clinical letters with high overall accuracy and humanization. In addition, the reading level of these letters is generally similar to that of letters currently generated by doctors.
以皮肤癌为例，Ali等[14]评估了ChatGPT生成的患者临床信函的可读性、事实准确性和人性化程度。在创建的38个假设临床场景中，7个涉及基底细胞癌，11个涉及鳞状细胞癌，20个涉及恶性黑色素瘤。信函中临床信息的总体准确度中位数为7（范围1-9）。写作风格的总体人性化中位数为7（5-9）。准确性权重κ为0.80 $(P{<}.001)$，人性化权重为0.77 $(P{<}.001)$。该评估表明，ChatGPT能够生成具有较高整体准确性和人性化的临床信函。此外，这些信函的阅读水平通常与医生当前生成的信函相似。
Radiology Reports
放射学报告
Jeblick et al [15] investigated 15 radiologists to assess the quality of the ChatGPT simplified radiology reports. Of all the ratings, $75%$ were “agree” or “strongly agree” $_ {(\mathrm{Q}3=2)}$ and none chose “strongly disagree.” Most radiologists felt that the simplified reports were accurate and complete and that there was no potential harm to patients. The initial results of this study indicate that there is great potential to use ChatGPT to improve patient-centered care in radiology.
Jeblick等人[15]调查了15名放射科医生，以评估ChatGPT简化放射学报告的质量。在所有评分中，$75%$为"同意"或"强烈同意"$_ {(\mathrm{Q}3=2)}$，无人选择"强烈不同意"。多数放射科医生认为简化报告准确完整，且不会对患者造成潜在伤害。该研究的初步结果表明，使用ChatGPT改善以患者为中心的放射学护理具有巨大潜力。
Medical Notes
医疗记录
ChatGPT helps doctors write medical notes. ChatGPT can write a structured medical note for a patient admitted to the intensive care unit, providing information about ongoing treatments, laboratory samples, blood gas analysis, and respiratory and he mo dynamic parameters. ChatGPT can correctly group most parameters into their appropriate sections, even if they are only in abbreviated form without any information about their meaning [16].
ChatGPT帮助医生撰写医疗记录。ChatGPT能为重症监护病房收治的患者编写结构化医疗记录，提供包括当前治疗方案、实验室样本、血气分析以及呼吸和血流动力学参数等信息。即使参数仅以缩写形式出现且未提供任何含义说明，ChatGPT也能将大多数参数正确归类到相应章节[16]。
Discharge Summaries
出院小结
Chin tag unt a et al [13] leveraged the variability in GPT-3 output by using ensembling and infusion of medical knowledge, enabling its use as an integral component of an effective low-shot learning method for medical sum mari z ation. GPT-3 takes as input a priming context for performing a task on a previously unseen example. Priming context refers to the textual description of a task and some demonstrations of task performance. These studies show that ChatGPT allows physicians to enter a brief description of the specific information to include, concepts to elaborate, and instructions to explain, and output a formal discharge summary in a matter of seconds (panel) [13,23]. ChatGPT can also improve the quality of the discharge summary itself [23].
Chin tag unt a等人[13]通过集成和医学知识注入的方式利用GPT-3输出的可变性，使其成为医疗摘要生成中有效的少样本学习方法的关键组成部分。GPT-3以任务启动上下文作为输入，用于在未见过的示例上执行任务。任务启动上下文指任务的文本描述以及一些任务执行示例。这些研究表明，ChatGPT允许医生输入简要描述，包括要包含的具体信息、需要详细阐述的概念以及解释说明，并在几秒钟内输出正式的出院摘要(panel)[13,23]。ChatGPT还可以提高出院摘要本身的质量[23]。
Future Research Directions
未来研究方向
Real-Time Monitoring and Predictive Analytics
实时监测与预测分析
Continuous monitoring of patient data, such as vital signs, laboratory results, and wearable device data, offers the opportunity for early detection of clinical deterioration and proactive intervention. Future research could explore how ChatGPT can analyze and interpret these real-time data streams, identifying patterns, trends, and abnormal changes. ChatGPT can provide timely alerts, risk assessment, and predictive analytics that enable health care professionals to intervene early and prevent adverse events when integrated into a monitoring system.
持续监测患者数据（如生命体征、实验室结果和可穿戴设备数据）为早期发现临床恶化并主动干预提供了机会。未来研究可探索ChatGPT如何分析和解读这些实时数据流，识别模式、趋势及异常变化。当ChatGPT集成到监测系统中时，它能提供及时警报、风险评估和预测分析，使医疗专业人员能够及早干预并预防不良事件。
Precision Medicine and Personalized Treatment
精准医疗与个性化治疗
ChatGPT can analyze patient-specific data, including genetic information, biomarkers, and treatment history, to generate tailored treatment recommendations and predict individual responses to therapies. ChatGPT can help physicians and patients by analyzing complex data sets and generating personalized treatment recommendations. Further research could focus on developing ChatGPT models that use large-scale genomic and clinical data to provide more accurate predictions of treatment outcomes, identify optimal therapeutic approaches, and assist in clinical trial matching for precision medicine initiatives.
ChatGPT能够分析患者特异性数据（包括遗传信息、生物标志物和治疗史），生成定制化治疗建议并预测个体对疗法的反应。通过分析复杂数据集和生成个性化治疗建议，ChatGPT可协助医生和患者。未来研究可聚焦于开发基于大规模基因组和临床数据的ChatGPT模型，以更精准预测治疗结果、确定最佳治疗方案，并支持精准医学项目的临床试验匹配。
Tele medicine and Remote Health Care
远程医疗与远程健康护理
As tele medicine and telehealth continue to evolve, ChatGPT’s role in facilitating virtual patient-physician interactions could be explored. It may involve the development of ChatGPT-based virtual assistants that can assist health care professionals in triaging patients, providing initial assessments, and providing remote guidance for home care. In addition, ChatGPT could be trained to solve patient problems, provide health education, and support self-care at home. ChatGPT could play an important role in facilitating virtual doctor-patient interactions by providing virtual assistance and remote guidance.
随着远程医疗和远程健康服务的持续发展，可以探索ChatGPT在促进虚拟医患互动中的作用。这可能涉及开发基于ChatGPT的虚拟助手，协助医疗专业人员进行患者分诊、提供初步评估以及远程居家护理指导。此外，ChatGPT可被训练用于解决患者问题、提供健康教育并支持居家自我护理。通过提供虚拟协助和远程指导，ChatGPT能在促进虚拟医患互动中发挥重要作用。
Integration With Existing Health Care Systems
与现有医疗系统的整合
Seamless integration of ChatGPT into existing clinical workflow and EHR systems is essential for its effective use in health care settings. Research should focus on developing standards and protocols for interoperability, data exchange, and secure communication between ChatGPT and EHR systems. It would enable the efficient use of ChatGPT in real-time CDS and documentation. ChatGPT can be used to improve the efficiency and accuracy of extracting information from unstructured clinical notes and EHRs. Future research can explore the integration of ChatGPT into EHR systems to enable intelligent data extraction, sum mari z ation, and analysis to support clinical research, quality improvement initiatives, and evidence-based practice.
将ChatGPT无缝集成到现有临床工作流程和电子健康记录(EHR)系统中对其在医疗环境中的有效应用至关重要。研究应侧重于制定ChatGPT与EHR系统之间互操作性、数据交换和安全通信的标准与协议，这将有助于在实时临床决策支持(CDS)和文档记录中高效利用ChatGPT。该技术可用于提升从非结构化临床记录和EHR中提取信息的效率与准确性。未来研究可探索将ChatGPT集成至EHR系统，实现智能数据提取、汇总和分析，以支持临床研究、质量改进计划及循证实践。
Possible Risks and Challenges of Using ChatGPT
使用ChatGPT的潜在风险与挑战
Despite the excellent results of ChatGPT in evaluation studies of its use in clinical practice, the potential negative effects should not be underestimated, including privacy, ethics, bias, and discrimination. ChatGPT can lead to intentional and unintentional misuse of various applications [16]. While not all of the proposed fraudulent uses are unique to ChatGPT, what is impressive is the effective acceleration of ChatGPT in creating false evidence and material with a high degree of plausibility [16]. ChatGPT may create hallucinations or false information. “Hallucination” refers to the fact that the content generated by the model is not based on reality, creating a completely fabricated story or fact [24]. Another concern is that ChatGPT can reproduce the biases present in the data on which it is trained [16]. In the health care field, the accuracy of information is crucial, and the presence of errors or inaccuracies in information is terrifying. To ensure the safe and reliable use of ChatGPT, a rigorous human review process and human involvement in the workflow are essential. Adherence to relevant standards and criteria, such as accuracy, reliability, interpret ability, explain ability, and user acceptance benchmarks, is necessary. It is imperative to explore existing frameworks and guidelines for evaluating AI systems in health care, developed by regulatory bodies or professional organizations, and implement them for ChatGPT. Validating ChatGPT against these benchmarks is vital to guarantee its safety and effectiveness in clinical practice.
尽管ChatGPT在临床应用评估研究中表现优异，但其潜在负面影响不容忽视，包括隐私、伦理、偏见和歧视等问题。ChatGPT可能导致各类应用场景的有意或无意滥用[16]。虽然并非所有欺诈性用途都专属于ChatGPT，但其在生成高度可信的虚假证据和材料方面展现出的加速效应令人震惊[16]。ChatGPT可能产生幻觉(hallucination)或虚假信息。"幻觉"指模型生成内容脱离现实依据，完全虚构故事或事实的现象[24]。另一重担忧是ChatGPT会复现训练数据中存在的偏见[16]。在医疗健康领域，信息准确性至关重要，存在错误或不准确信息将造成严重后果。为确保ChatGPT安全可靠地使用，必须建立严格的人工审核流程并保持人类参与工作流。需遵循准确性、可靠性、可解释性、用户接受度等基准标准。当务之急是探索监管机构或专业组织制定的现有医疗AI系统评估框架与指南，并将其应用于ChatGPT。根据这些基准验证ChatGPT对保障其临床应用的安全性与有效性至关重要。
Security measures must be taken to safeguard patient information while using ChatGPT, including encryption, access control, secure data storage, and compliance with privacy regulations. Patient data used for training and fine-tuning ChatGPT should be anonymized to protect privacy, and obtaining patient consent for data use during ChatGPT’s development and deployment is of utmost importance. Efforts should be made to mitigate re identification risks and prevent the linkage of de identified patient data to identifiable information. Documenting and monitoring system activities are crucial for accountability and audit ability. A proactive approach is necessary to ensure ongoing patient privacy and data protection. Compliance with relevant laws, regulations, and guidelines, such as data protection regulations, patient privacy laws, and health care regulations specific to AI technology, should be considered. The impact of compliance on ChatGPT’s clinical integration and the necessary steps to ensure adherence to legal and ethical standards should be addressed.
在使用ChatGPT时必须采取安全措施保护患者信息，包括加密、访问控制、安全数据存储以及遵守隐私法规。用于训练和微调ChatGPT的患者数据应进行匿名化处理以保护隐私，且在ChatGPT开发和部署过程中获取患者对数据使用的同意至关重要。需努力降低重新识别风险，并防止去标识化患者数据与可识别信息关联。记录和监控系统活动对责任追溯与审计能力极为关键。必须采取主动措施确保持续的患者隐私和数据保护。应遵守相关法律法规及指南，如数据保护条例、患者隐私法以及针对AI技术的医疗法规。需评估合规性对ChatGPT临床整合的影响，并采取必要步骤以确保符合法律与伦理标准。
While ChatGPT shows promise and has the potential to revolutionize the clinical practice paradigm, several barriers hinder its clinical application. First, it lacks the medical expertise and background required to comprehend complex relationships between conditions and treatments, as it is not specifically designed to answer medical questions. Therefore, the quality of recommendations generated by ChatGPT needs assessment from a clinical expert perspective, considering short-term and long-term impacts on clinical outcomes [5,16]. Second, ChatGPT’s training data is outdated and limited to information available up to September 2021 [25]. Given the rapid evolution of medical research and advancements, the lack of the latest information may impact its usability in clinical practice. Keeping ChatGPT’s training data up-to-date while ensuring data accuracy is crucial to address this limitation and enhance its use in clinical settings. Third, ChatGPT currently relies on manual input of information, necessitating future iterations to enable the automatic extraction of data from EHRs without the need for manual entry. However, managing patient data in this context presents significant challenges, as strict regulations must be in place to ensure patient privacy and prevent information misuse. Therefore, meticulous data storage and access management are essential [16].
虽然ChatGPT展现出潜力并有望彻底改变临床实践模式，但其临床应用仍存在多重障碍。首先，由于并非专为解答医学问题设计，它缺乏理解疾病与治疗间复杂关系所需的医学专业知识和背景。因此，需要从临床专家视角评估ChatGPT生成建议的质量，综合考虑其对临床结果的短期与长期影响 [5,16]。其次，ChatGPT的训练数据截至2021年9月 [25]，在医学研究快速发展的背景下，信息滞后可能影响其临床实用性。保持训练数据时效性与准确性对突破此限制至关重要。第三，当前ChatGPT依赖人工输入信息，未来需实现从电子健康记录(EHRs)自动提取数据的功能。但此类患者数据管理面临重大挑战，必须建立严格规范以确保患者隐私并防止信息滥用 [16]。
In conclusion, we must be cautious and proactive in addressing potential risks when using ChatGPT to ensure the safety and quality of patient care. With a clear understanding of the capabilities and limitations of ChatGPT, researchers and practitioners can effectively use the technology while avoiding any unintended consequences. Regardless of our attitude toward ChatGPT, the development of AI is unstoppable. The wisest course of action is to embrace it and use its capabilities to improve human health care.
总之，我们必须谨慎而积极地应对使用ChatGPT时的潜在风险，以确保患者护理的安全与质量。通过清晰理解ChatGPT的能力与局限，研究人员和从业者可以高效运用该技术，同时避免意外后果。无论我们对ChatGPT持何种态度，人工智能的发展势不可挡。最明智的做法是接纳它，并利用其能力改善人类医疗健康服务。
Acknowledgments
致谢
We did not use any artificial intelligence techniques to write the article.
我们没有使用任何人工智能技术来撰写这篇文章。
Authors' Contributions
作者贡献
JL and SL reviewed the literature and drafted and revised the manuscript. CW provided critical input, discussion, and revision of the manuscript. All authors read and approved the final manuscript.
JL和SL查阅文献并起草和修订了手稿。CW提供了关键意见、讨论和手稿修订。所有作者阅读并批准了最终手稿。
Conflicts of Interest
利益冲突
None declared.
无利益冲突声明。
Multimedia Appendix 1
多媒体附录 1
ChatGPT in clinical practice. [DOCX File , 35 KB-Multimedia Appendix 1]
ChatGPT在临床实践中的应用 [DOCX文件, 35 KB-多媒体附录1]
References
参考文献
Abbreviations
缩写
AI: artificial intelligence CDS: clinical decision support EHR: electronic health record HCC: hepatocellular carcinoma MSD: Merck Sharp & Dohme NCI: National Cancer Institute OE: open-ended SATA: select all that apply
AI: 人工智能
CDS: 临床决策支持
EHR: 电子健康记录
HCC: 肝细胞癌
MSD: 默沙东
NCI: 美国国家癌症研究所
OE: 开放式
SATA: 多选
©Jialin Liu, Changyu Wang, Siru Liu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.06.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creative commons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
©Jialin Liu, Changyu Wang, Siru Liu。本文首发于《医学互联网研究杂志》(https://www.jmir.org)，2023年6月28日。这是一篇遵循知识共享署名许可协议(https://creativecommons.org/licenses/by/4.0/)条款发布的开放获取文章，该许可允许在任何媒介上不受限制地使用、分发和复制，但须注明首次发表于《医学互联网研究杂志》的原创作品。必须包含完整的文献信息、原文链接(https://www.jmir.org/)以及上述版权和许可信息。
