Evaluation of ChatGPT as a Tool for Answering Clinical Questions in Pharmacy Practice.

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-12-01 Epub Date: 2024-05-22 DOI:10.1177/08971900241256731
Faria Munir, Anna Gehres, David Wai, Leah Song
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Abstract

Background: In the healthcare field, there has been a growing interest in using artificial intelligence (AI)-powered tools to assist healthcare professionals, including pharmacists, in their daily tasks. Objectives: To provide commentary and insight into the potential for generative AI language models such as ChatGPT as a tool for answering practice-based, clinical questions and the challenges that need to be addressed before implementation in pharmacy practice settings. Methods: To assess ChatGPT, pharmacy-based questions were prompted to ChatGPT (Version 3.5; free version) and responses were recorded. Question types included 6 drug information questions, 6 enhanced prompt drug information questions, 5 patient case questions, 5 calculations questions, and 10 drug knowledge questions (e.g., top 200 drugs). After all responses were collected, ChatGPT responses were assessed for appropriateness. Results: ChatGPT responses were generated from 32 questions in 5 categories and evaluated on a total of 44 possible points. Among all ChatGPT responses and categories, the overall score was 21 of 44 points (47.73%). ChatGPT scored higher in pharmacy calculation (100%), drug information (83%), and top 200 drugs (80%) categories and lower in drug information enhanced prompt (33%) and patient case (20%) categories. Conclusion: This study suggests that ChatGPT has limited success as a tool to answer pharmacy-based questions. ChatGPT scored higher in calculation and multiple-choice questions but scored lower in drug information and patient case questions, generating misleading or fictional answers and citations.

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将 ChatGPT 作为药学实践中回答临床问题的工具进行评估。
背景:在医疗保健领域,人们对使用人工智能(AI)驱动的工具来协助包括药剂师在内的医疗保健专业人员完成日常工作越来越感兴趣。研究目的对生成式人工智能语言模型(如 ChatGPT)作为回答基于实践的临床问题的工具的潜力以及在药学实践环境中实施前需要应对的挑战进行评论和深入探讨。方法:为了评估 ChatGPT,我们向 ChatGPT(3.5 版;免费版)提示了基于药学的问题并记录了回复。问题类型包括 6 个药物信息问题、6 个增强型药物信息提示问题、5 个患者案例问题、5 个计算问题和 10 个药物知识问题(如前 200 种药物)。收集完所有回答后,对 ChatGPT 回答的适当性进行评估。结果:从 5 个类别的 32 个问题中生成了 ChatGPT 回答,并对总共 44 个可能的点数进行了评估。在所有 ChatGPT 回答和类别中,总分为 44 分中的 21 分(47.73%)。ChatGPT 在药房计算(100%)、药品信息(83%)和前 200 种药品(80%)类别中得分较高,而在药品信息增强提示(33%)和患者病例(20%)类别中得分较低。结论本研究表明,ChatGPT 作为回答药学问题的工具取得的成功有限。ChatGPT 在计算题和多项选择题中得分较高,但在药物信息题和病例题中得分较低,会产生误导或虚构的答案和引文。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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