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搜索引擎中由人工智能驱动的聊天机器人:一项关于患者药物信息质量与风险的横断面研究。

Artificial intelligence-powered chatbots in search engines: a cross-sectional study on the quality and risks of drug information for patients.

作者信息

Andrikyan Wahram, Sametinger Sophie Marie, Kosfeld Frithjof, Jung-Poppe Lea, Fromm Martin F, Maas Renke, Nicolaus Hagen F

机构信息

Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

出版信息

BMJ Qual Saf. 2025 Jan 28;34(2):100-109. doi: 10.1136/bmjqs-2024-017476.

Abstract

BACKGROUND

Search engines often serve as a primary resource for patients to obtain drug information. However, the search engine market is rapidly changing due to the introduction of artificial intelligence (AI)-powered chatbots. The consequences for medication safety when patients interact with chatbots remain largely unexplored.

OBJECTIVE

To explore the quality and potential safety concerns of answers provided by an AI-powered chatbot integrated within a search engine.

METHODOLOGY

Bing copilot was queried on 10 frequently asked patient questions regarding the 50 most prescribed drugs in the US outpatient market. Patient questions covered drug indications, mechanisms of action, instructions for use, adverse drug reactions and contraindications. Readability of chatbot answers was assessed using the Flesch Reading Ease Score. Completeness and accuracy were evaluated based on corresponding patient drug information in the pharmaceutical encyclopaedia drugs.com. On a preselected subset of inaccurate chatbot answers, healthcare professionals evaluated likelihood and extent of possible harm if patients follow the chatbot's given recommendations.

RESULTS

Of 500 generated chatbot answers, overall readability implied that responses were difficult to read according to the Flesch Reading Ease Score. Overall median completeness and accuracy of chatbot answers were 100.0% (IQR 50.0-100.0%) and 100.0% (IQR 88.1-100.0%), respectively. Of the subset of 20 chatbot answers, experts found 66% (95% CI 50% to 85%) to be potentially harmful. 42% (95% CI 25% to 60%) of these 20 chatbot answers were found to potentially cause moderate to mild harm, and 22% (95% CI 10% to 40%) to cause severe harm or even death if patients follow the chatbot's advice.

CONCLUSIONS

AI-powered chatbots are capable of providing overall complete and accurate patient drug information. Yet, experts deemed a considerable number of answers incorrect or potentially harmful. Furthermore, complexity of chatbot answers may limit patient understanding. Hence, healthcare professionals should be cautious in recommending AI-powered search engines until more precise and reliable alternatives are available.

摘要

背景

搜索引擎常常是患者获取药物信息的主要资源。然而,由于引入了人工智能驱动的聊天机器人,搜索引擎市场正在迅速变化。患者与聊天机器人互动时对用药安全的影响在很大程度上仍未得到探索。

目的

探讨整合在搜索引擎中的人工智能驱动聊天机器人所提供答案的质量和潜在安全问题。

方法

针对美国门诊市场上最常用的50种药物,就患者10个常见问题对必应副驾驶进行查询。患者问题涵盖药物适应症、作用机制、使用说明、药物不良反应和禁忌症。使用弗莱什易读性分数评估聊天机器人答案的易读性。根据药品百科网站drugs.com上相应的患者药物信息评估完整性和准确性。对于预先选定的不准确的聊天机器人答案子集,医疗保健专业人员评估了如果患者遵循聊天机器人给出的建议可能造成伤害的可能性和程度。

结果

在生成的500个聊天机器人答案中,总体易读性表明根据弗莱什易读性分数,回复难以阅读。聊天机器人答案的总体中位数完整性和准确性分别为100.0%(四分位距50.0 - 100.0%)和100.0%(四分位距88.1 - 100.0%)。在20个聊天机器人答案子集中,专家发现66%(95%置信区间50%至85%)可能有害。如果患者遵循聊天机器人的建议,这20个聊天机器人答案中有42%(95%置信区间25%至60%)可能导致中度至轻度伤害,22%(95%置信区间10%至40%)可能导致严重伤害甚至死亡。

结论

人工智能驱动的聊天机器人能够提供总体完整且准确的患者药物信息。然而,专家认为相当数量的答案不正确或可能有害。此外,聊天机器人答案的复杂性可能会限制患者的理解。因此,在有更精确可靠的替代方案之前,医疗保健专业人员在推荐人工智能驱动的搜索引擎时应谨慎。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19d1/11874309/f9398eae5161/bmjqs-34-2-g001.jpg

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