Solmonovich Rachel L, Kouba Insaf, Quezada Oscar, Rodriguez-Ayala Gianni, Rojas Veronica, Bonilla Kevin, Espino Kevin, Bracero Luis A
Northwell, New Hyde Park, NY (Solmonovich, Kouba, Quezada, Rodriguez-Ayala, Rojas, Bonilla, Espino, and Bracero).
Department of Obstetrics and Gynecology, South Shore University Hospital, Bay Shore, NY (Solmonovich, Kouba, Rojas, Bonilla, Espino, and Bracero).
AJOG Glob Rep. 2024 Sep 19;4(4):100400. doi: 10.1016/j.xagr.2024.100400. eCollection 2024 Nov.
Effective patient counseling in Obstetrics and gynecology is vital. Existing language barriers between Spanish-speaking patients and English-speaking providers may negatively impact patient understanding and adherence to medical recommendations, as language discordance between provider and patient has been associated with medication noncompliance, adverse drug events, and underuse of preventative care. Artificial intelligence large language models may be a helpful adjunct to patient care by generating counseling templates in Spanish.
The primary objective was to determine if large language models can generate proficient counseling templates in Spanish on obstetric and gynecology topics. Secondary objectives were to (1) compare the content, quality, and comprehensiveness of generated templates between different large language models, (2) compare the proficiency ratings among the large language model generated templates, and (3) assess which generated templates had potential for integration into clinical practice.
Cross-sectional study using free open-access large language models to generate counseling templates in Spanish on select obstetrics and gynecology topics. Native Spanish-speaking practicing obstetricians and gynecologists, who were blinded to the source large language model for each template, reviewed and subjectively scored each template on its content, quality, and comprehensiveness and considered it for integration into clinical practice. Proficiency ratings were calculated as a composite score of content, quality, and comprehensiveness. A score of >4 was considered proficient. Basic inferential statistics were performed.
All artificial intelligence large language models generated proficient obstetrics and gynecology counseling templates in Spanish, with Google Bard generating the most proficient template (p<0.0001) and outperforming the others in comprehensiveness (=.03), quality (=.04), and content (=.01). Microsoft Bing received the lowest scores in these domains. Physicians were likely to be willing to incorporate the templates into clinical practice, with no significant discrepancy in the likelihood of integration based on the source large language model (=.45).
Large language models have potential to generate proficient obstetrics and gynecology counseling templates in Spanish, which physicians would integrate into their clinical practice. Google Bard scored the highest across all attributes. There is an opportunity to use large language models to try to mitigate the language barriers in health care. Future studies should assess patient satisfaction, understanding, and adherence to clinical plans following receipt of these counseling templates.
妇产科有效的患者咨询至关重要。说西班牙语的患者与说英语的医护人员之间存在的语言障碍可能会对患者对医疗建议的理解和依从性产生负面影响，因为医护人员与患者之间的语言不一致与用药不依从、药物不良事件以及预防保健利用不足有关。人工智能大语言模型通过生成西班牙语的咨询模板可能会成为患者护理的有益辅助工具。
主要目的是确定大语言模型是否能够生成关于妇产科主题的熟练的西班牙语咨询模板。次要目的是：（1）比较不同大语言模型生成的模板在内容、质量和全面性方面的差异；（2）比较大语言模型生成的模板之间的熟练程度评分；（3）评估哪些生成的模板具有整合到临床实践中的潜力。
横断面研究，使用免费的开放获取大语言模型生成关于选定妇产科主题的西班牙语咨询模板。以西班牙语为母语的执业妇产科医生对每个模板的源大语言模型不知情，对每个模板的内容、质量和全面性进行审查并主观评分，并考虑将其整合到临床实践中。熟练程度评分计算为内容、质量和全面性的综合得分。得分>4被认为是熟练的。进行了基本的推断统计。
所有人工智能大语言模型都生成了熟练的西班牙语妇产科咨询模板。谷歌巴德生成的模板最熟练（p<0.0001），在全面性（=0.03）、质量（=0.04）和内容（=0.01）方面优于其他模型。微软必应在这些领域得分最低。医生可能愿意将这些模板整合到临床实践中，基于源大语言模型的整合可能性没有显著差异（=0.45）。
大语言模型有潜力生成熟练的西班牙语妇产科咨询模板，医生会将其整合到临床实践中。谷歌巴德在所有属性上得分最高。有机会利用大语言模型来试图减轻医疗保健中的语言障碍。未来的研究应评估患者在收到这些咨询模板后对临床计划的满意度、理解度和依从性。
