The promise and challenges of ChatGPT in community pharmacy: A comparative analysis of response accuracy

Ali H. Salama
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Abstract

This study evaluates ChatGPT, an AI-based language model, in addressing common pharmacist inquiries in community pharmacies. The assessment encompasses Drug-Drug Interactions, Adverse Drug Effects, Drug Dosage, and Alternative Therapies, each comprising 20 questions, totaling 80 questions. Responses from ChatGPT were compared against standard answers, generating textual and chart scores. Textual score was computed by relating correct answers to the total questions within each category, while chart score involved the total correct answers multiplied by the chart-type questions. ChatGPT exhibited distinct performance rates: 30% for Drug-Drug Interactions, 65% for Adverse Drug Effects, 35% for Drug Dosage, and an impressive 85% for Alternative Therapies. While Alternative Therapies displayed high accuracy, challenges arose in accurately addressing Drug Dosage and Drug-Drug Interactions. Conclusion: The study underscores the complexity of pharmacy-related inquiries and the necessity for AI model enhancement. Despite promising accuracy in certain categories, like Alternative Therapies, improvements are crucial for Drug Dosage and Drug-Drug Interactions. The findings emphasize the need for ongoing AI model development to optimize integration into community pharmacy settings.
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社区药房使用 ChatGPT 的前景与挑战:回复准确性比较分析
本研究评估了基于人工智能的语言模型 ChatGPT 在解决社区药房药剂师常见咨询方面的效果。评估内容包括药物相互作用、药物不良反应、药物剂量和替代疗法,每项包括 20 个问题,共 80 个问题。将 ChatGPT 的回答与标准答案进行比较,得出文字和图表分数。文字分数是将正确答案与每个类别中的问题总数联系起来计算的,而图表分数则是正确答案总数乘以图表类型的问题。ChatGPT 显示了不同的成绩率:药物相互作用的正确率为 30%,药物不良反应的正确率为 65%,药物剂量的正确率为 35%,而替代疗法的正确率则高达 85%。虽然替代疗法的准确率很高,但在准确处理药物剂量和药物相互作用方面却存在挑战。结论这项研究强调了药学相关查询的复杂性和增强人工智能模型的必要性。尽管某些类别(如替代疗法)的准确性很高,但改进药物剂量和药物间相互作用的准确性至关重要。研究结果强调了持续开发人工智能模型的必要性,以优化与社区药房环境的整合。
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