Jin Haijiao, Guo Jinglu, Lin Qisheng, Wu Shaun, Hu Weiguo, Li Xiaoyang
Department of Nephrology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Nephrology, Ningbo Hangzhou Bay Hospital, Zhejiang, China.
Front Digit Health. 2024 Dec 5;6:1456911. doi: 10.3389/fdgth.2024.1456911. eCollection 2024.
The rapid development of artificial intelligence (AI) has shown great potential in medical document generation. This study aims to evaluate the performance of Claude 3.5-Sonnet, an advanced AI model, in generating discharge summaries for patients with renal insufficiency, compared to human physicians.
A prospective, comparative study was conducted involving 100 patients (50 with acute kidney injury and 50 with chronic kidney disease) from the nephrology department of Ningbo Hangzhou Bay Hospital between January and June 2024. Discharge summaries were independently generated by Claude 3.5-Sonnet and human physicians. The main evaluation indicators included accuracy, generation time, and overall quality.
Claude 3.5-Sonnet demonstrated comparable accuracy to human physicians in generating discharge summaries for both AKI (90 vs. 92 points, > 0.05) and CKD patients (88 vs. 90 points, > 0.05). The AI model significantly outperformed human physicians in terms of efficiency, requiring only about 30 s to generate a summary compared to over 15 min for physicians ( < 0.001). The overall quality scores showed no significant difference between AI-generated and physician-written summaries for both AKI (26 vs. 27 points, > 0.05) and CKD patients (25 vs. 26 points, > 0.05).
Claude 3.5-Sonnet demonstrates high efficiency and reliability in generating discharge summaries for patients with renal insufficiency, with accuracy and quality comparable to those of human physicians. These findings suggest that AI has significant potential to improve the efficiency of medical documentation, though further research is needed to optimize its integration into clinical practice and address ethical and privacy concerns.
人工智能(AI)的快速发展在医学文档生成方面展现出了巨大潜力。本研究旨在评估先进的AI模型Claude 3.5-Sonnet在为肾功能不全患者生成出院小结方面相对于人类医生的表现。
于2024年1月至6月在宁波杭州湾医院肾内科对100例患者(50例急性肾损伤患者和50例慢性肾脏病患者)进行了一项前瞻性比较研究。出院小结由Claude 3.5-Sonnet和人类医生独立生成。主要评估指标包括准确性、生成时间和整体质量。
Claude 3.5-Sonnet在为急性肾损伤(AKI)患者(90分对92分,>0.05)和慢性肾脏病(CKD)患者生成出院小结时,与人类医生的准确性相当。该AI模型在效率方面显著优于人类医生,生成一份小结仅需约30秒,而医生则需要超过15分钟(<0.001)。对于AKI患者(26分对27分,>0.05)和CKD患者(25分对26分,>0.05),AI生成的小结与医生撰写的小结在整体质量得分上无显著差异。
Claude 3.5-Sonnet在为肾功能不全患者生成出院小结方面展现出了高效率和可靠性,准确性和质量与人类医生相当。这些发现表明,AI在提高医学文档效率方面具有巨大潜力,不过还需要进一步研究以优化其在临床实践中的整合并解决伦理和隐私问题。