Performance Comparison of Junior Residents and ChatGPT in the Objective Structured Clinical Examination (OSCE) for Medical History Taking and Documentation of Medical Records: Development and Usability Study.
{"title":"Performance Comparison of Junior Residents and ChatGPT in the Objective Structured Clinical Examination (OSCE) for Medical History Taking and Documentation of Medical Records: Development and Usability Study.","authors":"Ting-Yun Huang, Pei Hsing Hsieh, Yung-Chun Chang","doi":"10.2196/59902","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study explores the cutting-edge abilities of large language models (LLMs) such as ChatGPT in medical history taking and medical record documentation, with a focus on their practical effectiveness in clinical settings-an area vital for the progress of medical artificial intelligence.</p><p><strong>Objective: </strong>Our aim was to assess the capability of ChatGPT versions 3.5 and 4.0 in performing medical history taking and medical record documentation in simulated clinical environments. The study compared the performance of nonmedical individuals using ChatGPT with that of junior medical residents.</p><p><strong>Methods: </strong>A simulation involving standardized patients was designed to mimic authentic medical history-taking interactions. Five nonmedical participants used ChatGPT versions 3.5 and 4.0 to conduct medical histories and document medical records, mirroring the tasks performed by 5 junior residents in identical scenarios. A total of 10 diverse scenarios were examined.</p><p><strong>Results: </strong>Evaluation of the medical documentation created by laypersons with ChatGPT assistance and those created by junior residents was conducted by 2 senior emergency physicians using audio recordings and the final medical records. The assessment used the Objective Structured Clinical Examination benchmarks in Taiwan as a reference. ChatGPT-4.0 exhibited substantial enhancements over its predecessor and met or exceeded the performance of human counterparts in terms of both checklist and global assessment scores. Although the overall quality of human consultations remained higher, ChatGPT-4.0's proficiency in medical documentation was notably promising.</p><p><strong>Conclusions: </strong>The performance of ChatGPT 4.0 was on par with that of human participants in Objective Structured Clinical Examination evaluations, signifying its potential in medical history and medical record documentation. Despite this, the superiority of human consultations in terms of quality was evident. The study underscores both the promise and the current limitations of LLMs in the realm of clinical practice.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"10 ","pages":"e59902"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612517/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Medical Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2196/59902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: This study explores the cutting-edge abilities of large language models (LLMs) such as ChatGPT in medical history taking and medical record documentation, with a focus on their practical effectiveness in clinical settings-an area vital for the progress of medical artificial intelligence.
Objective: Our aim was to assess the capability of ChatGPT versions 3.5 and 4.0 in performing medical history taking and medical record documentation in simulated clinical environments. The study compared the performance of nonmedical individuals using ChatGPT with that of junior medical residents.
Methods: A simulation involving standardized patients was designed to mimic authentic medical history-taking interactions. Five nonmedical participants used ChatGPT versions 3.5 and 4.0 to conduct medical histories and document medical records, mirroring the tasks performed by 5 junior residents in identical scenarios. A total of 10 diverse scenarios were examined.
Results: Evaluation of the medical documentation created by laypersons with ChatGPT assistance and those created by junior residents was conducted by 2 senior emergency physicians using audio recordings and the final medical records. The assessment used the Objective Structured Clinical Examination benchmarks in Taiwan as a reference. ChatGPT-4.0 exhibited substantial enhancements over its predecessor and met or exceeded the performance of human counterparts in terms of both checklist and global assessment scores. Although the overall quality of human consultations remained higher, ChatGPT-4.0's proficiency in medical documentation was notably promising.
Conclusions: The performance of ChatGPT 4.0 was on par with that of human participants in Objective Structured Clinical Examination evaluations, signifying its potential in medical history and medical record documentation. Despite this, the superiority of human consultations in terms of quality was evident. The study underscores both the promise and the current limitations of LLMs in the realm of clinical practice.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
