%0期刊文章%@ 2291- 9694% I JMIR出版物%V 10卡塔尔世界杯8强波胆分析% N 10% P e39616% T评估用于搜索医疗文档的自然语言处理算法对临床任务效率的影响:前瞻性交叉研究%A Park,Eunsoo H %A Watson,Hannah I %A Mehendale,Felicity V %A O'Neil,Alison Q %A， +爱丁堡大学医学和兽医学院，爱丁堡大学，校长大楼，49小法兰西新月，爱丁堡，EH16 4SB，英国，44 1312426792，e.park-7@sms.ed.ac.uk %K临床决策支持%K电子健康记录%K自然语言处理%K语义搜索%K临床信息学%D 2022 %7 26.10.2022 %9原始论文%J JMIR Med Inform %G英文%X背景:从电子健康记录(EHRs)中的自由文本中检索信息(IR)耗时且复杂。我们假设，自然语言处理(NLP)增强的电子病历搜索功能可以使临床工作流程更有效，并减少临床医生的认知负荷。目的:本研究旨在评估3个级别的搜索功能(无搜索、字符串搜索和nlp增强搜索)在模拟临床环境中从电子病历文档的自由文本中支持临床用户IR的有效性。方法:通过将3组患者记录上传到EHR研究软件应用程序中，并将这些记录与3个相应的IR任务一起呈现，模拟了临床环境。任务包括多项选择题和自由文本题。采用前瞻性交叉研究设计，招募了3组评估者，其中包括医生(n=19)和医学生(n=16)。评估者按照随机分配的小组的顺序使用每个搜索功能执行这3个任务。测量和分析了任务完成的速度和准确性，并在反馈调查中审查了用户对nlp增强搜索的看法。 Results: NLP-enhanced search facilitated more accurate task completion than both string search (5.14%; P=.02) and no search (5.13%; P=.08). NLP-enhanced search and string search facilitated similar task speeds, both showing an increase in speed compared to the no search function, by 11.5% (P=.008) and 16.0% (P=.007) respectively. Overall, 93% of evaluators agreed that NLP-enhanced search would make clinical workflows more efficient than string search, with qualitative feedback reporting that NLP-enhanced search reduced cognitive load. Conclusions: To the best of our knowledge, this study is the largest evaluation to date of different search functionalities for supporting target clinical users in realistic clinical workflows, with a 3-way prospective crossover study design. NLP-enhanced search improved both accuracy and speed of clinical EHR IR tasks compared to browsing clinical notes without search. NLP-enhanced search improved accuracy and reduced the number of searches required for clinical EHR IR tasks compared to direct search term matching. %M 36287591 %R 10.2196/39616 %U https://medinform.www.mybigtv.com/2022/10/e39616 %U https://doi.org/10.2196/39616 %U http://www.ncbi.nlm.nih.gov/pubmed/36287591