TY -非盟的公园,Eunsoo H AU -沃森,汉娜我非盟——Mehendale,费利西蒂V AU -奥尼尔,艾莉森问PY - 2022 DA - 2022/10/26 TI -评估对临床任务效率的影响自然语言处理算法搜索医疗文档:潜在的交叉研究乔-地中海JMIR通知SP - e39616六世- 10 - 10 KW -临床决策支持KW -电子健康记录KW -自然语言处理KW -语义搜索KW -临床信息学AB -背景:从电子健康记录(EHRs)中的自由文本中检索信息(IR)既耗时又复杂。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高效，减少临床医生的认知负荷。目的:本研究旨在评估三个级别的搜索功能(无搜索、字符串搜索和nlp增强搜索)在模拟临床环境中支持临床用户从电子病历文件的自由文本中进行IR的功效。方法:通过上传3组患者笔记到EHR研究软件应用程序，并将其与3个相应的IR任务一起呈现，模拟临床环境。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，共招募3组评估者，分别为医生(n=19)和医学生(n=16)。评估员按照他们随机分配的小组的顺序使用每个搜索功能执行3个任务。测量和分析任务完成的速度和准确性，并在反馈调查中回顾了用户对nlp增强搜索的看法。结果:与字符串搜索相比，nlp增强搜索能更准确地完成任务(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. SN - 2291-9694 UR - https://medinform.www.mybigtv.com/2022/10/e39616 UR - https://doi.org/10.2196/39616 UR - http://www.ncbi.nlm.nih.gov/pubmed/36287591 DO - 10.2196/39616 ID - info:doi/10.2196/39616 ER -