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美国退伍军人事务部电子健康记录肺功能测试数据提取工具的开发与验证

Development and validation of a pulmonary function test data extraction tool for the US department of veterans affairs electronic health record.

作者信息

Rabin Alexander S, Weinstein Julien B, Seelye Sarah M, Whittington Taylor N, Hogan Cainnear K, Prescott Hallie C

机构信息

Pulmonary Section, Veterans Affairs Ann Arbor Healthcare System, 2215 Fuller Road, 48105, Ann Arbor, MI, USA.

Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA.

出版信息

BMC Res Notes. 2024 Apr 23;17(1):115. doi: 10.1186/s13104-024-06770-3.

Abstract

OBJECTIVE

Pulmonary function test (PFT) results are recorded variably across hospitals in the Department of Veterans Affairs (VA) electronic health record (EHR), using both unstructured and semi-structured notes. We developed and validated a hospital-specific code to extract pre-bronchodilator measures of obstruction (ratio of forced expiratory volume in one second [FEV] to forced vital capacity [FVC]) and severity of obstruction (percent predicted of FEV).

RESULTS

Among 36 VA facilities with the most PFTs completed between 2018 and 2022 from a parent cohort of veterans receiving long-acting controller inhalers, 12 had a consistent syntactical convention or template for reporting PFT data in the EHR. Of the 42,718 PFTs identified from these 12 facilities, the hospital-specific text processing pipeline yielded 24,860 values for the FEV:FVC ratio and 23,729 values for FEV. A ratio of FEV:FVC less than 0.7 was identified in 17,615 of 24,922 studies (70.7%); 8864 of 24,922 (35.6%) had a severe or very severe reduction in FEV (< 50% of the predicted value). Among 100 randomly selected PFT reports reviewed by two pulmonary physicians, the coding solution correctly identified the presence of obstruction in 99 out of 100 studies and the degree of obstruction in 96 out of 100 studies.

摘要

目的

在退伍军人事务部(VA)电子健康记录(EHR)中,各医院对肺功能测试(PFT)结果的记录方式各不相同,使用的既有非结构化笔记,也有半结构化笔记。我们开发并验证了一种特定于医院的代码,用于提取支气管扩张剂使用前的阻塞测量值(一秒用力呼气量[FEV]与用力肺活量[FVC]的比值)和阻塞严重程度(FEV的预测百分比)。

结果

在2018年至2022年期间,从接受长效控制吸入器的退伍军人母队列中完成PFT最多的36家VA医疗机构中,有12家在EHR中报告PFT数据时有一致的句法惯例或模板。从这12家机构中识别出的42718次PFT中,特定于医院的文本处理流程得出FEV:FVC比值的24860个值和FEV的23729个值。在24922项研究中的17615项(70.7%)中,FEV:FVC比值小于0.7;在24922项中的8864项(35.6%)中,FEV有严重或非常严重的降低(<预测值的50%)。在由两位肺科医生审查的100份随机选择的PFT报告中,编码解决方案在100项研究中的99项中正确识别出阻塞的存在,在100项研究中的96项中正确识别出阻塞的程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/11040816/7b0a456c1111/13104_2024_6770_Fig1_HTML.jpg

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