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翻译失误:诊断记录显示肿瘤护理电子健康记录活检后存在更多不准确之处。

Lost in Translation: Diagnosis Records Show More Inaccuracies After Biopsy in Oncology Care EHRs.

作者信息

Diaz-Garelli Jose-Franck, Strowd Roy, Wells Brian J, Ahmed Tamjeed, Merrill Rebecca, Topaloglu Umit

机构信息

Wake Forest Baptist Medical Center, Winston Salem, NC.

出版信息

AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:325-334. eCollection 2019.

Abstract

The use of diagnosis (DX) data is crucial to secondary use of electronic health record (EHR) data, yet accessible structured DX data often lack in accuracy. DX descriptions associated with structured DX codes vary even after recording biopsy results; this may indicate poor data quality. We hypothesized that biopsy reports in cancer care charts do not improve intrinsic DX data quality. We analyzed DX data for a manually well-annotated cohort of patients with brain neoplasms. We built statistical models to predict the number of fully-accurate (i.e., correct neoplasm type and anatomical location) and inaccurate DX (i.e. type or location contradicts cohort data) descriptions. We found some evidence of statistically larger numbers of fully-accurate (RR=3.07, p=0.030) but stronger evidence of much larger numbers of inaccurate DX (RR=12.3, p=0.001 and RR=19.6, p<0.0001) after biopsy result recording. Still, 65.9% of all DX records were neither fully-accurate nor fully-inaccurate. These results suggest EHRs must be modified to support more reliable DX data recording and secondary use of EHR data.

摘要

诊断(DX)数据的使用对于电子健康记录(EHR)数据的二次利用至关重要,但可获取的结构化DX数据往往缺乏准确性。即使在记录活检结果之后,与结构化DX代码相关的DX描述仍存在差异;这可能表明数据质量较差。我们推测癌症护理图表中的活检报告并不能提高内在DX数据的质量。我们分析了一组人工注释完善的脑肿瘤患者的DX数据。我们建立了统计模型来预测完全准确(即肿瘤类型和解剖位置正确)和不准确DX(即类型或位置与队列数据相矛盾)描述的数量。我们发现,在记录活检结果后,有一些证据表明完全准确的DX数量在统计学上更多(RR=3.07,p=0.030),但有更强的证据表明不准确DX的数量要多得多(RR=12.3,p=0.001和RR=19.6,p<0.0001)。尽管如此,所有DX记录中有65.9%既不是完全准确也不是完全不准确。这些结果表明,必须对电子健康记录进行修改,以支持更可靠的DX数据记录和电子健康记录数据的二次利用。

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