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Use of the i2b2 research query tool to conduct a matched case–control clinical research study: advantages, disadvantages and methodological considerations

机译:使用i2b2研究查询工具进行匹配的病例对照临床研究:优缺点和方法学考虑

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Background A major aim of the i2b2 (informatics for integrating biology and the bedside) clinical data informatics framework aims to create an efficient structure within which patients can be identified for clinical and translational research projects. Our objective was to describe the respective roles of the i2b2 research query tool and the electronic medical record (EMR) in conducting a case-controlled clinical study at our institution. Methods We analyzed the process of using i2b2 and the EMR together to generate a complete research database for a case–control study that sought to examine risk factors for kidney stones among gastrostomy tube (G-tube) fed children. Results Our final case cohort consisted of 41/177 (23%) of potential cases initially identified by i2b2, who were matched with 80/486 (17%) of potential controls. Cases were 10 times more likely to be excluded for inaccurate coding regarding stones vs. inaccurate coding regarding G-tubes. A majority (67%) of cases were excluded due to not meeting clinical inclusion criteria, whereas a majority of control exclusions (72%) occurred due to inadequate clinical data necessary for study completion. Full dataset assembly required complementary information from i2b2 and the EMR. Conclusions i2b2 was critical as a query analysis tool for patient identification in our case–control study. Patient identification via procedural coding appeared more accurate compared with diagnosis coding. Completion of our investigation required iterative interplay of i2b2 and the EMR to assemble the study cohort.
机译:背景技术i2b2(用于整合生物学和床边信息的信息学)临床数据信息学框架的主要目标是创建一个有效的结构,在该结构中可以识别患者以进行临床和转化研究项目。我们的目的是描述i2b2研究查询工具和电子病历(EMR)在我们机构进行病例对照临床研究中的各自作用。方法我们分析了一起使用i2b2和EMR的过程,以生成一个病例对照研究的完整研究数据库,该研究旨在检查喂养胃造口管(G-tube)的儿童肾结石的危险因素。结果我们的最终病例队列由i2b2最初识别的41/177(23%)潜在病例组成,与80/486(17%)的潜在对照匹配。因结石的编码不正确而与G管的编码不正确相比,排除病例的可能性要高10倍。大多数病例(67%)由于未达到临床纳入标准而被排除在外,而多数对照排除(72%)由于研究完成所需的临床数据不足而发生。完整的数据集组装需要来自i2b2和EMR的补充信息。结论在我们的病例对照研究中,i2b2作为用于患者识别的查询分析工具至关重要。与诊断编码相比,通过程序编码进行的患者识别更为准确。要完成我们的研究,需要i2b2和EMR的迭代相互作用来组建研究队列。

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