Background: A major aim of the i2b2 (informatics for integrating biology and the bedside) clinical data informatics\r\nframework aims to create an efficient structure within which patients can be identified for clinical and translational\r\nresearch projects.\r\nOur objective was to describe the respective roles of the i2b2 research query tool and the electronic medical\r\nrecord (EMR) in conducting a case-controlled clinical study at our institution.\r\nMethods: We analyzed the process of using i2b2 and the EMR together to generate a complete research database\r\nfor a caseââ?¬â??control study that sought to examine risk factors for kidney stones among gastrostomy tube (G-tube) fed\r\nchildren.\r\nResults: Our final case cohort consisted of 41/177 (23%) of potential cases initially identified by i2b2, who were\r\nmatched with 80/486 (17%) of potential controls. Cases were 10 times more likely to be excluded for inaccurate\r\ncoding regarding stones vs. inaccurate coding regarding G-tubes. A majority (67%) of cases were excluded due to\r\nnot meeting clinical inclusion criteria, whereas a majority of control exclusions (72%) occurred due to inadequate\r\nclinical data necessary for study completion. Full dataset assembly required complementary information from i2b2\r\nand the EMR.\r\nConclusions: i2b2 was critical as a query analysis tool for patient identification in our caseââ?¬â??control study. Patient\r\nidentification via procedural coding appeared more accurate compared with diagnosis coding. Completion of our\r\ninvestigation required iterative interplay of i2b2 and the EMR to assemble the study cohort.
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