Abstract

Utilization of informatics for integrating biology and the bedside to access preliminary outcome data of post-operative complication of spine surgery associated with diabetes mellitus

Author(s): Tomoko Tanaka, Abu Saleh Mohammad Mosa, N Scott Litofsky

Study Design: Retrospective

Study Objective: To evaluate the utility of Informatics for Integrating Biology and the Bedside database (i2b2) of University of Missouri in comparing post-operative outcomes after spinal surgery of patients with Diabetes Mellitus (DM) to those without.

Summary of background data: Studies in cardiovascular surgery, orthopedic surgery, and spine surgery have shown an association of poor preoperative hyperglycemia control with worse outcomes. However, the details of that association are not well described. Outcomes of spine surgery gleaned from nationwide databases are not universally available; some require significant costs, while others are not always available to all investigators. Informatics for Integrating Biology and the Bedside (i2b2) is a National Institutes of Health -sponsored National Center for Biomedical Computing developed for researchers to search electronic medical records for de-identified patient data to facilitate research investigations.

Methods: The Informatics for Integrating Biology and the Bedside (i2b2) database of University of Missouri was queried for various spine surgeries using categories of Non-DM patients, DM patients, and complications.

Results: Between Jan. 1, 2000 and Sept. 30, 2015 a total of 26009 spine surgeries were performed at University of Missouri Health Care. Diabetes Mellitus (DM) was not present in 20834, with 5175 had DM. DM patients had a twofold higher incidence of wound infection, Deep Venous Thrombosis, and Urinary Tract Infection. Pulmonary Embolism and myocardial infarction were 3 times more common in DM. Stroke rate was 3.9 more likely in DM. Overall, comorbidities were 2.4 fold higher in DM. The estimated time to acquire the above data was 8 hours.

Conclusions: Informatics for Integrating Biology and the Bedside is an excellent tool to extract preliminary data to develop hypothesis, test hypothesis, and gather preliminary report in a reasonable period of time. De-identified data allows researchers to perform acquire data without IRB approval.


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