• Jesse M Ehrenfeld, Jonathan P Wanderer, Maxim Terekhov, Brian S Rothman, and Warren S Sandberg.
• From the Departments of Anesthesiology, Surgery, Biomedical Informatics, Health Policy, Vanderbilt University School of Medicine, Nashville, Tennessee (J.M.E.); Department of Surgery, Uniformed Services University of the Health Sciences, Vanderbilt University Hospital, Nashville, Tennessee (J.M.E.); Departments of Anesthesiology and Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee (J.P.W.); and Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee (M.T., B.S.R., W.S.S.).
• Anesthesiology. 2017 Mar 1; 126 (3): 431-440.

BackgroundDiabetic patients receiving insulin should have periodic intraoperative glucose measurement. The authors conducted a care redesign effort to improve intraoperative glucose monitoring.MethodsWith approval from Vanderbilt University Human Research Protection Program (Nashville, Tennessee), the authors created an automatic system to identify diabetic patients, detect insulin administration, check for recent glucose measurement, and remind clinicians to check intraoperative glucose. Interrupted time series and propensity score matching were used to quantify pre- and postintervention impact on outcomes. Chi-square/likelihood ratio tests were used to compare surgical site infections at patient follow-up.ResultsThe authors analyzed 15,895 cases (3,994 preintervention and 11,901 postintervention; similar patient characteristics between groups). Intraoperative glucose monitoring rose from 61.6 to 87.3% in cases after intervention (P = 0.0001). Recovery room entry hyperglycemia (fraction of initial postoperative glucose readings greater than 250) fell from 11.0 to 7.2% after intervention (P = 0.0019), while hypoglycemia (fraction of initial postoperative glucose readings less than 75) was unchanged (0.6 vs. 0.9%; P = 0.2155). Eighty-seven percent of patients had follow-up care. After intervention the unadjusted surgical site infection rate fell from 1.5 to 1.0% (P = 0.0061), a 55.4% relative risk reduction. Interrupted time series analysis confirmed a statistically significant surgical site infection rate reduction (P = 0.01). Propensity score matching to adjust for confounders generated a cohort of 7,604 well-matched patients and confirmed a statistically significant surgical site infection rate reduction (P = 0.02).ConclusionsAnesthesiologists add healthcare value by improving perioperative systems. The authors leveraged the one-time cost of programming to improve reliability of intraoperative glucose management and observed improved glucose monitoring, increased insulin administration, reduced recovery room hyperglycemia, and fewer surgical site infections. Their analysis is limited by its applied quasiexperimental design.

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