Novel approach to inpatient glucometric monitoring and variability in a community hospital setting.

The diabetes population is expected to at least double in the next 25 years, and the cost of treating the disease will nearly triple as hospitalizations associated with diabetes continue to rise.1,2 Hyperglycemia in the hospital environment is associated with higher rates of complications, longer lengths of stay, and higher mortality rates.3-10 Improved glucose management has been demonstrated to reduce length of stay and improve morbidity and mortality outcomes, although reports vary on the intensity with which inpatient glucose control should be maintained.11-16 In the current environment of increased reporting of quality outcomes, it remains critically important for health care systems to have the capacity to monitor glucose management and to set appropriate targets to minimize complications and costs. Health care systems across the nation face serious challenges when managing blood glucose levels in high-risk, hospitalized patients, and often this care is suboptimal.17,18 Although standardized, evidence-based protocols and team management models have the potential to improve care delivery and quality outcomes in glucose management, there nevertheless remain formidable barriers to the systemwide implementation of these approaches. Moreover, a standardized metric is needed to assess and compare the efficacy and safety of these glucose management interventions. The Society for Hospital Medicine provides guidelines for tracking glucose control in the hospital environment, but these have not been adopted consistently across health systems.19,20 The most commonly used metrics include a day- or stay-weighted mean of glucose values using point-of-care (POC) measurements.21 These averages provide summaries of glucose control, but may fail to fully capture important aspects of individual patient experiences, such as hyper- or hypoglycemic events, and/or glucose variability. Indeed, glucose variability has been linked with mortality, and thus has been proposed as an important indicator of blood glucose management.22 Nevertheless, as Eslami et al22 point out, commonly used measures of variability (eg, standard deviation [SD], mean amplitude of glycemic excursions [MAGE], glycemic lability index) also have limitations, due variously to underlying asymmetric distributions of blood glucose values, sampling frequency, or severity of illness. Scripps, one of the largest health systems in San Diego County, manages 4 hospitals on 5 campuses and 2 integrated medical groups, and is affiliated with over 1500 primary care physicians and specialists. In partnership with the Scripps Whittier Diabetes Institute (SWDI), Scripps has invested significant resources to developing a systemwide glucose management program.23,24 In 2009, Scripps established a robust glucometric data reporting system that included the ability to determine rates of “well-managed days” (ie, days in which no more than 1 reading is outside the window of 70 to 180 mg/dL) based on hospital POC glucose testing. Adding a measure of rate to identify frequent glucose excursions can provide added information on where to target intervention efforts to provide support mechanisms and fine-tune algorithms to more rapidly bring blood glucose values into well-managed ranges. The purpose of this article is to introduce a simple metric of glucose variability: glucose excursion rate. This metric is examined using data from a 2-year observational study of glucose management conducted at Scripps. For exploratory purposes, we also examine age, gender, ethnicity, and illness severity as predictors of glucose variability.