Objective:The objective of this study was to determine inaccuracies of miscoded blood glucose (BG) meters and potential errors in insulin dose based on values from these meters. Research Design:Fasting diabetic subjects at three clinical centers participated in a 2-hour meal tolerance test. At various times subjects' blood was tested on five BG meters and on a Yellow Springs Instruments laboratory glucose analyzer. Some meters were purposely miscoded. Using the BG values from these meters, along with three insulin dose algorithms, Monte Carlo simulations were conducted to generate ideal and simulated-meter glucose values and subsequent probability of insulin dose errors based on normal and empirical distribution assumptions. Results:Maximal median percentage biases of miscoded meters were +29% and -37%, while maximal median percentage biases of correctly coded meters were only +0.64% and -10.45% (p = 0.000, c 2 test, df = 1). Using the low-dose algorithm and the normal distribution assumption, the combined data showed that the probability of insulin error of ±1U, ±2, ±3, ±4, and ±5U for miscoded meters could be as high as 49.6, 50.0, 22.3, 1.4, and 0.04%, respectively. This is compared to manually, correctly coded meters where the probability of error of ±1, ±2, and ±3U could be as high as 44.6, 7.1, and 0.49%, respectively. There was no instance of a ±4 or ±5U insulin dose error with a manually, correctly coded meter. For autocoded meters, the probability of ±1 and ±2U could be as high as 35.4 and 1.4%, respectively. For autocoded meters there were no calculated insulin dose errors above ±2U. The probability of insulin misdosing with either manually, correctly coded or autocoded meters was significantly lower than that with miscoded meters. Results using empirical distributions showed similar trends of insulin dose errors. Conclusions:Blood glucose meter coding errors may result in significant insulin dosing errors. To avoid error, patients should be instructed to code their meters correctly or be advised to use an autocoded meter that showed superior performance over manually, correctly coded meters in this study.

The purpose of this study was to evaluate the effect of redesigning the education program from individual instructional sessions to a format where the majority of instruction was provided through small group classes. Patient outcomes of lifestyle changes as evidenced by weight loss, improved glycemic control, adoption of a consistent pattern of blood glucose monitoring, and increased physical activity were evaluated using a physician satisfaction survey and a patient satisfaction and lifestyle change survey. The findings indicate that the changes in the education program accommodated a variety of needs; facilitated cost-effectiveness; were convenient for the patients, educators, and physicians; and still promoted adaptive lifestyle changes in behavior leading to improved glycemic control, increased levels of physical activity, and weight loss in persons with type 2 diabetes.

Background: