Despite accuracy standards, there are performance differences among commercially available blood glucose monitoring (BGM) systems. The objective of this analysis was to assess the potential clinical and economic impact of accuracy differences of various BGM systems using a modeling approach.
We simulated additional risk of hypoglycemia due to blood glucose (BG) measurement errors of five different BGM systems based on results of a real-world accuracy study, while retaining other sources of glycemic variability. Using data from published literature, we estimated an annual additional number of required medical interventions as a result of hypoglycemia. We based our calculations on patients with type 1 diabetes mellitus (T1DM) and T2DM requiring multiple daily injections (MDIs) of insulin in a U.S. health care system. We estimated additional costs attributable to treatment of severe hypoglycemic episodes resulting from BG measurement errors.
Results from our model predict an annual difference of approximately 296,000 severe hypoglycemic episodes from BG measurement errors for T1DM (105,000 for T2DM MDI) patients for the estimated U.S. population of 958,800 T1DM and 1,353,600 T2DM MDI patients, using the least accurate BGM system versus patients using the most accurate system in a U.S. health care system. This resulted in additional direct costs of approximately $339 million for T1DM and approximately $121 million for T2DM MDI patients per year.
Our analysis shows that error patterns over the operating range of BGM meter may lead to relevant clinical and economic outcome differences that may not be reflected in a common accuracy metric or standard. Further research is necessary to validate the findings of this model-based approach.
[Show abstract][Hide abstract] ABSTRACT: Modeling approaches demonstrate that improvement in the accuracy of blood glucose (BG) meters may lead to cost savings. An improvement of accuracy of BG meters on the basis of a reduction in error range from 20% to 5% has been reported to be associated with substantial cost savings in Germany. The aim of this study is to analyze potential cost savings related to a reduction in error range from 20% to 15% and 10% of glucose meters in Germany. The health economic analysis included the number of type 1 diabetic and the number of insulin-treated patients in Germany, the costs for glucose monitoring, a model on the effects of the improvement of accuracy on the impact of severe hypoglycemic episodes, HbA1c, and subsequently myocardial infarctions and the costs of diabetes-related complications in Germany. In the model, a reduction of 1% and 3.5% reduction in severe hypoglycemic episodes, and a 0.14% and 0.28% reduction in HbA1c was included. In type 1 diabetes the savings could be equal to a reduction in health care expenditures of more than €1.0 million (20% vs 15% error range) and €3.4 million (20% vs 10% error range). Respectively, potential savings of more than €6.0 million and €20.1 million were calculated for the group of insulin-treated patients. The model demonstrates that a reduction of error range of BG meters from 20% to 15% and 10% may translate into substantial savings for the German health care system.
Journal of diabetes science and technology 02/2014; 8(3):479-482. DOI:10.1177/1932296813516206
[Show abstract][Hide abstract] ABSTRACT: Objective:
The self-monitoring of blood glucose plays a critical role in management of diabetes mellitus. Although laboratory comparisons of glucose meter accuracy are often acceptable, clinical comparisons show frequent inaccuracies. In this paper, we evaluate the accuracy of self-monitoring blood glucose meters using glucose meter and serum comparisons from a large Canadian laboratory.
This study was performed using secondary data obtained from the Laboratory Information System of Calgary Services, the sole provider of laboratory testing to Calgary and surrounding areas. We examined anonymous quality assurance data for glucose meter comparisons performed on home glucose meters between January 1, 2010, and April 30, 2013.
A total of 39 542 comparisons were recorded on 18 540 different subjects. Overall, 6.7% of differences were greater than the current International Standards Organization standard of 15%, and 3.7% exceeded the Canadian guideline of 20%.
Glucose meter checks were infrequently performed (on average, once per 1.6 years). A significant subset of meter results was inaccurate.
Canadian Journal of Diabetes 08/2014; 38(5). DOI:10.1016/j.jcjd.2014.04.004 · 2.00 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background:
This study evaluated the accuracy of Contour(®) Next (CN; Bayer HealthCare LLC, Diabetes Care, Whippany, NJ) compared with five blood glucose monitoring systems (BGMSs) across a wide range of clinically occurring blood glucose levels.
Subjects and methods:
Subjects (n=146) were ≥ 18 years and had type 1 or type 2 diabetes. Subjects' glucose levels were safely lowered or raised to provide a wide range of glucose values. Capillary blood samples were tested on six BGMSs and a YSI glucose analyzer (YSI Life Sciences, Inc., Yellow Springs, OH) as the reference. Extreme glucose values were achieved by glucose modification of the blood sample. System accuracy was assessed by mean absolute difference (MAD) and mean absolute relative difference (MARD) across several glucose ranges, with <70 mg/dL evaluated by MAD as the primary end point.
In the low glucose range (<70 mg/dL), MAD values were as follows: Accu-Chek(®) Aviva Nano (Roche Diagnostics, Indianapolis, IN), 3.34 mg/dL; CN, 2.03 mg/dL; FreeStyle Lite(®) (FSL; Abbott Diabetes Care, Inc., Alameda, CA), 2.77 mg/dL; OneTouch(®) Ultra(®) 2 (LifeScan, Inc., Milpitas, CA), 10.20 mg/dL; OneTouch(®) Verio(®) Pro (LifeScan, Inc.), 4.53 mg/dL; and Truetrack(®) (Nipro Diagnostics, Inc., Fort Lauderdale, FL), 11.08 mg/dL. The lowest MAD in the low glucose range, from CN, was statistically significantly lower than those of the other BGMSs with the exception of the FSL. CN also had a statistically significantly lower MARD than all other BGMSs in the low glucose range. In the overall glucose range (21-496 mg/dL), CN yielded the lowest MAD and MARD values, which were statistically significantly lower in comparison with the other BGMSs.
When compared with other BGMSs, CN demonstrated the lowest mean deviation from the reference value (by MAD and MARD) across multiple glucose ranges.
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