Evaluation of the analytical performance of the coulometry-based Optium Omega blood glucose meter

Large-scale performance evaluation of Accu-Chek inform II point-of-care glucose meters

BACKGROUND

The aim of this study was to report the experience of large-scale performance evaluation of 238 Accu-Chek Inform II point-of-care (POC) glucose meters in a single medical setting.

METHODS

The repeatability of 238 POC devices, the within-site imprecision of 12 devices, and the linearity of 49 devices were evaluated using glucose control solutions. The glucose results of 24 POC devices and central laboratory were compared using patient samples.

RESULTS

Mean concentration of control solutions was 2.39 mmol/L for Level 1 and 16.52 mmol/L for Level 2. The pooled repeatability coefficient of variation (CV) of the 238 devices was 2.0% for Level 1 and 1.6% for Level 2. The pooled within-site imprecision CV and reproducibility CV of the 12 devices were 2.7% and 2.7% for Level 1, and 1.9%, and 1.9% for Level 2, respectively. The test results of all 49 devices were linear within analytical measurement range from 1.55-31.02 mmol/L. The correlation coefficient for individual POC devices ranged from 0.9967-0.9985. The total correlation coefficient for the 24 devices was 0.998.

CONCLUSIONS

The Accu-Chek Inform II POC blood glucose meters performed well in terms of precision, linearity, and correlation evaluations. Consensus guidelines for the large-scale performance evaluations of POC devices are required.

Higher accuracy of self-monitoring of blood glucose in insulin-treated patients in Germany: clinical and economical aspects

BACKGROUND

Accuracy standards of blood glucose (BG) meters are currently under review. Revised standards are expected to tighten accuracy requirements. Regarding clinical and financial impact of BG meter accuracy, very little data are available. The aim of this study was to analyze potential cost savings related to higher accuracy of glucose meters in Germany.

METHODS

As a model for calculation, a reduction of meter error from 20% to 5% was applied. The health economic analysis was based on four main pillars: (1) number of insulin-treated patients; (2) costs for glucose monitoring in Germany; (3) data of a modeling analysis on the impact on hypoglycemic episodes, glycosylated hemoglobin (HbA1c), and, subsequently, myocardial infarctions; and (4) costs of diabetes-related complications in Germany. A reduction of meter error from 20% to 5% was identified to be associated with a 10% reduction in severe hypoglycemic episodes and a 0.39% reduction in HbA1c, which translates into a 0.5% reduction of myocardial infarctions.

RESULTS

According to the health economic analysis, the reduction in severe hypoglycemic episodes and myocardial infarctions led to cost savings of €24.14 per patient per year. Considering 390,000 type 1 diabetes patients or 2.3 million insulin-treated patients in Germany, these savings could be equal to a reduction in health care expenditures of more than €9.4 million and €55.5 million, respectively.

CONCLUSIONS

Potential cost savings and clinical effects due to higher accuracy of BG meters should provide an impetus to implementation of tighter accuracy standards and development of glucose meters that provide highest possible accuracy.

Evaluation of the analytical performance of the coulometry-based Optium Omega blood glucose meter: what do such evaluations show?

The article entitled "Evaluation of the Analytical Performance of the Coulometry-Based Optium Omega Blood Glucose Meter", by Solnica and colleagues in this issue of Journal of Diabetes Science and Technology demonstrates that the Optium Omega blood glucose meter meets the analytical requirements for glucose meter performance and it is stated that the results are clinically useful. The authors studied precision, bias, and reagent lot-to-lot error sources. The ultimate goal of an evaluation is to estimate the distribution of errors (from any source) that will be experienced in routine use. The data collection and analysis methods to achieve this are discussed, as are the standards used to compare the results. Claiming clinical usefulness is almost a boilerplate statement in evaluations but meeting standards does not prove clinical usefulness.