New Criteria for Assessing the Accuracy of Blood Glucose Monitors meeting, October 28, 2011

Abstract

Glucose meters (GMs) are routinely used for self-monitoring of blood glucose by patients and for point-of-care glucose monitoring by health care providers in outpatient and inpatient settings. Although widely assumed to be accurate, numerous reports of inaccuracies with resulting morbidity and mortality have been noted. Insulin dosing errors based on inaccurate GMs are most critical. On October 28, 2011, the Diabetes Technology Society invited 45 diabetes technology clinicians who were attending the 2011 Diabetes Technology Meeting to participate in a closed-door meeting entitled New Criteria for Assessing the Accuracy of Blood Glucose Monitors. This report reflects the opinions of most of the attendees of that meeting. The Food and Drug Administration (FDA), the public, and several medical societies are currently in dialogue to establish a new standard for GM accuracy. This update to the FDA standard is driven by improved meter accuracy, technological advances (pumps, bolus calculators, continuous glucose monitors, and insulin pens), reports of hospital and outpatient deaths, consumer complaints about inaccuracy, and research studies showing that several approved GMs failed to meet FDA or International Organization for Standardization standards in postapproval testing. These circumstances mandate a set of new GM standards that appropriately match the GMs' analytical accuracy to the clinical accuracy required for their intended use, as well as ensuring their ongoing accuracy following approval. The attendees of the New Criteria for Assessing the Accuracy of Blood Glucose Monitors meeting proposed a graduated standard and other methods to improve GM performance, which are discussed in this meeting report.

Figure 1

Blood GM accuracy and precision. (A) Accuracy measures how close the average of a hundred or more GM values over a wide range of glucose readings is to an average of the laboratory values taken at the same time. Accuracy ignores the error in individual values. (B) Precision shows how consistent glucose readings are with each other, or how closely a series of meter values agree with each other, regardless of how close they are to the reference lab value. Precision is often measured as coefficient of variation. (C) Having both accuracy and precision in one meter is the best option. An ideal glucose meter will have a low mean absolute relative error.

Figure 2

Blood GM bias and linearity. Bias is the average of systematic or built-in meter errors, and is usually measured as the percentage difference above or below a reference lab’s values. An ideal bias is 0.0%. Linearity shows upward or downward trends in meter values relative to lab reference values. An ideal linearity is 1.0. The 95% limit of agreement shows the two lines where 95% of the meter results can be found relative to the reference values. An ideal limit of agreement shows two lines very close to the zero line. In the example above, bias and linearity of a sample meter are shown for the low, middle, and high glucose ranges, while the limit of agreement for all values is shown by the upper and lower dashed lines.

Figure 3

One example of how meters might be rated for intended use.