A Rosetta Stone for Insulin Treatment: Self-Monitoring of Blood Glucose

Miscoding and other user errors: importance of ongoing education for proper blood glucose monitoring procedures

BACKGROUND

This article reviews the literature to date and reports on a new study that documented the frequency of manual code-requiring blood glucose (BG) meters that were miscoded at the time of the patient's initial appointment in a hospital-based outpatient diabetes education program.

METHOD

Between January 1 and May 31, 2007, the type of BG meter and the accuracy of the patient's meter code (if required) and procedure for checking BG were checked during the initial appointment with the outpatient diabetes educator. If indicated, reeducation regarding the procedure for the BG meter code entry and/or BG test was provided.

RESULTS

Of the 65 patients who brought their meter requiring manual entry of a code number or code chip to the initial appointment, 16 (25%) were miscoded at the time of the appointment. Two additional problems, one of dead batteries and one of improperly stored test strips, were identified and corrected at the first appointment.

CONCLUSIONS

These findings underscore the importance of checking the patient's BG meter code (if required) and procedure for testing BG at each encounter with a health care professional or providing the patient with a meter that does not require manual entry of a code number or chip to match the container of test strips (i.e., an autocode meter).

Recent progress in analytical instrumentation for glycemic control in diabetic and critically ill patients

Implementing strict glycemic control can reduce the risk of serious complications in both diabetic and critically ill patients. For this reason, many different analytical, mainly electrochemical and optical sensor approaches for glucose measurements have been developed. Self-monitoring of blood glucose (SMBG) has been recognised as being an indispensable tool for intensive diabetes therapy. Recent progress in analytical instrumentation, allowing submicroliter samples of blood, alternative site testing, reduced test time, autocalibration, and improved precision, is comprehensively described in this review. Continuous blood glucose monitoring techniques and insulin infusion strategies, developmental steps towards the realization of the dream of an artificial pancreas under closed loop control, are presented. Progress in glucose sensing and glycemic control for both patient groups is discussed by assessing recent published literature (up to 2006). The state-of-the-art and trends in analytical techniques (either episodic, intermittent or continuous, minimal-invasive, or noninvasive) detailed in this review will provide researchers, health professionals and the diabetic community with a comprehensive overview of the potential of next-generation instrumentation suited to either short- and long-term implantation or ex vivo measurement in combination with appropriate body interfaces such as microdialysis catheters.

Significant insulin dose errors may occur if blood glucose results are obtained from miscoded meters

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, chi(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.

Quality control of self-monitoring of blood glucose: why and how?

The control of analytical quality of self-monitoring of blood glucose (SMBG) is recommended as a routine procedure in diabetes management. This control procedure should be easily accessible to patients, convenient, not time-consuming, and provide a reliable assessment of glucose meter performance. Optimally it should be located in the diabetes outpatient clinic. Presently there are two approaches to carrying out SMBG quality control. The first is based on the comparison of results obtained by a controlled glucose meter and use of the laboratory method or point-of-care testing device as a surrogate reference analyzer. The second one is a traditionally organized external quality assessment scheme with use of a dedicated control material, which is distributed to all participants. The recommended allowable meter error in SMBG can be realistically set at 10%.

Palm glucose readings compared with fingertip readings under steady and dynamic glycemic conditions, using the OneTouch Ultra Blood Glucose Monitoring System

OBJECTIVES

Past studies have suggested the absence of lag between palm glucose and fingertip glucose, even when glucose levels are changing rapidly. However, at any given time point, there may be differences between palm and fingertip glucose values because of glycemic instability and/or test methodology. The objectives of this study included assessing the variability in fingertip blood glucose test results between two fingers, and establishing whether the variability in blood glucose test results obtained from the palm was clinically equivalent to that observed in fingertip-to-fingertip comparisons.

METHODS

This multicenter trial was conducted on patients under both steady-state glycemic conditions and after meal and exercise challenges (to promote rapidly changing glucose). Sequential capillary glucose testing, performed with the One Touch Ultra Blood Glucose Monitoring System (LifeScan, Inc., Milpitas, CA), was allocated to two of four fingertip sites and one of two palm sites in each subject using a randomized, balanced, incomplete block design. One of the fingertips was designated the reference site. Fingertip-to-fingertip variability and fingertip- to-palm variability were assessed under these steady-state and dynamic testing conditions using error grid analysis and by comparing the proportion of clinically acceptable blood glucose tests at the palm site versus the fingertip site. Clinically acceptable agreement was defined as pairs of values (fingertip to reference, or palm to reference) within 15 mg/dL when reference glucose was < or = 75 mg/dL or within 20% when reference glucose was >75 mg/dL.

RESULTS

One hundred eighty-one subjects with type 1 [n = 74 (40.9%)] or type 2 [n = 107 (59.1%)] diabetes at eight clinical sites completed the study. Overall, the proportion of clinically acceptable agreement was high for both palm (95.1%) and fingertip (97.5%) testing. The mean difference between palm and fingertip clinically acceptable agreement when done by healthcare professionals was -1.3% and -4.4%, under steady-state and dynamic glycemic conditions, respectively. Error grid analysis showed >97% of all palm and fingertip measurements fell in Zone A.

CONCLUSION

This study demonstrated that variability between fingertip-to-fingertip and palm-to-fingertip measurements was in the clinically acceptable range during steady-state conditions and when glucose was rapidly changing.

Biosensors—a perspective

Biosensors have been under development for over 35 years and research in this field has become very popular for 15 years. Electrochemical biosensors are the oldest of the breed, yet sensors for only one analyte (glucose) have achieved widespread commercial success at the retail level. This perspective provides some cautions related to expectations for biosensors, the funding of science, and the wide gap between academic and commercial achievements for sensor research. The goal of this commentary is not to arrive at any particular truth, but rather to stimulate lively discussion.