Significant Insulin Dose Errors May Occur if Blood Glucose Results are Obtained from Miscoded Meters
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. Fasting diabetic subjects at three clinical centers participated in a 2-hour meal tolerance test. At various times subjects' bl...
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| Published in | Journal of diabetes science and technology Vol. 1; no. 2; pp. 205 - 210 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Diabetes Technology Society
01.03.2007
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-2968 1932-3107 1932-3107 |
| DOI | 10.1177/193229680700100211 |
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| Summary: | 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.
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.
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.
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. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Disclosures: Weiping Zhong is a full-time employee of Bayer HealthCareLLC; Lois J Proud was a full-time employee of Bayer HealthCareLLC until retirement on November 30, 2006; and Joan Lee Parkes is a full-time employee of Bayer HealthCareLLC. Funding: This work was funded by a grant from Bayer HealthCare LLC |
| ISSN: | 1932-2968 1932-3107 1932-3107 |
| DOI: | 10.1177/193229680700100211 |