Benefits to health care professionals and patients with diabetes of a novel blood glucose meter that provides pattern recognition and real-time automatic messaging compared to conventional paper logbooks
DOI:
https://doi.org/10.1179/2057332415Y.0000000001Keywords:
Blood glucose monitoring, blood glucose patterns, colour range indicator, glycemic control, logbooksAbstract
AbstractBackground: Self-monitoring of blood glucose is crucial for maintaining overall blood glucose (BG) levels. Health care professionals (HCPs) must rapidly assess patient BG data and recommend treatment changes, as appropriate, during short office visits. A meter offering automatic BG pattern recognition and in-the-moment messaging may change how HCPs and patients with diabetes work together to achieve glycemic control.
Methods: Two separate studies evaluated the potential benefits of the OneTouch Verio® BG monitoring system. In one study, 64 HCPs were evaluated on their ability to rapidly recognise BG patterns in simulated logbooks compared to using the meter, before completing a survey on potential benefits of the meter to themselves and their patients. In the other study, patients with diabetes used the meter at home for 1 week before also completing a survey.
Results: Patients indicated that the meter was simple to use and understand. For HCPs, using the meter to identify BG patterns was significantly faster and more accurate than using a logbook. In addition, HCPs believed the meter features would make interpreting BG results easier for patients.
Conclusions: An easy to use meter with in-the-moment BG insights may help improve patient management of glycemic control between office visits. In addition, using the meter may improve efficiency during office visits.
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Grady M, Campbell D, MacLeod K, Srinivasan A. Evaluation of a blood glucose monitoring system with automatic high- and low-pattern recognition software in insulin-using patients: pattern detection and patient-reported insights. J Diabetes Sci Technol. 2013;7:970–8.
Virdi N, Daskiran M, Nigam S, Kozma C, Raja P. The association of self-monitoring of blood glucose use with medication adherence and glycemic control in patients with type 2 diabetes initiating non-insulin treatment. Diabetes Technol Ther. 2012;14:790–8.
Choudhary P, Genovese S, Reach G. Blood glucose pattern management in diabetes: creating order from disorder. J Diabetes Sci Technol. 2013;7:1575–84.
Bailey T, Chang A, Rosenblit PD, Jones L, Teft G, Setford S, et al. A comprehensive evaluation of the performance of the test strip technology for OneTouch Verio glucose meter systems. Diabetes Technol Ther. 2012;14(8):701–9.
Hirsch IB, Bode BW, Childs BP, Close KL, Fisher WA, Gavin JR, et al. Self-monitoring of blood glucose (SMBG) in insulin- and non-insulin-using adults with diabetes; consensus recommendations for improving SMBG accuracy, utilization, and research. Diabetes Technol Ther. 2008;10:419–39.
Mazze RS, Shamoon H, Pasmantier R, Lucido D, Murphy J, Hartmann K, et al. Reliability of blood glucose monitoring by patients with diabetes mellitus. Am J Med. 1984;77:211–7.
Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, et al. Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 2012;35:1364–79.
Barnes CS, Ziemer DC, Miller CD, Doyle JP, Watkins CJr, Cook CB, et al. Little time for diabetes management in the primary care setting. Diabetes Educ. 2004;30:126–35.
Katz LB, Dirani RG, Li G, Randoll FA, Mahoney JJ. Automated glycemic pattern analysis can improve health care professional efficiency and accuracy. J Diabetes Sci Technol. 2013;7:163–6.
Schwartz FL, Marling CR, Shubrook J. Automated glycemic pattern analysis: overcoming diabetes clinical inertia. J Diabetes Sci Technol. 2013;7:167–9.
Rodbard HW, Schnell O, Unger J, Rees C, Amstutz L, Parkin CG, et al. Use of an automated decision support tool optimizes clinicians’ ability to interpret and appropriately respond to structured self-monitoring of blood glucose data. Diabetes Care 2012;35:693–8.
Nigam S, Virdi NS, Daskiran M, Kozma CM, Paris A, Dickson WM. Association between sitagliptin adherence and self-monitoring of blood glucose. J Diabetes Sci Technol. 2012;6:555–62.
, ADVANCE Collaborative GroupPatel A, MacMahon S, Chalmers J, Neal B, Billot L, Woodward M, et al. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. New Engl J Med. 2008;358:2560–72.
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