The A1CNow + provides accuracy and precision when performing POCT of HbA1c as an aid in diabetes management. Ongoing improvements in this and other HbA1c POCT devices may lead to a greater global acceptance of the role of POCT of HbA1c in diabetes management.

Background: Glycated hemoglobin (A1C) monitoring is an integral component of diabetes management. This study was conducted to evaluate the performance of the A1CNow® SELFCHECK device when used by lay users and health care professionals (HCPs) to measure A1C. Methods: Subjects performed two A1CNow SELFCHECK finger-stick self-tests followed by a finger-stick test of the subject's blood by a HCP. The primary endpoint assessed accuracy of the subject and HCP A1CNow SELFCHECK readings. Secondary endpoints included precision, comprehension of instructional material (written material ± DVD), and product satisfaction. For accuracy comparison, a venous blood sample was drawn from each subject and tested by laboratory (TOSOH) analysis. Subject comprehension of product instructional material was evaluated via first-time failure (FTF) rate as recorded by the HCP, and subject satisfaction was assessed through written survey. Results: A total of 110 subjects with ( n = 93) and without ( n = 17) diabetes participated. Of 177 subject A1C values, 165 (93.2%) were within the acceptable range of ±13.5% of the laboratory reference value and considered accurate. Regression analysis showed good correlation of subject values to laboratory and HCP results ( R2 = 0.93 for both). The average within-subject coefficient of variation was 4.57% ( n = 74). The FTF rates with and without instructional DVD were 11.3% ( n = 56) and 39.6% ( n = 54), respectively. Subjects with diabetes/prediabetes overwhelmingly indicated that they were “very” to “extremely” likely (93.5%) to discuss their home A1C results with their HCP. Conclusions: Lay users found the A1CNow SELFCHECK easy to use, and both lay users and HCPs were able to measure A1C accurately.

Objective: The objective of the study is to identify predictors of utilization of a type 2 diabetes (T2D) management App over time for insulin users (IUs) and noninsulin users (NIUs). Research Design and Methods: We followed over 16 weeks a national sample of unselected T2D adults who independently elected to download and pair a CONTOUR DIABETES App with their CONTOUR NEXT ONE glucose meter. App use and frequency of glucose testing were recorded. Baseline surveys recorded participant demographic, disease status, distress, medication taking, and views of technology to predict utilization. Results: Mean age was 51.6 years (108 IUs; 353 NIUs), 48% were female, time with diabetes was 6.9 years, and self-reported HbA1c was 8.1% (36.3 mmol/mol). Mean duration of App use was 85.4 days and 40% stopped using the App before 16 weeks. Continuous users were older and reported higher distress, better medication taking, and more positive attitudes toward technology (all P < .01). IUs tested more frequently than NIUs, but frequency and intensity of testing decreased markedly for both groups over time. More predictors of App use frequency and testing occurred for NIUs than IUs: older age, higher HbA1c, lower distress, more medication taking (all P < .05). Conclusions: App use and testing decreased markedly over time. Variations in the predictors of frequency of App use suggest that the utilization of mobile technologies requires a tailored approach that addresses the specific needs of individual users, compared with adopting a one-size-fits-all strategy, and that IUs and NIUs may require very different strategies of customization.

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Objective: Evaluations of technology to help adults manage type 2 diabetes (T2D) have yielded mixed results. We analyzed the effectiveness of a free app linked to a glucose meter to study reductions in glucose levels over time among a self-selected sample of adults with T2D. Research Design and Methods: Adults with T2D >12 months, >21 years, ability to read English (insulin using—IU and non-insulin using—NIU) who independently elected to pair their CONTOUR NEXT ONE meter with the CONTOUR DIABETES App were invited to participate. Glucose data from baseline to 16 weeks were uploaded to the cloud (N = 461). Assessment of diabetes distress, medication taking, quality of life, and hypoglycemia concerns occurred at baseline, six, and 16 weeks. Results: Findings indicated a significant decrease in weekly glucose levels over time: baseline mean = 169 (62.0) (9.4 mmol/L; 3.44); 16-week mean = 146.5 (36.0) (8.1 mmol/L; 2.0) ( P < .001), with no IU and NIU differences. Largest reductions occurred during the first six weeks, with no later rebound effects. Significant, though modest, improvements in global quality of life ( P = .03), hypoglycemia concerns ( P = .01), and diabetes distress ( P < .001) occurred over 16 weeks. Conclusions: Making an App for monitoring glucose easily available for download with a glucose meter can be helpful for self-selected adults with T2D. Effective utilization assumes that users are sufficiently motivated and engaged, are comfortable and trusting of the technology, and have sufficient knowledge of how to make use of the glucose data.