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Clinical Therapeutics/New Technology— Glucose Monitoring and Sensing 2348‑Pub CLINICAL THERAPEUTICS/NEW TECHNOLOGY—GLUCOSECATEGORY MONITORING AND SENSING CLINICAL THERAPEUTICS/NEW TECHNOLOGY— Figure. GLUCOSE MONITORING AND SENSING 2348‑PUB Impact of CME on Improving Understanding of Advances in Glucose Data Interpretation AMY LARKIN, MICHAEL LACOUTURE, ANNE LE, New York, NY A substantial advance in the field of glucose monitoring is the develop- ment of CGM devices. We sought to determine if online continuing medical education (CME) could improve the clinical knowledge and competence of diabetologists/endocrinologists (D/Es) and nurses regarding advances in glu- cose data interpretation. A CME activity was developed as an online video discussion between 2 experts. The effects of education were assessed using a 4-question linked pre-/post-assessment study design, McNemar’s chi-squared test, and Cramer’s V for effect size. Baseline knowledge was higher among D/E compared to nurses: ∙ 63% of D/Es compared to 20% of nurses recognized similarities in glucose monitoring devices. 2350‑PUB ∙ 47% of D/Es compared to 22% of nurses recognized clinical applica- Efficacy of PHR Integrated with EHR and Self‑Monitoring Devices tion of glucose data. on Self‑Care in Patients with Type 2 Diabetes SATOSHI TANIGUCHI, JIN TEMMA, AKIO KURODA, TORU HORIE, HIROYASU ∙ 55% of D/Es compared to 36% of nurses recognized an effective MORI, REIKO SUZUKI, YAYOI ASANO, MICHIKO ARAKI, YU TAMAKI, MUNEHIDE strategy for patient engagement using glucose data. MATSUHISA, Tokushima, Japan Significant overall improvements (P < .05) were seen for both D/Es (n = 137; Background: Digital Personal Health Records (PHR) with tele-medicine medium effect V= 0.171) and nurses (n = 763; small-medium effect V= 0.15). have been proved to be effective in treating diabetes. However, simply digi- tizing logbooks (improving recording, reviewing and sharing capability) may Therapeutics ∙ 17% more D/Es and 24% more nurses correctly recognized A1c pro- Clinical Diabetes/ vides information about glucose exposure. be enough to increase adherence. PUBLISHED ONLY Objective: To develop and evaluate the efficacy of a PHR integrated with ∙ 24% more D/Es and 8% more nurses correctly identified the ability to Electronic Health Record (EHR) and self-monitoring devices. use glucose monitoring data for advancing therapy. Method: A 3-month multi-center randomized trial was performed to type 2 ∙ 20% more D/Es and 17% more nurses selected an effective strategy diabetes patients. Intervention group used the developed PHR “e-DM Diary,” for engaging a patient in their diabetes management plan using glu- with BG monitor, digital scale, BP monitor and activity monitor. Control group cose data. used self-monitoring devices with paper logbooks issued by Japan Asso- Additional education needed: ciation for Diabetes Education and Care, a standard protocol in Japan. The e-DM Diary or paper logbook was referenced at doctor visits. There were no ∙ 36% of D/Es and 54% of nurses failed to recognize similarities in other modifications to treatment. glucose monitoring devices. Overview of e-DM Diary: e-DM Diary is accessed by smartphone or PC. Self- ∙ 31% of D/Es and 71% of nurses failed to recognize information pro- monitoring results are automatically uploaded through patient’s smartphone vided by measuring A1c. via Bluetooth. Patient’s EHR, including test results, treatment goals, and pre- ∙ 53% of D/Es and 63% of nurses failed to recognize clinical applica- scription information were provided automatically. Patient’s status of diabetes tion of glucose data. complications, self-monitoring goals and results, were presented in graphs. This study demonstrates the success of a targeted educational interven- Results: 28 participated were enrolled in this study (intervention=15/con- tion on improving knowledge and competence of D/Es and nurses regarding trol=13, age avg. 54 y.o., HbA1c 6.9%). Summary of Diabetes Self-Care Activ- clinical application glucose data interpretation advances. Baseline knowl- ities Measure, glycemic control and body weight did not change before and edge was higher among D/Es. Additional education on advances in glucose after the study period in both groups, and there was no difference between data is needed for both groups. groups. Patient’s age, e-Health literacy did not influence the results. In the intervention group, 12 of 15 patients answered that e-DM Diary was Supported By: Abbott Diabetes Care effective in reducing the “hassle” of self-monitoring. There were 3 cases were the patient’s understanding of diabetes complication improved. 2349‑PUB Conclusion: e-DM Diary’s capability to reduce hassle of self-care was Blood Glucose Telemonitoring at Retail Pharmacies in China: The recognized, and self-care supporting capability was par to paper logbooks. Alternative Sites for Community Diabetic Care Supported By: Japan Ministry of Internal Affairs and Communications WENHAO QU, YINGJIE LI, YING CHEN, ZHEN WANG, KAI LIU, Shanghai, China Objective: To implement a digital solution at retail pharmacies to improve community diabetic care. 2351‑PUB Methods: We developed a digital solution that consists of bluetooth glucose meter, an App and a cloud database for diabetic care support, and implemented the solution in 1,146 retail pharmacies in 94 cities in China. Dia- WITHDRAWN betic patients who were pharmacy members can receive in-store services of: 1) BG testing with the results synchronized to the cloud, 2) App-assisted personalized coaching, 3) App-assisted personalized meal plans, and 4) phar- macy consultation. This report profiles a diabetic population of 85,790 during Jun 6th 2015 and Nov 4th 2016. Results: The study population had an average age of 59.7 ± 11.8, BMI of 23.7 ± 3.4, and male of 44.3%. A total of 204,887 BG tests were performed, and 28,492 people had at least 2 measurements. Both fasting blood glucose (FBG) and random blood glucoses (RBG) were improved (Figure). Plotting the baseline FBG readings against the category of each city’s economic status found a strong negative correlation r = -0.92, P = 0.029, with the lowest baseline FBG in the economically most advanced cities. Yet the same analy- sis for the glycemic control effect indicated no correlation r = -0.14, P = 0.817. Conclusion: Regional economic status affects the population BG level and pharmacists are effective in community diabetic control regardless the geo- graphic difference. ADA-Supported Research For author disclosure information, see page A751. A613 CLINICAL THERAPEUTICS/NEW TECHNOLOGY—GLUCOSECATEGORY MONITORING AND SENSING 2352‑PUB 2354‑PUB A Chinese Study to Build a HbA1c Prediction Model with 12‑Week Mid‑infrared Quantum Cascade Laser Spectroscopy for Noninva‑ Self‑Monitoring Blood Glucose Values sive, In Vivo Glucose Sensing LING WANG AN, YOU JIE ZHANG, JU MING LU, ZHAO HENG HU, YAU JIUNN ALEXANDRA WERTH, SABBIR LIAKAT, CLAIRE GMACHL, Princeton, NJ LEE, LI NONG JI, A1C PREDICTION STUDY GROUP, Beijing, China, Shangluo, China, Quantum cascade (QC) lasers, invented in 1994, have drastically expanded Pingtung, Taiwan the opportunities for mid-infrared spectroscopy. The mid-infrared region, Objective: The HbA1c value is widely used to judge the diabetes control. often called the fingerprint region, has strong molecular absorption features Day-to-day diabetes management is guided by self-monitoring blood glucose for a multitude of biomarkers. QC laser spectroscopy can provide sensitive (SMBG) data. To predict HbA1c with daily SMBG data may encourage people and selective monitoring of these biomarkers. Recently, we have imple- with type 2 diabetes mellitus (T2DM) to pursue good glycemic control. This mented a noninvasive, mobile glucose sensor based on this technology. Our retrospective study aimed to define a mathematic model to predict HbA1c system has three main components: a QC laser, an integrating sphere, and a value with SMBG values obtained from daily lives. thermal-electrically cooled mercury cadmium telluride (MCT) detector. The Methods: A total of 195 subjects with T2DM with 245 HbA1c and 21,375 QC laser is swept from 8-10μm; this wavelength range contains unique spec- SMBG data were analyzed. HbA1c data were collected after the 12 weeks tral absorption features of glucose, particularly the C-O stretching mode at SMBG. One HbA1c value was correspondent with a mean of 87 SMBG values. 9.5μm. The light penetrates into the dermis layer of the skin where it is Results: By linear regression analysis, there were significant correlation absorbed by the glucose molecules in the interstitial fluid. The light is then observed between the HbA1c level and past three 28-days average SMBG backscattered off of the collagen fibers and other scatters then collected values (A1C=2.986+0.119×SMBG3+0.198×SMBG2+0.167×SMBG1, R2=0.432, using the integrating sphere and MCT detector. Backscattered spectra are p=0.000), allowing prediction of HbA1c with changing SMBG. The linear collected every 5 minutes from a single subject after eating a meal. We ana- regression equation between the HbA1c and the 84-days SMBG values also lyze the series of collected spectra using principal component (PC) analysis showed good correlation (y=3.119+0.466×SMBG, R2=0.432, p=0.000). When to determine the wavelengths that correspond to highest variance. We con- compared the estimated HbA1c and observed HbA1c values, 70% of the sam- sistently see a strong correlation with the predicted PC of the spectra and ples had variance within 10% and 88% of the samples had variance within the known glucose absorption spectrum. 15%. Similar results were found when compared the estimated HbA1c calcu- Figure. lated by equation provide by Nathan DM (and A1c-Derived Average Glucose Study Group. Diabetes Care,2008,31:1473-1478) and the observed HbA1c Therapeutics values. The samples with higher variance had significantly fewer SMBG Clinical Diabetes/ frequency (p=0.011). PUBLISHED ONLY Conclusions: This HbA1c prediction model could be experimentally used for subjects with T2DM in daily diabetes management.
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