Diabetes Remote Monitoring Research Articles

Diabetes Remote Monitoring Program Implementation: A Mixed Methods Analysis of Delivery Strategies, Barriers and Facilitators.

Remote patient monitoring (RPM) is being increasingly utilized as a type of telemedicine modality to improve access to quality health care, although there are documented challenges with this type of innovation. The goals of this study were to characterize clinic delivery strategies for an RPM program and to examine barriers and facilitators to program implementation in a variety of community clinic settings. Primary data were collected via individual and small group interviews and surveys of clinical staff from South Carolina primary care clinics participating in an RPM program for patients with diabetes mellitus type 2 in 2019. We used a parallel convergent mixed methods study design with six South Carolina primary care outpatient clinics currently participating in a diabetes remote monitoring program. Clinic staff participants completed surveys to define delivery strategies and experiences with the program in a variety of clinical settings. Interviews of clinic staff examined barriers and facilitators to program implementation guided by the Consolidated Framework for Implementation Research (CFIR). Quantitative survey data were summarized via descriptive statistics. Qualitative data from interviews were analyzed in a template analysis approach with primary themes identified and organized by two independent coders and guided by the CFIR. Quantitative and qualitative findings were then synthesized in a final step. RPM program delivery strategies varied across clinic, patient population, and program domains, largely affected by staffing, leadership buy-in, resources, patient needs, and inter-site communication. Barriers and facilitators to implementation were linked to similar factors that influenced delivery strategy. RPM programs were implemented in a variety of different clinic settings with program delivery tailored to fit within each clinic's workflow and meet patients' needs. By addressing the barriers identified in this study with focused training and support strategies, delivery processes can improve implementation of RPM programs and thus benefit patient outcomes in rural and community settings.

Impact of a diabetes remote monitoring program on medication adherence.

BACKGROUND: Medication nonadherence in diabetes is well documented to be associated with inadequate glycemic control. Through remote blood glucose (BG) monitoring, unlimited test strip and lancet supplies, personal coaching, and online access to clinical information and educational resources, diabetes remote monitoring (DRM) programs may provide a solution. OBJECTIVE: To examine the relationship between patient participation in a DRM solution and adherence to oral antidiabetic drugs (OAD). METHODS: A retrospective, propensity score-matched cohort study was conducted using deidentified administrative claims data from a large pharmacy benefit manager. Commercially insured patients aged 18 years or older and having 2 or more 30-day adjusted OAD claims comprised the target sample. Patients enrolled in insurance plans that implemented DRM, who had at least 1 BG check (ever engaged) between April 1, 2015, and March 31, 2018 (exposure) were matched to patients enrolled in insurance plans that did not implement DRM (nonexposure). After a 1:2 matching on baseline demographics, disease burden proxy, total pharmacy out-of-pocket costs, previous adherence and insulin use, nonexposure group participants were assigned the same first BG check date as their matched DRM participants. Medication adherence measured as proportion of days covered (PDC) in the 365 days following first BG check was examined as a continuous and binary outcome measure (PDC > 80% or adherent vs < 80% or nonadherent). Multivariable linear and logistic regression were conducted to examine differential magnitude in adherence and likelihood of being adherent, respectively. RESULTS: The final sample consisted of 6,002 exposure and 12,004 nonexposure group patients. DRM participants who were ever engaged had a 4.5% higher adherence rate (P < 0.001) and 42% higher odds of being adherent (P < 0.001) in the period after engagement compared with non-DRM participants. Sensitivity analyses showed that patients engaged continuously (> 1 BG check per week) for 3, 6, and 12 months had 5.1%, 5.2%, and 6.4% higher adherence rates, respectively (P < 0.001), and 52%, 64%, and 98% higher odds of being adherent, respectively (P < 0.001), compared with non-DRM participants. CONCLUSIONS: The study findings offer evidence that DRM engagement is associated with higher odds of medication adherence. DRM solutions that provide access to glucose test results, personalized coaching, educational resources, and lower testing supply cost can also influence adherence. Our findings have important implications for payers and patients related to improved health outcomes due to higher medication adherence. DISCLOSURES: Funding for this study was provided by Express Scripts. Munshi, Amelung, Carter, and Henderson are employed by Express Scripts. James and Shah are employed by Livongo, which provided the DRM solution.

Evaluation of a Diabetes Remote Monitoring Program Facilitated by Connected Glucose Meters for Patients With Poorly Controlled Type 2 Diabetes: Randomized Crossover Trial.

BackgroundPatients with poorly controlled type 2 diabetes (T2D) experience increased morbidity, increased mortality, and higher cost of care. Self-monitoring of blood glucose (SMBG) is a critical component of diabetes self-management with established diabetes outcome benefits. Technological advancements in blood glucose meters, including cellular-connected devices that automatically upload SMBG data to secure cloud-based databases, allow for improved sharing and monitoring of SMBG data. Real-time monitoring of SMBG data presents opportunities to provide timely support to patients that is responsive to abnormal SMBG recordings. Such diabetes remote monitoring programs can provide patients with poorly controlled T2D additional support needed to improve critical outcomes.ObjectiveTo evaluate 6 months of a diabetes remote monitoring program facilitated by cellular-connected glucose meter, access to a diabetes coach, and support responsive to abnormal blood glucose recordings greater than 400 mg/dL or below 50 mg/dL in adults with poorly controlled T2D.MethodsPatients (N=119) receiving care at a diabetes center of excellence participated in a two-arm, 12-month randomized crossover study. The intervention included a cellular-connected glucose meter and phone-based diabetes coaching provided by Livongo Health. The coach answered questions, assisted in goal setting, and provided support in response to abnormal glucose levels. One group received the intervention for 6 months before returning to usual care (IV/UC). The other group received usual care before enrolling in the intervention (UC/IV) for 6 months. Change in hemoglobin A1c (HbA1c) was the primary outcome, and change in treatment satisfaction was the secondary outcome.ResultsImprovements in mean HbA1c were seen in both groups during the first 6 months (IV/UC −1.1%, SD 1.5 vs UC/IV −0.8%, SD 1.5; P<.001). After crossover, there was no significant change in HbA1c in IV/UC (mean HbA1c change +0.2, SD 1.7, P=.41); however, those in UC/IV showed further improvement (mean HbA1c change −0.4%, SD 1.0, P=.008). A mixed-effects model showed no significant treatment effect (IV vs UC) over 12 months (P=.06). However, participants with higher baseline HbA1c and those in the first time period experienced greater improvements in HbA1c. Both groups reported similar improvements in treatment satisfaction throughout the study.ConclusionsPatients enrolled in the diabetes remote monitoring program intervention experienced improvements in HbA1c and treatment satisfaction similar to usual care at a specialty diabetes center. Future studies on diabetes remote monitoring programs should incorporate scheduled coaching components and involve family members and caregivers.Trial RegistrationClinicalTrials.gov NCT03124043; https://clinicaltrials.gov/ct2/show/NCT03124043

DIY diabetes remote monitoring [Resources

Ny son, Evan, was diagnosed with type 1 diabetes in August 2012. Type 1 diabetes is an autoimmune disease that attacks the pancreas and prevents insulin production. The body needs insulin to transport glucose from the blood to the cells. Synthetic insulin is used to manage type 1 diabetes, but it doesn’t work as quickly as human insulin. Determining the right dose of insulin for a given meal’s carbohydrate content becomes an all-consuming balancing act. Too little insulin and blood sugar skyrockets, causing potentially lifethreatening complications. Too much insulin and blood sugar plunges to dangerous levels.

Evaluation of a Remote Monitoring System for Diabetes Control

PurposeThe use of technology to implement cost-effective health care management on a large scale may be an alternative for diabetes management but needs to be evaluated in controlled trials. This study assessed the utility and cost-effectiveness of an automated Diabetes Remote Monitoring and Management System (DRMS) in glycemic control versus usual care. MethodsIn this randomized, controlled study, patients with uncontrolled diabetes on insulin were randomized to use of the DRMS or usual care. Participants in both groups were followed up for 6 months and had 3 clinic visits at 0, 3, and 6 months. The DRMS used text messages or phone calls to remind patients to test their blood glucose and to report results via an automated system, with no human interaction unless a patient had severely high or low blood glucose. The DRMS made adjustments to insulin dose(s) based on validated algorithms. Participants reported medication adherence through the Morisky Medication Adherence Scale-8, and diabetes-specific quality of life through the diabetes Daily Quality of Life questionnaire. A cost-effectiveness analysis was conducted based on the estimated overall costs of DRMS and usual care. FindingsA total of 98 patients were enrolled (59 [60%] female; mean age, 59 years); 87 participants (89%) completed follow-up. HbA1c was similar between the DRMS and control groups at 3 months (7.60% vs 8.10%) and at 6 months (8.10% vs 7.90%). Changes from baseline to 6 months were not statistically significant for self-reported medication adherence and diabetes-specific quality of life, with the exception of the Daily Quality of Life–Social/Vocational Concerns subscale score (P = 0.04). ImplicationsAn automated system like the DRMS may improve glycemic control to the same degree as usual clinic care and may significantly improve the social/vocational aspects of quality of life. Cost-effectiveness analysis found DRMS to be cost-effective when compared to usual care and suggests DRMS has a good scale of economy for program scale up. Further research is needed to determine how to sustain the benefits seen with the automated system over longer periods.