The Effect of a Cellular-Enabled Glucose Meter on Glucose Control for Patients With Diabetes: Prospective Pre-Post Study

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study

BACKGROUND

The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

OBJECTIVE

This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

METHODS

In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

RESULTS

The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

CONCLUSIONS

This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Beyond the EHR: How Digital Health Tools Foster Participatory Health and Self-Care for Patients with Diabetes

Just as physicians managing patients with diabetes find that it is a data-driven process, for patients living with diabetes, it is even more so, as physicians see them every few months, but patients need to live with diabetes all the time. Fortunately, the advent of the web has allowed patients to connect with information, medical care, and other patients, while mobile and connected technologies such as smartphones have provided the flexibility to do this-and to manage and share their health information-from anywhere. Healthcare professionals who care for patients with diabetes should be aware of the digital health technologies that enable patients to better care for themselves, be more active participants in their healthcare, and improve the quality of their lives.

Remote glucose monitoring is feasible for patients and providers using a commercially available population health platform

OBJECTIVE

Remote patient monitoring (RPM) holds potential to enable more individualized and effective care for patients with type 1 diabetes (T1D), but requires population analytics to focus limited clinical resources on patients most in need. We explored the feasibility of RPM from patient and provider standpoints using a commercially available data analytic platform (glooko Population Health) among a cohort of youth with T1D.

STUDY DESIGN

Patients aged 1-20 years with established T1D (≥12 months) and CGM use (≥3 months) were recruited to participate. Participants' CGM devices were connected to the glooko app and linked to the research team's glooko account during a one-month baseline period. This was followed by a six-month intervention period during which participants with >15% of glucose values >250 mg/dl or >5% of values <70 mg/dl each month were contacted with personalized diabetes management recommendations. Participants were surveyed about their experiences, and effects on glycemic control were estimated via change in glucose management indicator (GMI) generated from CGM data at baseline and completion. Changes in time spent within various glucose ranges were also evaluated, and all glycemic metrics were compared to a non-randomized control group via difference-in-difference regression, adjusting for baseline characteristics.

RESULTS

Remote data-sharing was successful for 36 of 39 participants (92%). Between 33%-66% of participants merited outreach each month, and clinician outreach required a median of 10 minutes per event. RPM was reported to be helpful by 94% of participants. RPM was associated with a GMI change of -0.25% (P=0.047) for the entire cohort, and stratified analysis revealed greatest treatment effects among participants with baseline GMI of 8.0-9.4% (GMI change of -0.68%, P=0.047; 19.84% reduction in time spent >250 mg/dl, P=0.005).

CONCLUSIONS

This study demonstrates the feasibility of RPM for patients with T1D using a commercially available population health platform, and suggests that RPM with clinician-initiated outreach may be particularly beneficial for patients with suboptimal glycemic control at entry. However, larger randomized studies are needed to fully explore the glycemic impact of RPM.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04696640, identifier NCT04696640.

The Management Perspective in Digital Health Literature: Systematic Review

BACKGROUND

New digital health technologies are considered one solution to challenges in the health sector, which include rising numbers of chronic diseases and increased health spending. As digitalization in health care is still in its infancy, there are many unanswered questions about the impact of digital health on management.

OBJECTIVE

This paper assesses the current state of knowledge in the field of digital health from a management perspective. It highlights research gaps within this field to determine future research opportunities.

METHODS

A systematic review of digital health literature was conducted using 3 databases. The chosen articles (N=38) were classified according to a taxonomy developed for the purpose, and research gaps were identified based on the topic areas discussed.

RESULTS

The literature review revealed a slight prevalence of practical (n=21, 55%) over theoretical (n=17, 45%) approaches. Most of the papers (n=23, 61%) deal with information technology (IT) and are, therefore, focused more on technology and less on management. The research question in most of the papers (n=31, 82%) deals with the creation of concepts, and very few (n=4, 11%) evaluate or even question existing solutions. Most consider the main reason for digitalization to be the optimization of operational processes (n=26, 68%), and 42% (n=16) deal with new business models. The topic area discussed most frequently was found to be eHealth (n=30, 79%). By contrast, the field of tech health with topics such as sensors receives the least attention (n=3, 8%), despite its significant potential for health care processes and strategy.

CONCLUSIONS

Three main research propositions were identified. First, research into digital health innovation should not focus solely on the technology aspects but also on its implications for strategic and operational management. Second, the research community should target other domains besides eHealth. Third, we observed a lack of quantitative research on the real impact of digital health on organizations and their management. More quantitative evidence is required regarding the expected outcome and impact of the implementation of digital health solutions into our health care organizations.

Blood Pressure Monitoring as a Digital Health Tool for Improving Diabetes Clinical Outcomes: Retrospective Real-world Study

Background

Remote data capture for blood glucose (BG) or blood pressure (BP) monitoring and the use of a supportive digital app are becoming the model in diabetes and hypertension chronic care. One of the goals in chronic condition management is to increase awareness and generate behavioral change in order to improve outcomes in diabetes and related comorbidities, such as hypertension. In addition, there is a lack of understanding of the association between BG and BP levels when using digital health tools.

Objective

By applying a rigorous study framework to digital health data, this study investigated the relationship between BP monitoring and BG and BP levels, as well as a lagged association between BP and BG. We hypothesized that during the first 6 months of BP monitoring, BG and BP levels would decrease. Finally, we suggested a positive association between BP levels and the following month’s BG levels.

Methods

In this retrospective, real-world case-control study, we extracted the data of 269 people with type 2 diabetes (T2D) who tracked their BG levels using the Dario digital platform for a chronic condition. We analyzed the digital data of the users who, in addition to BG, monitored their BP using the same app (BP-monitoring [BPM] group, n=137) 6 months before and after starting their BP monitoring. Propensity score matching established a control group, no blood pressure monitoring (NBPM, n=132), matched on demographic and baseline clinical measures to the BPM group. A piecewise mixed model was used for analyzing the time trajectories of BG, BP, and their lagged association.

Results

Analysis revealed a significant difference in BG time trajectories associated with BP monitoring in BPM and NBPM groups (t=–2.12, P=.03). The BPM group demonstrated BG reduction improvement in the monthly average BG levels during the first 6 months (t=–3.57, P<.001), while BG did not change for the NBPM group (t=0.39, P=.70). Both groups showed similarly stable BG time trajectories (B=0.98, t=1.16, P=.25) before starting the use of the BP-monitoring system. In addition, the BPM group showed a significant reduction in systolic (t=–6.42, P<.001) and diastolic (t=–4.80, P<.001) BP during the first 6 months of BP monitoring. Finally, BG levels were positively associated with systolic (B=0.24, t=2.77, P=.001) and diastolic (B=0.30, t=2.41, P=.02) BP.

Conclusions

The results of this study shed light on the association between BG and BP levels and on the role of BP self-monitoring in diabetes management. Our findings also underscore the need and provide a basis for a comprehensive approach to understanding the mechanism of BP regulation associated with BG.

Efficacy of Digitally Supported and Real-Time Self-Monitoring of Blood Glucose-Driven Counseling in Patients with Type 2 Diabetes Mellitus: A Real-World, Retrospective Study in North India

PURPOSE

Poor glycemic control is prevalent in patients with type 2 diabetes mellitus (T2DM) in India. This study aims to understand the effectiveness of a smartphone-connected glucometer, real-time feedback, and contextualized counseling on glycemic control and hypoglycemic episodes in T2DM patients.

METHODS

This retrospective, multicenter study reviewed the medical records of T2DM patients belonging to several cities of north India, who were digitally engaged with a smartphone-connected glucometer and who had received at least one counseling session between September 2019 and July 2020. Intervention included self-monitoring of blood glucose (SMBG) using a smartphone-connected glucometer enabled with real-time transmission of information to certified diabetes educators (CDE) and their corresponding counseling based on SMBG findings.

RESULTS

Of 7111 adult T2DM patients included in this study, majority (75%) of the patients received a single session of counseling, and the remaining patients received 2 (16.7%), 3 (5%), 4 (2%), or ≥5 (1.3%) sessions. The mean age of the patients was 51.6 years, and the majority (77.9%) were males. Digital monitoring of BG and counseling with CDE significantly reduced the mean fasting (by 9.6%), pre-prandial (by 9.9%), and post-prandial (by 9.2%) BG values in 53%, 52%, and 54% of patients, respectively. The majority (81.4%) of patients showed no hypoglycemic episode (≤70 mg/dL) post-counseling. The hypoglycemia episodes observed with FBG, pre-prandial, and post-prandial BG values were reduced significantly by 58.5%, 48.1%, and 61.8%, respectively, post-counseling.

CONCLUSION

Digitally supported and real-time SMBG-driven counselling was effective in glycemic control and reduction of hypoglycemic episodes in T2DM patients in India. Moreover, reduction in hypoglycemia may be due to back end real-time support of CDE intervention.

Changing face of healthcare: digital therapeutics in the management of diabetes

Diagnosis, prevention, management and treatment of acute and chronic medical conditions have improved with technological advancements in terms of scalability, efficacy, access, and personalized approach. Digital therapeutic applications (DTx) (Blue Star, Diabeo System, Livongo Diabetes Program, Tidepool etc.,) use web-based applications/cloud platforms to provide evidence-based, personalized, rapid point of care management of chronic, behavior-modifiable conditions, including diabetes mellitus (DM). DTx has improved patient compliance, therapeutic success and economic outcomes in DM management by enabling active patient engagement, lifestyle change, comprehensive medical care, and periodic monitoring of glycemic status. Addressing concerns along DTx data vulnerability, comparative efficacy with conventional treatments, ability to accommodate diverse population needs, and resolving ambiguous regulatory policies and reimbursement guidelines are critical for increasing access to DTx, and overcoming availability, accessibility, and affordability issues in the existing resource limited healthcare environment. In this commentary the authors explore the potential, prospects, and challenges of DTx in the management of Diabetes Mellitus.

Telemedicine via Continuous Remote Care: A Proactive, Patient-Centered Approach to Improve Clinical Outcomes

The COVID-19 pandemic has revolutionized health care for patients and providers alike. Telemedicine has moved from the periphery of our health care system to center stage more rapidly than anyone could have envisioned. Currently, virtual care has quite effectively replicated the traditional health system’s care delivery model and reimbursement structure—a patient makes an appointment, then sees a physician (except with video or phone replacing in-office visits) who makes a care plan, and the patient and physician meet again at a later timepoint to assess progress. Replicating this episodic care paradigm virtually has been invaluable for delivering care swiftly during the COVID-19 pandemic; however, we can and should do more with the connectedness and convenience that telemedicine technology enables. Continuous remote care, with a data-driven, proactive outreach to patients, represents a decisive step forward in contrast to the currently available episodic, reactive, patient-initiated care. In the context of continuous remote care, patient biometric and symptom data (patient entered and connected data) are assimilated in real time by artificial intelligence–enabled clinical platforms to bring physicians' and other health care team members’ attention to those patients who need intervention, whether this is via medication adjustments, acute care management, or lifestyle coaching. In this paper, we discuss how an innovative continuous remote care approach has improved outcomes in another deadly pandemic—type 2 diabetes mellitus.

Emerging technologies for the management of type 2 diabetes mellitus

Diabetes mellitus is a global health problem affecting 422 million people worldwide, of which 34.2 million live in the United States alone. Complications due to diabetes can lead to considerable morbidity and mortality related to both microvascular and macrovascular disease. While glycosylated hemoglobin testing is the standard test utilized to evaluate glycemic control, emerging targets like "time in range" and "glycemic variability" often provide more accurate assessments of glycemic fluctuations and have implications for diabetes complications and quality of life. Patients with diabetes face considerable burdens of self-care including frequent glucose monitoring, multiple insulin injections, dietary management, and the need to track daily activities, all of which lead to reduced adherence and psychological burnout. From the provider perspective, limited patient data and access to self-management tools lead to treatment inertia and a reduced ability to help patients achieve and maintain their glycemic goals. In the past few decades, there have been considerable advances in treatment-based technology and technological applications designed to help reduce patient burden and provide tools for better self-management. These advances make real-time clinical data available for clinicians to make necessary changes in treatment regimens. In this review, we discuss the latest emerging technologies available for the management of people with type 2 diabetes mellitus.

Real-world insights from launching remote peer-to-peer mentoring in a safety net healthcare delivery setting

Peer mentors have been proven to improve diabetes outcomes, especially among diverse patients. Delivering peer mentoring via remote strategies (phone, text, mobile applications) is critical, especially in light of the recent pandemic. We conducted a real-world evaluation of a remote diabetes intervention in a safety-net delivery system in New York. We summarized the uptake, content, and pre-post clinical effectiveness for English- and Spanish-speaking participants. Of patients who could be reached, 71% (n = 690/974) were enrolled, and 90% of those (n = 618/690) participated in coaching. Patients and mentors had a mean of 32 check-ins, and each patient set an average of 10 goals. 29% of the participants accessed the program via the smartphone application. Among participants with complete hemoglobin A1c data (n = 179), there was an absolute 1.71% reduction (P < .01). There are multiple lessons for successful implementation of remote peer coaching into settings serving diverse patients, including meaningful patient-mentor matching and addressing social determinants.

Change in Glycemic Control for Patients Enrolled in a Membership-Based Primary Care Program: Longitudinal Observational Study

Background

Both primary care practices based on the chronic care model (CCM) and digital therapeutics have been shown to improve the care of patients with diabetes.

Objective

The aim of this observational study was to examine the change in diabetes control for patients enrolled in a membership-based primary care service that is based on the CCM.

Methods

Using a diabetes registry, we analyzed the change in glycated hemoglobin (HbA_1c) for patients with uncontrolled diabetes mellitus (initial HbA_1c≥9%). All patients had access to a technology-enhanced primary care practice built on the CCM.

Results

The registry included 621 patients diagnosed with uncontrolled diabetes. All patients had at least two HbA_1c measurements, with the average time between the first and last measurement of 1.2 years (SD 0.4). The average starting value of HbA_1c was 10.7, which decreased to 8.7, corresponding to a reduction of 2.03 (P<.001). Secondary analyses showed statistically significant reductions in total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides.

Conclusions

Patients with initially uncontrolled diabetes who undergo care in a technology-enhanced primary care practice based on the CCM have long-term clinically meaningful reductions in HbA_1c.

Remote patient monitoring sustains reductions of hemoglobin A1c in underserved patients to 12 months

AIMS

We sought to determine whether underserved patients enrolled in a statewide remote patient monitoring (RPM) program for diabetes achieve sustained improvements in hemoglobin A_1c at 6 and 12 months and whether those improvements are affected by demographic and clinical variables.

METHODS

Demographic and clinical variables were obtained at baseline, 6 months and 12 months. Baseline HbA1c values were compared with those obtained at 6 and 12 months via paired t-tests. A multivariable regression model was developed to identify patient-level variables associated with HbA_1c change at 12 months.

RESULTS

HbA_1c values were obtained for 302 participants at 6 months and 125 participants at 12 months. Compared to baseline, HbA_1c values were 1.8% (19 mmol/mol) lower at 6 months (p < 0.01) and 1.3% (14 mmol/mol) lower at 12 months (p < 0.01). Reductions at 12 months were consistent across clinical settings. A regression model for change in HbA_1c showed no statistically significant difference for patient age, sex, race, household income, insurance, or clinic type.

CONCLUSIONS

Patients enrolled in RPM had improved diabetes control at 6 and 12 months. Neither clinic type nor sociodemographic variables significantly altered the likelihood that patients would benefit from this type of technology. These results suggest the promise of RPM for delivering care to underserved populations.

Role of Digital Engagement in Diabetes Care Beyond Measurement: Retrospective Cohort Study

BACKGROUND

The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes.

OBJECTIVE

This study investigated the association between digital engagement (operationalized as tagging of behaviors alongside glucose measurements) and the monthly average blood glucose level in persons with type 2 diabetes during the first year of managing their diabetes with a digital chronic disease management platform. We hypothesize that during the first 6 months, blood glucose levels will drop faster and further in patients with increased digital engagement and that difference in outcomes will persist for the remainder of the year. Finally, we hypothesize that disaggregated between- and within-person variabilities in digital engagement will predict individual-level changes in blood glucose levels.

METHODS

This retrospective real-world analysis followed 998 people with type 2 diabetes who regularly tracked their blood glucose levels with the Dario digital therapeutics platform for chronic diseases. Subjects included "nontaggers" (users who rarely or never used app features to notice and track mealtime, food, exercise, mood, and location, n=585) and "taggers" (users who used these features, n=413) representing increased digital engagement. Within- and between-person variabilities in tagging behavior were disaggregated to reveal the association between tagging behavior and blood glucose levels. The associations between an individual's tagging behavior in a given month and the monthly average blood glucose level in the following month were analyzed for quasicausal effects. A generalized mixed piecewise statistical framework was applied throughout.

RESULTS

Analysis revealed significant improvement in the monthly average blood glucose level during the first 6 months (t=-10.01, P<.001), which was maintained during the following 6 months (t=-1.54, P=.12). Moreover, taggers demonstrated a significantly steeper improvement in the initial period relative to nontaggers (t=2.15, P=.03). Additional findings included a within-user quasicausal nonlinear link between tagging behavior and glucose control improvement with a 1-month lag. More specifically, increased tagging behavior in any given month resulted in a 43% improvement in glucose levels in the next month up to a person-specific average in tagging intensity (t=-11.02, P<.001). Above that within-person mean level of digital engagement, glucose levels remained stable but did not show additional improvement with increased tagging (t=0.82, P=.41). When assessed alongside within-person effects, between-person changes in tagging behavior were not associated with changes in monthly average glucose levels (t=1.30, P=.20).

CONCLUSIONS

This study sheds light on the source of the association between user engagement with a diabetes tracking app and the clinical condition, highlighting the importance of within-person changes versus between-person differences. Our findings underscore the need for and provide a basis for a personalized approach to digital health.

Managing New-Onset Type 1 Diabetes During the COVID-19 Pandemic: Challenges and Opportunities

Background: The current COVID-19 pandemic provides an incentive to expand considerably the use of telemedicine for high-risk patients with diabetes, and especially for the management of type 1 diabetes (T1D). Telemedicine and digital medicine also offer critically important approaches to improve access, efficacy, efficiency, and cost-effectiveness of medical care for people with diabetes. Methods: Two case reports are presented where telemedicine was used effectively and safely after day 1 in person patient education. These aspects of the management of new-onset T1D patients (adult and pediatric) included ongoing diabetes education of the patient and family digitally. The patients used continuous glucose monitoring with commercially available analysis software (Dexcom Clarity and Glooko) to generate ambulatory glucose profiles and interpretive summary reports. The adult subject used multiple daily insulin injections; the pediatric patient used an insulin pump. The subjects were managed using a combination of e-mail, Internet via Zoom, and telephone calls. Results: These two cases show the feasibility and effectiveness of use of telemedicine in applications in which we had not used it previously: new-onset diabetes education and insulin dosage management. Conclusions: The present case reports illustrate how telemedicine can be used safely and effectively for new-onset T1D training and education for both pediatric and adult patients and their families. The COVID-19 pandemic has acutely stimulated the expansion of the use of telemedicine and digital medicine. We conclude that telemedicine is an effective approach for the management of patients with new-onset T1D.

Digital Diabetes Care System Observations from a Pilot Evaluation Study in Vietnam

Digital technologies are gaining an important role in the management of patients with diabetes. We assessed clinical outcomes and user satisfaction of incorporating a digital diabetes care system in diabetes clinics of a developing country. The system integrated a wireless blood glucose monitor that communicates data to any smartphone utilizing a patented acoustic data transfer method, a mobile-app, and cloud-based software that stores, analyzes, and presents data. Five hospital endocrinology clinics in Vietnam sequentially recruited all patients willing to join the study, providing they had a smartphone and access to internet connectivity. Face-to-face visits were conducted at baseline and at 12 weeks, with monthly digital visits scheduled in the interim and additional digital visits performed as needed. HbA1c levels were measured at baseline and at 12 weeks (±20 days). The study included 300 patients of whom 279 completed the evaluation. Average glucose levels declined from 170.4 ± 64.6 mg/dL in the first 2 weeks to 150.8 ± 53.2 mg/dL in the last 2 weeks (n = 221; p < 0.001). HbA1c levels at baseline and 12 weeks declined from 8.3% ± 1.9% to 7.6% ± 1.3% (n = 126; p < 0.001). The digital solution was broadly accepted by both patients and healthcare professionals and improved glycemic outcomes. The durability, scalability, and cost-effectiveness of this approach merits further study.