One Drop | Mobile: An Evaluation of Hemoglobin A1c Improvement Linked to App Engagement

Association Between Treatment Adherence and Continuous Glucose Monitoring Outcomes in People With Diabetes Using Smart Insulin Pens in a Real-World Setting

OBJECTIVE

To evaluate the association of insulin injection adherence, smart insulin pen engagement, and glycemic control using real-world data from 16 countries from adults self-administering basal insulin degludec and bolus insulin with a smart insulin pen (NovoPen 6 or NovoPen Echo Plus) alongside continuous glucose monitoring (CGM).

RESEARCH DESIGN AND METHODS

Data were aggregated over 14-day periods. Treatment adherence was defined according to the number of missed basal and missed bolus insulin doses and smart pen engagement according to the number of days with data uploads.

RESULTS

Data from 3,945 adults, including 25,157 14-day periods with ≥70% CGM coverage, were analyzed. On average, 0.2 basal and 6.0 bolus insulin doses were missed over 14 days. The estimated probability of missing at least one basal insulin dose over a 14-day period was 17.6% (95% CI 16.5, 18.7). Missing one basal or bolus insulin dose per 14 days was associated with a significant decrease in percentage of time with glucose levels in range (TIR) (3.9-10.0 mmol/L), of -2.8% (95% CI -3.7, -1.8) and -1.7% (-1.8, -1.6), respectively; therefore, missing two basal or four bolus doses would decrease TIR by >5%. Smart pen engagement was associated positively with glycemic outcomes.

CONCLUSIONS

This combined analysis of real-world smart pen and CGM data showed that missing two basal or four bolus insulin doses over a 14-day period would be associated with a clinically relevant decrease in TIR. Smart insulin pens provide valuable insights into treatment injection behaviors.

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.

Evaluation of Mobile Applications for Patients with Diabetes Mellitus: A Scoping Review

There has been increasing interest in mobile healthcare for diabetes management. However, there remains limited evidence regarding the effectiveness of these mobile applications (apps). This scoping review aimed to evaluate the clinical effectiveness of mobile diabetes management apps. We used the following search terms: "mobile app", "mobile application", and "diabetes". We included only articles written in English and published between January 2016 and August 2021. We identified two, six, and four articles focused on type 1 diabetes, type 2 diabetes, and both diabetes types, respectively. Five, four, and three of these studies reported on the apps' functionality, usability, and both, respectively. Our findings indicated that diabetes mobile apps allowed for convenient user experience and improved blood sugar levels in patients with diabetes. Considering these findings, usability must be comprehensively evaluated by using definitions such as the ISO9241-11 usability definition or the mobile application rating scale (MARS) when developing diabetes-related apps. For the feasibility of diabetes mobile apps, we recommend that HbA1C and self-management be included as evaluation variables. Given the increasing importance of continuous management for patients with diabetes, interventions using mobile apps are bound to become effective tools for patient-led self-management.

Associations of bolus insulin injection frequency and smart pen engagement with glycaemic control in people living with type 1 diabetes

AIM

To evaluate whether both bolus insulin injection frequency and smart pen engagement were associated with changes in glycaemic control, using real-world data from adults with type 1 diabetes (T1D).

MATERIALS AND METHODS

Adults using a smart pen (NovoPen 6) to administer bolus insulin (fast-acting insulin aspart or insulin aspart) alongside continuous glucose monitoring were eligible for inclusion. Smart pen engagement was characterized by number of days with pen data uploads over the previous 14 days. Glycaemic control was evaluated by analysing glucose metrics.

RESULTS

Overall, data from 1194 individuals were analysed. The number of daily bolus injections was significantly associated with time in range (TIR; 3.9-10.0 mmol/L [70-180 mg/dL]; P < 0.0001). Individuals administering, on average, three daily bolus insulin injections had an estimated 11% chance of achieving >70% TIR. The probability of achieving >70% TIR increased with the mean number of daily bolus injections. However, the percentage of TIR was lower on days when individuals administered higher-than-average numbers of injections. The observed mean number of daily bolus injections administered across the study population was lower than the optimal number required to reach glycaemic targets (4.8 injections vs. 6-8 injections). Smart pen engagement was significantly associated with improved TIR.

CONCLUSIONS

Glycaemic control was associated with daily bolus insulin injection frequency and smart pen engagement. A treatment regimen combining an optimal bolus injection strategy, and effective smart pen engagement, may improve glycaemic control among adults with T1D.

Sustained Improvements in Readings in-Range Using an Advanced Bluetooth® Connected Blood Glucose Meter and a Mobile Diabetes App: Real-World Evidence from more than 55,000 People with Diabetes

INTRODUCTION

The OneTouch Verio Reflect^® (OTVR) Blood Glucose Meter features a color range indicator and provides on-meter guidance, insights, and encouragement. Diabetes management is enhanced by the OneTouch Reveal^® (OTR) Mobile App. We sought to provide real-world evidence (RWE) that combining devices improves glycemia.

METHODS

Anonymized glucose and app analytics from more than 55,000 people with diabetes (PWDs) were extracted from a server. Data from their first 14 days using OTVR Meter and OTR App was compared with 14 days prior to 90- and 180-day timepoints using paired within-subject differences.

RESULTS

In people with type 1 (PwT1D) or type 2 diabetes (PwT2D), readings in-range (RIR 70-180 mg/dL) improved by 7.8 percentage points (57.9-65.7%) and 12.0 percentage points (72.8-84.8%), respectively, over 180 days and hyperglycemia (> 180 mg/dL) was reduced by - 8.4 percentage points (37.9-29.5%) and - 12.2 percentage points (26.2-14.1%). RIR improved by > 10 percentage points in 38% of PwT1D and 39% of PwT2D. PwT1D spending > 2 to 4 sessions or > 10 to 20 min per week on the app improved RIR by 7.0 and 8.2 percentage points, respectively. PwT2D spending > 2 to 4 sessions or > 10 to 20 min per week on the app improved RIR by 12.6 and 12.1 percentage points, respectively. In PwT1D or T2D, mean blood glucose reduced by - 14.3 and - 19.8 mg/dL, respectively, from baseline to 180 days, with no clinically meaningful changes in percentage of hypoglycemic readings (< 70 mg/dL). PwT1D 65 years and older performed the most app sessions (10 per week) and improved RIR by 7.9 percentage points. PwT2D 65 years and older spent more time on the app (45 min per week) than PwT2D of any other age and improved RIR by 7.6 percentage points. All glycemic changes were statistically significant (p < 0.0005).

CONCLUSION

Real-world data from more than 55,000 PWDs demonstrates sustained improvements in readings in-range in PWDs using the OneTouch Verio Reflect Blood Glucose Meter and OneTouch Reveal App.

One Drop Improves Productivity for Workers With Type 2 Diabetes: One Drop for Workers With Type 2 Diabetes

OBJECTIVE

Diabetes research on work productivity has been largely cross-sectional and retrospective, with only one known randomized controlled trial (RCT) published, to our knowledge. Secondary analysis of the Fit-One RCT tested the effect of One Drop's digital health program on workplace productivity outcomes, absenteeism, and presenteeism, for employees and specifically for older workers with type 2 diabetes.

METHODS

Analysis of the 3-month Fit-One trial data from employees who have type 2 diabetes explored productivity using logistic analyses and generalized estimating equations.

RESULTS

Treatment and control group comparisons showed that workers ( N = 125) using One Drop see direct benefits to workplace productivity, which leads to productivity savings for employers.

CONCLUSION

This was the first RCT to demonstrate that a mobile health application for managing type 2 diabetes can positively affect productivity at work.

Adherence and Persistence to Insulin Therapy in People with Diabetes: Impact of Connected Insulin Pen Delivery Ecosystem

Diabetes is an increasing public health problem, and insulin is the mainstay for treatment of type 1 diabetes. In type 2 diabetes treatment, insulin therapy is used after oral or other injectable agents become inadequate to achieve glycemic control. Despite the advances in insulin therapy, management of diabetes remains challenging. Numerous studies have reported low adherence and persistence to insulin therapy, which acts as a barrier to successful glycemic control and diabetes management. The aim of this targeted review article is to provide an overview of adherence and persistence to insulin therapy in people with diabetes and to discuss the impact of the emergence of a new connected ecosystem of increasingly sophisticated insulin pens, glucose monitoring systems, telemedicine, and mHealth on diabetes management. With the emergence of a connected diabetes ecosystem, we have entered an era of advanced personalized insulin delivery, which will have the potential to enhance diabetes self-management and clinical management. Early systems promise to unlock the potential to address missed or late bolus insulin delivery, which should help to address non-adherence and non-persistence. Over time, improvements in this ecosystem have the potential to combine insulin data with previously missing contextualized patient data, including meal, glucose, and activity data to support personalized clinical decisions and ultimately revolutionize insulin therapy.

A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes

Diabetes mellitus is a serious chronic disease that affects the blood sugar levels in individuals, with current predictions estimating that nearly 578 million people will be affected by diabetes by 2030. Patients with type II diabetes usually follow a self-management regime as directed by a clinician to help regulate their blood glucose levels. Today, various technology solutions exist to support self-management; however, these solutions tend to be independently built, with little to no research or clinical grounding, which has resulted in poor uptake. In this paper, we propose, develop, and implement a nudge-inspired artificial intelligence (AI)-driven health platform for self-management of diabetes. The proposed platform has been co-designed with patients and clinicians, using the adapted 4-cycle design science research methodology (A4C-DSRM) model. The platform includes (a) a cross-platform mobile application for patients that incorporates a macronutrient detection algorithm for meal recognition and nudge-inspired meal logger, and (b) a web-based application for the clinician to support the self-management regime of patients. Further, the platform incorporates behavioral intervention techniques stemming from nudge theory that aim to support and encourage a sustained change in patient lifestyle. Application of the platform has been demonstrated through an illustrative case study via two exemplars. Further, a technical evaluation is conducted to understand the performance of the MDA to meet the personalization requirements of patients with type II diabetes.

J. Schreiber L, Wallace EJ, Wylie R, O'Sullivan J, Dolan EB, Duffy GP. Medical devices, smart drug delivery, wearables and technology for the treatment of Diabetes Mellitus

Diabetes mellitus refers to a group of metabolic disorders which affect how the body uses glucose impacting approximately 9% of the population worldwide. This review covers the most recent technological advances envisioned to control and/or reverse Type 1 diabetes mellitus (T1DM), many of which will also prove effective in treating the other forms of diabetes mellitus. Current standard therapy for T1DM involves multiple daily glucose measurements and insulin injections. Advances in glucose monitors, hormone delivery systems, and control algorithms generate more autonomous and personalised treatments through hybrid and fully automated closed-loop systems, which significantly reduce hypo- and hyperglycaemic episodes and their subsequent complications. Bi-hormonal systems that co-deliver glucagon or amylin with insulin aim to reduce hypoglycaemic events or increase time spent in target glycaemic range, respectively. Stimuli responsive materials for the controlled delivery of insulin or glucagon are a promising alternative to glucose monitors and insulin pumps. By their self-regulated mechanism, these "smart" drugs modulate their potency, pharmacokinetics and dosing depending on patients' glucose levels. Islet transplantation is a potential cure for T1DM as it restores endogenous insulin and glucagon production, but its use is not yet widespread due to limited islet sources and risks of chronic immunosuppression. New encapsulation strategies that promote angiogenesis and oxygen delivery while protecting islets from recipients' immune response may overcome current limiting factors.

Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study

Background

Personalized feedback is an effective behavior change technique frequently incorporated into mobile health (mHealth) apps. Innovations in data science create opportunities for leveraging the wealth of user data accumulated by mHealth apps to generate personalized health forecasts. One Drop’s digital program is one of the first to implement blood glucose forecasts for people with type 2 diabetes. The impact of these forecasts on behavior and glycemic management has not been evaluated to date.

Objective

This study sought to evaluate the impact of exposure to blood glucose forecasts on blood glucose logging behavior, average blood glucose, and percentage of glucose points in range.

Methods

This retrospective cohort study examined people with type 2 diabetes who first began using One Drop to record their blood glucose between 2019 and 2021. Cohorts included those who received blood glucose forecasts and those who did not receive forecasts. The cohorts were compared to evaluate the effect of exposure to blood glucose forecasts on logging activity, average glucose, and percentage of glucose readings in range, after controlling for potential confounding factors. Data were analyzed using analysis of covariance (ANCOVA) and regression analyses.

Results

Data from a total of 1411 One Drop users with type 2 diabetes and elevated baseline glucose were analyzed. Participants (60.6% male, 795/1311; mean age 50.2 years, SD 11.8) had diabetes for 7.1 years on average (SD 7.9). After controlling for potential confounding factors, blood glucose forecasts were associated with more frequent blood glucose logging (P=.004), lower average blood glucose (P<.001), and a higher percentage of readings in range (P=.03) after 12 weeks. Blood glucose logging partially mediated the relationship between exposure to forecasts and average glucose.

Conclusions

Individuals who received blood glucose forecasts had significantly lower average glucose, with a greater amount of glucose measurements in a healthy range after 12 weeks compared to those who did not receive forecasts. Glucose logging was identified as a partial mediator of the relationship between forecast exposure and week-12 average glucose, highlighting a potential mechanism through which glucose forecasts exert their effect. When administered as a part of a comprehensive mHealth program, blood glucose forecasts may significantly improve glycemic management among people living with type 2 diabetes.

New digital health technologies for insulin initiation and optimization for people with type 2 diabetes

OBJECTIVE

The health and economic burden of type 2 diabetes (T2D) is of global significance. Many people with T2D eventually need insulin to help reduce their risk of serious associated complications. However, barriers in initiating and/or optimizing insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigate how new and future technologies may provide opportunities to help overcome barriers to insulin initiation and/or optimization.

METHODS

A focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support insulin initiation and/or optimization were identified by manually filtering over 300 publications and conference abstracts.

RESULTS

Most software tools have been developed for a smartphone platform. At present, published data suggest that use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care with additional benefits such as reduced healthcare provider (HCP) time burden and improved diabetes knowledge. However, there remains a paucity of good quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin use.

CONCLUSIONS

New digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, titration advice, and records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve titration and treatment adherence, resulting in better outcomes for people with diabetes.

Standardized evaluation of the quality and persuasiveness of mobile health applications for diabetes management

This study evaluates diabetes self-management mobile health applications available from European app stores with respect to quality, concordance with recommended self-management tasks and implementation of persuasive system design principles. The European Play Store and Apple App Store were systematically searched and relevant apps were tested. Two raters independently assessed app quality using the Mobile Application Rating Scale and conducted a content analysis of provided persuasive system design principles and self-management tasks. A total of 2,269 mobile health applications were identified and 120 could be included in the evaluation. The overall quality was rated as moderate M = 3.20 (SD = 0.39, min = 2.31, max = 4.62), with shortcomings in the subcategories of engagement (M = 2.80, SD = 0.67) and information quality (M = 2.26, SD = 0.48). Scientific evidence is available for 8% of the apps. The reviewed apps implemented a median of three persuasive system design principles (range 0-15) and targeted a median of 4.5 (range 1-8) self-management tasks, however, with a lack of information about psychosocial coping strategies. Most available diabetes self-management apps lack a scientific evidence base. Persuasive system design features are underrepresented and may form a promising tool to improve app quality. Furthermore, the interaction of physical and behavioral health should be improved in existing diabetes self-management mobile health applications.

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.

Managing Diabetes Using Mobiab: Long Term Case Study of the Impact of a Mobile App on Self-Management (Preprint)

Background

This paper describes the development of a mobile app for diabetes mellitus (DM) control and self-management and presents the results of long-term usage of this system in the Czech Republic. DM is a chronic disease affecting large numbers of people worldwide, and this number is continuously increasing. There is massive potential to increase adherence to self-management of DM with the use of smartphones and digital therapeutics interventions.

Objective

This study aims to describe the process of development of a mobile app, called Mobiab, for DM management and to investigate how individual features are used and how the whole system benefits its long-term users. Using at least 1 year of daily records from users, we analyzed the impact of the app on self-management of DM.

Methods

We have developed a mobile app that serves as an alternative form to the classic paper-based protocol or diary. The development was based on cooperation with both clinicians and people with DM. The app consists of independent individual modules. Therefore, the user has the possibility to use only selected features that they find useful. Mobiab was available free of charge on Google Play Store from mid-2014 until 2019. No targeted recruitment was performed to attract users.

Results

More than 500 users from the Czech Republic downloaded and signed up for the mobile app. Approximately 80% of the users used Mobiab for less than 1 week. The rest of the users used it for a longer time and 8 of the users produced data that were suitable for long-term analysis. Additionally, one of the 8 users provided their medical records, which were compared with the gathered data, and the improvements in their glucose levels and overall metabolic stability were consistent with the way in which the mobile app was used.

Conclusions

The results of this study showed that the usability of a DM-centered self-management smartphone mobile app and server-based systems could be satisfactory and promising. Nonetheless, some better ways of motivating people with diabetes toward participation in self-management are needed. Further studies involving a larger number of participants are warranted to assess the effect on long-term diabetes management.

Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials

OBJECTIVE

Guidance is needed on studying engagement and treatment effects in digital health interventions, including levels required for benefit. We evaluated multiple analytic approaches for understanding the association between engagement and clinical outcomes.

MATERIALS AND METHODS

We defined engagement as intervention participants' response rate to interactive text messages, and considered moderation, standard regression, mediation, and a modified instrumental variable (IV) analysis to investigate the relationship between engagement and clinical outcomes. We applied each approach to two randomized controlled trials featuring text message content in the intervention: REACH (Rapid Encouragement/Education and Communications for Health), which targeted diabetes, and VERB (Vanderbilt Emergency Room Bundle), which targeted hypertension.

RESULTS

In REACH, the treatment effect on hemoglobin A1c was estimated to be -0.73% (95% CI: [-1.29, -0.21]; P = 0.008), and in VERB, the treatment effect on systolic blood pressure was estimated to be -10.1 mmHg (95% CI: [-17.7, -2.8]; P = 0.007). Only the IV analyses suggested an effect of engagement on outcomes; the difference in treatment effects between engagers and non-engagers was -0.29% to -0.51% in the REACH study and -1.08 to -3.25 mmHg in the VERB study.

DISCUSSION

Standard regression and mediation have less power than a modified IV analysis, but the IV approach requires specification of assumptions. This is the first review of the strengths and limitations of various approaches to evaluating the impact of engagement on outcomes.

CONCLUSIONS

Understanding the role of engagement in digital health interventions can help reveal when and how these interventions achieve desired outcomes.

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.

The Effects of Continuous Usage of a Diabetes Management App on Glycemic Control in Real-world Clinical Practice: Retrospective Analysis

Background

The efficacy of digital technology in improving diabetes management has typically been demonstrated through studies such as randomized controlled trials, which have reported a steeper reduction in hemoglobin A_1c (HbA_1c) values for patients who adopted a digital solution. However, evidence from real-world clinical practice is still limited.

Objective

This study aimed to evaluate the effectiveness of digital interventions by tracking HbA_1c improvements over 1 year in real-world clinical settings.

Methods

Patients used the Health2Sync mobile app to track self-measured outcomes and communicate with health care professionals (HCPs). HCPs used the web-based Patient Management Platform to monitor patient data, view test results from clinical laboratories, and communicate with patients. Patients who have been onboarded for at least 13 months and have consecutive HbA_1c findings for 5 quarters were included in the analysis. They were then stratified into 3 groups (high, mid, and low retention) based on their level of use of Health2Sync in the first 6 months of onboarding. A mixed model was built to compare the slopes of the rate of reduction in HbA_1c among the groups. In addition, these patients’ retention on the app from the seventh to the 12th month was verified through multiple comparisons.

Results

A sample of 2036 users was included in the analysis. With the mixed model coefficient estimates, we found that app users had significant HbA_1c percentage reductions as the passed quarter count increased (t=–9.869; P<.001), and that effectiveness increased in the high (t=–5.173) and mid retention (t=–6.620) groups as the interaction effects were significantly negative compared to that in the low retention group (P<.001) in the passed quarter count. The low retention group also had the highest average HbA_1c value at the end of 13 months (high: 7.01%, SD 1.02%; mid: 6.99%, SD 1.00%; low: 7.17%, SD 1.14%) (Bonferroni correction: high vs low, P=.07; mid vs low, P=.02; high vs mid, P>.99). The level of use of the app remained consistent in the seventh to the 12th month after onboarding (high: 5.23 [SD 1.37] months, mid: 2.43 [SD 1.68] months, low: 0.41 [SD 0.97] months) (P<.001).

Conclusions

Our analysis shows that continuous usage of the diabetes management app is associated with better glycemic control in real-world clinical practice. Further studies are required to reveal the efficacy for specific diabetes types and to observe effects beyond 1 year.

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.

Electrochemical glucose sensors in diabetes management: an updated review (2010-2020)

While over half a century has passed since the introduction of enzyme glucose biosensors by Clark and Lyons, this important field has continued to be the focus of immense research activity. Extensive efforts during the past decade have led to major scientific and technological innovations towards tight monitoring of diabetes. Such continued progress toward advanced continuous glucose monitoring platforms, either minimal- or non-invasive, holds considerable promise for addressing the limitations of finger-prick blood testing toward tracking glucose trends over time, optimal therapeutic interventions, and improving the life of diabetes patients. However, despite these major developments, the field of glucose biosensors is still facing major challenges. The scope of this review is to present the key scientific and technological advances in electrochemical glucose biosensing over the past decade (2010-present), along with current obstacles and prospects towards the ultimate goal of highly stable and reliable real-time minimally-invasive or non-invasive glucose monitoring. After an introduction to electrochemical glucose biosensors, we highlight recent progress based on using advanced nanomaterials at the electrode-enzyme interface of three generations of glucose sensors. Subsequently, we cover recent activity and challenges towards next-generation wearable non-invasive glucose monitoring devices based on innovative sensing principles, alternative body fluids, advanced flexible materials, and novel platforms. This is followed by highlighting the latest progress in the field of minimally-invasive continuous glucose monitoring (CGM) which offers real-time information about interstitial glucose levels, by focusing on the challenges toward developing biocompatible membrane coatings to protect electrochemical glucose sensors against surface biofouling. Subsequent sections cover new analytical concepts of self-powered glucose sensors, paper-based glucose sensing and multiplexed detection of diabetes-related biomarkers. Finally, we will cover the latest advances in commercially available devices along with the upcoming future technologies.

One Drop App With an Activity Tracker for Adults With Type 1 Diabetes: Randomized Controlled Trial

BACKGROUND

In 2017, mobile app support for managing diabetes was available to 64% of the global population of adults with diabetes. One Drop's digital therapeutics solution includes an evidence-based mobile app with global reach, a Bluetooth-connected glucometer, and in-app coaching from Certified Diabetes Educators. Among people with type 1 diabetes and an estimated hemoglobin A_1c level≥7.5%, using One Drop for 3 months has been associated with an improved estimated hemoglobin A_1c level of 22.2 mg/dL (-0.80%). However, the added value of integrated activity trackers is unknown.

OBJECTIVE

We conducted a pragmatic, remotely administered randomized controlled trial to evaluate One Drop with a new-to-market activity tracker against One Drop only on the 3-month hemoglobin A_1c level of adults with type 1 diabetes.

METHODS

Social media advertisements and online newsletters were used to recruit adults (≥18 years old) diagnosed (≥1 year) with T1D, naïve to One Drop's full solution and the activity tracker, with a laboratory hemoglobin A_1c level≥7%. Participants (N=99) were randomized to receive One Drop and the activity tracker or One Drop only at the start of the study. The One Drop only group received the activity tracker at the end of the study. Multiple imputation, performed separately by group, was used to correct for missing data. Analysis of covariance models, controlling for baseline hemoglobin A_1c, were used to evaluate 3-month hemoglobin A_1c differences in intent-to-treat (ITT) and per protocol (PP) analyses.

RESULTS

The enrolled sample (N=95) had a mean age of 41 (SD 11) years, was 73% female, 88% White, diagnosed for a mean of 20 (SD 11) years, and had a mean hemoglobin A_1c level of 8.4% (SD 1.2%); 11% of the participants did not complete follow up. Analysis of covariance assumptions were met for the ITT and PP models. In ITT analysis, participants in the One Drop and activity tracker condition had a significantly lower 3-month hemoglobin A_1c level (mean 7.9%, SD 0.60%, 95% CI 7.8-8.2) than that of the participants in the One Drop only condition (mean 8.4%, SD 0.62%, 95% CI 8.2-8.5). In PP analysis, participants in the One Drop and activity tracker condition also had a significantly lower 3-month hemoglobin A_1c level (mean 7.9%, SD 0.59%, 95% CI 7.7-8.1) than that of participants in the One Drop only condition (mean 8.2%, SD 0.58%, 95% CI 8.0-8.4).

CONCLUSIONS

Participants exposed to One Drop and the activity tracker for the 3-month study period had a significantly lower 3-month hemoglobin A_1c level compared to that of participants exposed to One Drop only during the same timeframe. One Drop and a tracker may work better together than alone in helping people with type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03459573; https://clinicaltrials.gov/ct2/show/NCT03459573.

Artificial Intelligence: The Future for Diabetes Care

Artificial intelligence (AI) is a fast-growing field and its applications to diabetes, a global pandemic, can reform the approach to diagnosis and management of this chronic condition. Principles of machine learning have been used to build algorithms to support predictive models for the risk of developing diabetes or its consequent complications. Digital therapeutics have proven to be an established intervention for lifestyle therapy in the management of diabetes. Patients are increasingly being empowered for self-management of diabetes, and both patients and health care professionals are benefitting from clinical decision support. AI allows a continuous and burden-free remote monitoring of the patient's symptoms and biomarkers. Further, social media and online communities enhance patient engagement in diabetes care. Technical advances have helped to optimize resource use in diabetes. Together, these intelligent technical reforms have produced better glycemic control with reductions in fasting and postprandial glucose levels, glucose excursions, and glycosylated hemoglobin. AI will introduce a paradigm shift in diabetes care from conventional management strategies to building targeted data-driven precision care.

International ResearchKit App for Women with Menstrual Pain: Development, Access, and Engagement

BACKGROUND

Primary dysmenorrhea is a common condition in women of reproductive age. A previous app-based study undertaken by our group demonstrated that a smartphone app supporting self-acupressure introduced by a health care professional can reduce menstrual pain.

OBJECTIVE

This study aims to evaluate whether a specific smartphone app is effective in reducing menstrual pain in 18- to 34-year-old women with primary dysmenorrhea in a self-care setting. One group of women has access to the full-featured study app and will be compared with 2 control groups who have access to fewer app features. Here, we report the trial design, app development, user access, and engagement.

METHODS

On the basis of the practical implications of the previous app-based study, we revised and reengineered the study app and included the ResearchKit (Apple Inc) framework. Behavior change techniques (BCTs) were implemented in the app and validated by expert ratings. User access was estimated by assessing recruitment progress over time. User evolution and baseline survey respondent rate were assessed to evaluate user engagement.

RESULTS

The development of the study app for a 3-armed randomized controlled trial required a multidisciplinary team. The app is accessible for the target population free of charge via the Apple App Store. In Germany, within 9 months, the app was downloaded 1458 times and 328 study participants were recruited using it without external advertising. A total of 98.27% (5157/5248) of the app-based baseline questions were answered. The correct classification of BCTs used in the app required psychological expertise.

CONCLUSIONS

Conducting an innovative app study requires multidisciplinary effort. Easy access and engagement with such an app can be achieved by recruitment via the App Store. Future research is needed to investigate the determinants of user engagement, optimal BCT application, and potential clinical and self-care scenarios for app use.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03432611; https://clinicaltrials.gov/ct2/show/NCT03432611 (Archived by WebCite at http://www.webcitation.org/75LLAcnCQ).

What Do Adults with Type 2 Diabetes Want from the "Perfect" App? Results from the Second Diabetes MILES: Australia (MILES-2) Study

Background: We investigated what Australian adults with type 2 diabetes (T2D) want from the "perfect" diabetes self-management application. Methods: Adults with T2D completed a national online survey including an open-ended question: "If you were describing the perfect app to help you manage your diabetes, what would it do?" Qualitative responses were subjected to thematic analysis. Results: Of the 339 participants who provided usable responses, 153 (45%) were women, the mean age was 58 ± 10 years, and 139 participants (41%) managed their diabetes with insulin. Two primary themes emerged. First, participants expressed a desire for assistance with practical aspects of diabetes self-management to improve, and reduce the cognitive burden of, self-management; this included tracking and visualizing multiple sources of data, using data to inform automated, personalized coaching, reminders, and alarms, and automating upload and linking of data through connected devices. Second, they desired assistance with psychological and emotional aspects of diabetes self-management; this included ongoing encouragement and motivation, help with stress management or negative emotions, and complementing existing health care by facilitating interconnectivity with health professionals. Conclusions: Our findings suggest that the clear desire of people with type 2 diabetes is for the "perfect app" to reduce not only the practical, but also the cognitive and emotional burden of diabetes self-management. They provide further evidence that understanding the desires of people living with diabetes needs to be the first step in app development to ensure that apps provide features, support, and benefits that people with diabetes value.

Virtual Coaching to Enhance Diabetes Care

Rates of diabetes are increasing worldwide and there is not a sufficient clinical workforce to care for these patients. Diabetes-related apps are a feasible way to provide diabetes education to large numbers of people with diabetes but attrition rates are high. Apps enhanced by virtual coaching may be a way to circumnavigate these problems. Virtual coaches are able to address common treatment barriers and other health disparities by providing data-driven individualized support in real time, at any time of day, and from anywhere. Enhanced glycemic benefits have been seen in those who use an app plus virtual coaching versus those who use an app alone, along with clinically meaningful behavior change, psychosocial effects, prolonged engagement, and high levels of satisfaction with the system. More research needs to be done to determine the longitudinal and widespread effects of virtual coaching in different populations.

A Mobile Lifestyle Management Program (GlycoLeap) for People With Type 2 Diabetes: Single-Arm Feasibility Study

Background

Singapore’s current prevalence of diabetes exceeds 13.6%. Although lifestyle modification can be effective for reducing the risks for complications of type 2 diabetes mellitus (T2DM), traditional lifestyle interventions are often difficult to administer in the primary care setting due to limited resources. Mobile health apps can address these limitations by offering low-cost, adaptable, and accessible platforms for disseminating lifestyle management interventions.

Objective

Using the RE-AIM evaluation framework, this study assessed the potential effectiveness and feasibility of GlycoLeap, a mobile lifestyle management program for people with T2DM, as an add-on to standard care.

Methods

This single-arm feasibility study recruited 100 patients with T2DM and glycated hemoglobin (HbA_1c) levels of ≥7.5% from a single community health care facility in Singapore. All participants were given access to a 6-month mobile lifestyle management program, GlycoLeap, comprising online lessons and the Glyco mobile phone app with a health coaching feature. The GlycoLeap program was evaluated using 4 relevant dimensions of the RE-AIM framework: (1) reach (percentage who consented to participate out of all patients approached), (2) effectiveness (percentage point change in HbA_1c [primary outcome] and weight loss [secondary outcome]), (3) implementation (program engagement as assessed by various participatory metrics), and (4) maintenance (postintervention user satisfaction surveys to predict the sustainability of GlycoLeap). Participants were assessed at baseline and at follow-up (≥12 weeks after starting the intervention).

Results

A total of 785 patients were approached of whom 104 consented to participate, placing the reach at 13.2%. Four were excluded after eligibility screening, and 100 patients were recruited. Program engagement (implementation) started out high but decreased with time for all evaluated components. Self-reported survey data suggest that participants monitored their blood glucose on more days in the past week at follow-up compared to baseline (P<.001) and reported positive changes to their diet due to app engagement (P<.001) (implementation). Primary outcome data were available for 83 participants. Statistically significant improvements were observed for HbA_1c (–1.3 percentage points, P<.001) with greater improvements for those who logged their weight more often (P=.007) (effectiveness). Participants also had a 2.3% reduction in baseline weight (P<.001) (effectiveness). User satisfaction was high with 74% (59/80) and 79% (63/80) of participants rating the app good or very good and claiming that they would probably or definitely recommend the app to others, respectively (maintenance).

Conclusions

Although measures of program engagement decreased with time, clinically significant improvements in HbA_1c were achieved with the potential for broader implementation. However, we cannot rule out that these improvements were due to factors unrelated to GlycoLeap. Therefore, we would recommend evaluating the effectiveness and cost effectiveness of GlycoLeap using a randomized controlled trial of at least 12 months.

Trial Registration

ClinicalTrials.gov NCT03091517; https://clinicaltrials.gov/ct2/show/NCT03091517 (Archived by WebCite at http://www.webcitation.org/77rNqhwRn)

Seamless recording of glucometer measurements among older experienced diabetic patients - A study of perception and usability

Self-measurement and documentation of blood-glucose are critical elements of diabetes management, particularly in regimes including insulin. In this study, we analyze the usability of iBG-STAR, the first blood glucose meter connectable to a smartphone. This technology records glucometer measurements, removing the burden of documentation from diabetic patients. This study assesses the potential for implementation of iBG-STAR in routine care. Twelve long-term diabetic patients (4 males; median age of 66.5 years) were enrolled in the study. N = 4/12 reported diabetic polyneuropathy. Reported subjective mental workload for all tasks related to iBG-STAR was on average lower than 12 points, corresponding to the verbal code 'nearly no effort needed'. A "Post Study System Usability Questionnaire", evaluated the glucometer at an average value of 2.06 (SD = 1.02) on a 7-Likert-scale (1 = 'I fully agree' to 7 = 'I completely disagree') for usability. These results represent a positive user-experience. Patients with polyneuropathy may experience physical difficulties in completing the tasks, thereby affecting usability. Technologically savvy patients (n = 6) with a positive outlook on diabetes assessed the product as a suitable tool for themselves and would recommend to other diabetic patients. The main barrier to regular use was treating physicians' inability to retrieve digitally recorded data. This barrier was due to a shortcoming in interoperability of mobile devices and medical information systems.

Connecting Smartphone and Wearable Fitness Tracker Data with a Nationally Used Electronic Health Record System for Diabetes Education to Facilitate Behavioral Goal Monitoring in Diabetes Care: Protocol for a Pragmatic Multi-Site Randomized Trial

Background

Mobile and wearable technology have been shown to be effective in improving diabetes self-management; however, integrating data from these technologies into clinical diabetes care to facilitate behavioral goal monitoring has not been explored.

Objective

The objective of this paper is to report on a study protocol for a pragmatic multi-site trial along with the intervention components, including the detailed connected health interface. This interface was developed to integrate patient self-monitoring data collected from a wearable fitness tracker and its companion smartphone app to an electronic health record system for diabetes self-management education and support (DSMES) to facilitate behavioral goal monitoring.

Methods

A 3-month multi-site pragmatic clinical trial was conducted with eligible patients with diabetes mellitus from DSMES programs. The Chronicle Diabetes system is currently freely available to diabetes educators through American Diabetes Association–recognized DSMES programs to set patient nutrition and physical activity goals. To integrate the goal-setting and self-monitoring intervention into the DSMES process, a connected interface in the Chronicle Diabetes system was developed. With the connected interface, patient self-monitoring information collected from smartphones and wearable fitness trackers can facilitate educators’ monitoring of patients’ adherence to their goals. Feasibility outcomes of the 3-month trial included hemoglobin A_1c levels, weight, and the usability of the connected system.

Results

An interface designed to connect data from a wearable fitness tracker with a companion smartphone app for nutrition and physical activity self-monitoring into a diabetes education electronic health record system was successfully developed to enable diabetes educators to facilitate goal setting and monitoring. A total of 60 eligible patients with type 2 diabetes mellitus were randomized into either group 1) standard diabetes education or 2) standard education enhanced with the connected system. Data collection for the 3-month pragmatic trial is completed. Data analysis is in progress.

Conclusions

If results of the pragmatic multi-site clinical trial show preliminary efficacy and usability of the connected system, a large-scale implementation trial will be conducted.

Trial Registration

ClinicalTrials.gov NCT02664233; https://clinicaltrials.gov/ct2/show/NCT02664233 (Archived by WebCite at http://www.webcitation.org/6yDEwXHo5)