Managing diabetes in the digital age

Telehealth Technologies in Diabetes Self-management and Education

BACKGROUND

The coronavirus pandemic of 2019 (COVID-19) forced worldwide recognition and implementation of telehealth as a means of providing continuity of care by varied health care institutions. Diabetes is a global health threat with rates that continue to accelerate, thereby causing an increased need for clinicians to provide diabetes care and education to keep up with demand. Utilizing technology to provide education via phone/smartphone, video/audio, web, text message, mobile apps, or a combination of these methods can help improve patient access and clinical outcomes, cut costs, and close gaps in care.

METHODS

While numerous publications have summarized the various tools and technologies available for capturing remote clinical data and their relevance to diabetes care and self-management, this review focuses on self-educational telehealth tools available for diabetes self-management, their advantages and disadvantages, and factors that need to be considered prior to implementation. Recent relevant studies indexed by PubMed were included.

RESULTS

The widespread use and popularity of phones/smartphones, tablets, computers, and the Internet by patients of all age groups, cultures, socioeconomic and geographic areas allow for increased outreach, flexibility, and engagement with diabetes education, either in combination or as an adjunct to traditional in-person visits. Demonstrated benefits of using health technologies for diabetes self-management education include improved lifestyle habits, reduced hemoglobin A1C levels, decreased health care costs, and better medication adherence. Potential drawbacks include lack of regulation, need for staff training on methodologies used, the requirement for patients to be tech savvy, privacy concerns, lag time with technology updates/glitches, and the need for more long-term research data on efficacy.

CONCLUSIONS

Telehealth technologies for diabetes self-education improve overall clinical outcomes and have come a long way. With increasing numbers of patients with diabetes, it is expected that more optimal and user-friendly methodologies will be developed to fully engage and help patients communicate with their physicians.

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.

Patterns and Predictors Associated With Long-Term Glycemic Control in Pediatric and Young Adult Patients with Type 1 Diabetes

BACKGROUND

The development of diabetes technology is rapid and requires education and resources to be successfully implemented in diabetes care management.

METHOD

In an observational study, we evaluated the use of advanced diabetes technology, resource utilization, and glycemic control. The study population was 725 individuals with type 1 diabetes (T1D) living in Region Halland, Sweden. The study cohort was followed for 7 years between 2013 and 2019.

RESULTS

Children aged 0 to 17 years were associated with significantly better glucose control than young adults aged 18 to 25 years. The mean HbA1c in children and young adults was 53 mmol/mol (7.0%) compared to 61 mmol/mol (7.7%) (P < .0001), respectively. Comorbidities such as attention deficit hyperactivity disorder (ADHD), autism, and coelic disease were associated with higher HbA1c. All groups, regardless of age and comorbidity, showed a positive effect on glucose control after visiting a dietitian or psychologist. Differences were found between the age groups in terms of more use of advanced diabetes technology and more frequent visits to a physician in children compared to young adults.

CONCLUSIONS

More frequent visits to physicians, and a visit to dietitians, and psychologists were associated with improved glucose control in individuals with T1D 0 to 25 years. Increased resources, including access to more advanced technologies, may be required in young adults with T1D.

Support Provided by Caregivers for Community-Dwelling Diabetic Hispanic Adults with Intellectual Disabilities and Comorbid Conditions

Diabetes is an age-related chronic health condition and a major public health concern. Diabetes is one of the significant causes of morbidity and mortality and a major contributing factor to dementia. Recent research reveals that Hispanic Americans are at an increased risk of chronic conditions such as diabetes, dementia, and obesity. Recent research also revealed that diabetes develops at least ten years earlier in Hispanics and Latinos than in neighboring non-Hispanic whites. Furthermore, the management of diabetes and providing necessary/timely support is a challenging task for healthcare professionals. Caregiver support is an emerging area of research for people with diabetes, mainly family caregiver support work for Hispanic and Native Americans. Our article discusses several aspects of diabetes, factors associated with diabetes among Hispanics, its management, and how caregivers can support individuals with diabetes.

Digital interventions self-management education for type 1 and 2 diabetes: A systematic review and meta-analysis

OBJECTIVE

To describe and assess digital health-led diabetes self-management education and support (DSMES) effectiveness in improving glycosylated hemoglobin, diabetes knowledge, and health-related quality of life (HrQoL) of Type 1 and 2 Diabetes in the past 10 years.

DESIGN

Systematic Review and Meta-Analysis. The protocol was registered on PROSPERO registration number CRD42019139884.

DATA SOURCES

PubMed, EMBASE, Cochrane library, Web of Science, and Scopus between January 2010 and August 2019. Study Selection and Appraisal: Randomized control trials of digital health-led DSMES for Type 1 (T1DM) or 2 (T2DM) diabetes compared to usual care were included. Outcomes were change in HbA1c, diabetes knowledge, and HrQoL. Cochrane Risk of Bias 2.0 tool was used to assess bias and GRADEpro for overall quality. The analysis involved narrative synthesis, subgroup and pooled meta-analyses.

RESULTS

From 4286 articles, 39 studies (6861 participants) were included. Mean age was 51.62 years, range (13-70). Meta-analysis revealed intervention effects on HbA1c for T2DM with difference in means (MD) from baseline -0.480% (-0.661, -0.299), I²75% (6 months), -0.457% (-0.761, -0.151), I² 81% (12 months), and for T1DM -0.41% (-1.022, 0.208) I² 83% (6 months), -0.03% (-0.210, 0.142) I² 0% (12 months). Few reported HrQoL with Hedges' g 0.183 (-0.039, 0.405), I² 0% (6 months), 0.153 (-0.060, 0.366), I² 0% (12 months) and diabetes knowledge with Hedges' g 1.003 (0.068, 1.938), I² 87% (3 months).

CONCLUSION

Digital health-led DSMES are effective in improving HbA1c and diabetes knowledge, notably for T2DM. Research shows non-significant changes in HrQoL. Intervention effect on HbA1c was more impressive if delivered through mobile apps or patient portals. Further research is needed on the impact of DSMES on these outcomes, especially for newly diagnosed diabetes patients.

Improved Methods for Mid-Term Blood Glucose Level Prediction Using Dietary and Insulin Logs

Background and Objectives: The daily lifestyle management of diabetes requires accurate predictions of the blood glucose level between meals. The objective of this study was to improve the accuracy achieved by previous work, especially on the mid-term, i.e., 120 to 180 min prediction horizons, for insulin-dependent patients. Materials and Methods: An absorption model-based method is proposed to train an artificial neural network with the bolus and basal insulin dosing and timing, the baseline blood glucose level, the maximal glucose infusion rate, and the total carbohydrate content as parameters. The approach was implemented in various algorithmic setups, and it was validated on data from a small-scale clinical trial with continuous glucose monitoring. Results: Root mean square error results for the mid-term horizons are 1.72 mmol/L (120 min) and 1.95 mmol/L (180 min). The accuracy of the proposed model measured on the clinical data is better than the accuracy reported by any other currently available and comparable models. Conclusions: A relatively short (ca. two weeks) training sample of a continuous glucose monitor and dietary/insulin log is sufficient to provide accurate predictions. For the outpatient application in practice, a hybrid model is proposed that combines the present mid-term method with the authors’ previous work for short-term predictions.

Comparing Two Commercially Available Diabetes Apps to Explore Challenges in User Engagement: Randomized Controlled Feasibility Study

BACKGROUND

Diabetes apps represent a promising addition to face-to-face self-management interventions, which can be time and resource intensive. However, few randomized controlled trials have evaluated the efficacy of diabetes apps, in particular as a stand-alone intervention without additional clinical support.

OBJECTIVE

We used a feasibility randomized trial design to investigate differences in user engagement between 2 commercially available apps (free versions of Glucose Buddy and mySugr) over 2 weeks in adults with type 2 diabetes. Feasibility was assessed based on recruitment uptake, adherence to the diabetes apps, and follow-up rates. We also hypothesized that the diabetes app mySugr would demonstrate higher user engagement at follow-up due to its use of gamification. We also predicted higher user engagement would be associated with improved self-care behaviors and illness beliefs.

METHODS

Adults with type 2 diabetes attending outpatient diabetes clinics in Auckland were recruited and randomized (1:1 without blinding) to use either the Glucose Buddy or mySugr diabetes apps. User engagement, self-care behaviors, and illness beliefs were measured 2 weeks after baseline. Spearman rank correlations, Mann-Whitney tests, and Wilcoxon signed-rank tests were used to explore associations between the outcome measures and to investigate possible changes between and within groups. Six participants were interviewed to further explore acceptability and usability.

RESULTS

In total, 58 participants (29 per group) completed the 2-week follow-up, of whom only 38 reported using the apps (Glucose Buddy: n=20; mySugr: n=18). Both groups reported low engagement (Glucose Buddy: median 4 days; mySugr: median 6.5 days; P=.06; use for both groups: median 10 minutes). No changes were observed in self-care or illness beliefs in either group. Out of the self-care behaviors, only blood glucose testing was significantly associated with minutes of app use (P=.02). The interviews suggested that although both apps were deemed acceptable, they were generally viewed as time-consuming and too complicated to use.

CONCLUSIONS

Low engagement with both Glucose Buddy and mySugr reflect the challenges associated with engaging users with diabetes apps. Due to low engagement and loss to follow-up, the changes in outcome measures should be interpreted with caution. The results highlight the need for more clinical support as well as involvement from end users and behavior change specialists in order to incorporate evidence-based behavior change techniques to motivate and provide value to users.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry ACTRN12618000424202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374671.

"Counting Carbs to Be in Charge": A Comparison of an Internet-Based Education Module With In-Class Education in Adolescents With Type 1 Diabetes

Carbohydrate counting is an essential component of type 1 diabetes education but can be difficult for adolescents to learn. Because adolescents are avid users of technology, an Internet-based education module was compared with an in-class education session in terms of carbohydrate counting accuracy in adolescents with type 1 diabetes. Adolescent participants displayed increased carbohydrate counting accuracy after attending an in-class education session compared with an Internet-based education module. These results suggest that online education is best reserved as an adjunctive therapy to in-class teaching in this population.

Smart Insulin Pens are Associated with Improved Clinical Outcomes at Lower Cost Versus Standard-of-Care Treatment of Type 1 Diabetes in Sweden: A Cost-Effectiveness Analysis

INTRODUCTION

Real-world evidence has demonstrated improved glycemic control and insulin management following introduction of smart insulin pens in a Swedish type 1 diabetes (T1D) population. To understand the implications for healthcare costs and expected health outcomes, this analysis evaluated the long-term cost-effectiveness of introducing smart insulin pens to standard-of-care T1D treatment (standard care) from a Swedish societal perspective.

METHODS

Clinical outcomes and healthcare costs (in 2018 Swedish krona, SEK) were projected over patients' lifetimes using the IQVIA CORE Diabetes Model to estimate cost-effectiveness. Clinical data and baseline characteristics for the simulated cohort were informed by population data and a prospective, noninterventional study of a smart insulin pen in a Swedish T1D population. This analysis captured direct and indirect costs, mortality, and the impact of diabetes-related complications on quality of life.

RESULTS

Over patients' lifetimes, smart insulin pen use was associated with per-patient improvements in mean discounted life expectancy (+ 0.90 years) and quality-adjusted life expectancy (+ 1.15 quality-adjusted life-years), in addition to mean cost savings (direct, SEK 124,270; indirect, SEK 373,725), versus standard care. A lower frequency and delayed onset of complications drove projected improvements in quality-adjusted life expectancy and lower costs with smart insulin pens versus standard care. Overall, smart insulin pens were a dominant treatment option relative to standard care across all base-case and sensitivity analyses.

CONCLUSIONS

Use of smart insulin pens was projected to improve clinical outcomes at lower costs relative to standard care in a Swedish T1D population and represents a good use of healthcare resources in Sweden.

Are residents receiving the training needed within their residency programs to optimally manage patients with diabetes?

Objective: Diabetes is a prevalent and growing problem in the United States (U.S.); primary care physicians need to be prepared to initiate and progressively advance treatment. The objective of this study was to understand how diabetes management is taught in U.S. Family Medicine (FM) and Internal Medicine (IM) residency programs.Methods: Invitations to complete an online survey were sent via postal mail to U.S. FM and IM residency programs in 2019.Results: Directors/associate directors from 68 FM residencies and 66 IM residencies completed the online survey out of 645 (10.5%) and 505 (13.1%) programs, respectively. Most respondents rated cardiovascular disease and risk management in diabetes as 'very important' (90%), but only about half (47%) did so for newer generation insulin analogs and 27% for digital health technologies. About two-thirds of programs cover non-insulin options for type 2 diabetes (66%) and types of insulin (63%) to a great extent, but only about one-third of programs cover social determinants of health (36%) and pre-diabetes (35%) to this degree. Many programs report plans to expand training on cardiovascular disease and diabetes (59%), but only 32% plan to expand training on digital technology for diabetes care. Lack of faculty time and competing priorities are cited as being the biggest barriers to expanding diabetes training.Conclusions: Our study found that the current U.S. FM and IM residency program diabetes curricula are dominantly oriented toward cardiovascular disease and 'traditional' insulins. A variety of training materials and resources could help overcome some of the current barriers to curriculum expansion of other important components of diabetes care that may help future physicians successfully manage diabetes with newer generation insulin and glucose monitoring technologies.Abbreviations: U.S: United States; PCP: Primary Care Physician; FM: Family Medicine; IM: Internal Medicine; CGM: Continuous Glucose Monitor; AAFP: American Academy of Family Physicians; ACGME: Accreditation Council for Graduate Medical Education; U/mL: units per milliliter; CME: Continuing Medical Education.

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.

Improving Adherence in Type 2 Diabetes

International Diabetes Federation estimates that there are more than a half-billion adults ages 20 to 79 years worldwide who have diabetes mellitus (DM) and that the global health care expenditure for adults with DM in 2015 was $673 billion. Nonadherence and nonpersistence to prescribed type 2 DM medications are common and remain a barrier to optimal health outcomes. There is a high prevalence of nonadherence among older adults. Research has focused on prevalence and predictors of adherence, research methodologies, and development of measures of adherence. Improvements hopefully will result in better disease monitoring, medication adherence, and reduced rates of diabetes complications.

Recent trends in diabetes-related consumer health information technology research

Diabetes-related consumer health information technology (CHIT) has been designed to facilitate self-management practices, and its use has improved health outcomes for many consumers. This analysis sought to identify tendencies in diabetes-related CHIT research from 2010-2015 to help researchers find novel research topics, periodicals, collaborators, and funding agencies and experts and lay consumers to find scholarly information. Six search engines encompassing computer science, engineering, and medicine yielded potential diabetes-related CHIT publications. Abstracts and full texts were screened based on inclusion and exclusion criteria. Information on year, periodical, periodical domain, keywords, author location, author institutions, authors, and funding agencies were collected from included publications. The screening process yielded 1551 publications. Studies were published in a core of twenty periodicals, commonly comprising medicine or technology domains. "Telemedicine" was the most frequently used keyword. Harvard University, Dr. Eirik Årsand, and the National Institute of Diabetes and Digestive Kidney Diseases were the most frequent author institution, author, and funding agency, respectively, associated with publications. This analysis revealed potential for novel research on the sociology and economics of diabetes-related CHIT, among other topics. A lack of collaboration between top authors in the field indicates potential for new, impactful collaborations. Ongoing bibliometric research will be necessary to assess changes in this field. The opportunity exists to inform lay consumers and researchers through bibliometric analyses of other consumer health informatics topics.

An Evaluation of Digital Health Tools for Diabetes Self-Management in Hispanic Adults: Exploratory Study

Background

Although multiple self-monitoring technologies for type 2 diabetes mellitus (T2DM) show promise for improving T2DM self-care behaviors and clinical outcomes, they have been understudied in Hispanic adult populations who suffer disproportionately from T2DM.

Objective

The objective of this study was to evaluate the acceptability, feasibility, and potential integration of wearable sensors for diabetes self-monitoring among Hispanic adults with self-reported T2DM.

Methods

We conducted a pilot study of T2DM self-monitoring technologies among Hispanic adults with self-reported T2DM. Participants (n=21) received a real-time continuous glucose monitor (RT-CGM), a wrist-worn physical activity (PA) tracker, and a tablet-based digital food diary to self-monitor blood glucose, PA, and food intake, respectively, for 1 week. The RT-CGM captured viewable blood glucose concentration (mg/dL) and PA trackers collected accelerometer-based data, viewable on the device or an associated tablet app. After 1 week of use, we conducted a semistructured interview with each participant to understand experiences and thoughts on integration of the data from the devices into a technology-facilitated T2DM self-management intervention. We also conducted a brief written questionnaire to understand participants’ self-reported T2DM history and past experience using digital health tools for T2DM self-management. Feasibility was measured by device utilization and objective RT-CGM, PA tracker, and diet logging data. Acceptability and potential integration were evaluated through thematic analysis of verbatim interview transcripts.

Results

Participants (n=21, 76% female, 50.4 [SD 11] years) had a mean self-reported hemoglobin A_1c of 7.4 [SD 1.8] mg/dL and had been diagnosed with T2DM for 7.4 [SD 5.2] years (range: 1-16 years). Most (89%) were treated with oral medications, whereas the others self-managed through diet and exercise. Nearly all participants (n=20) used both the RT-CGM and PA tracker, and 52% (11/21) logged at least one meal, with 33% (7/21) logging meals for 4 or more days. Of the 8 possible days, PA data were recorded for 7.1 [SD 1.8] days (range: 2-8), and participants averaged 7822 [SD 3984] steps per day. Interview transcripts revealed that participants felt most positive about the RT-CGM as it unveiled previously unknown relationships between lifestyle and health and contributed to changes in T2DM-related thoughts and behaviors. Participants felt generally positive about incorporating the wearable sensors and mobile apps into a future intervention if support were provided by a health coach or health care provider, device training were provided, apps were tailored to their language and culture, and content were both actionable and delivered on a single platform.

Conclusions

Sensor-based tools for facilitating T2DM self-monitoring appear to be a feasible and acceptable technology among low-income Hispanic adults. We identified barriers to acceptability and highlighted preferences for wearable sensor integration in a community-based intervention. These findings have implications for the design of T2DM interventions targeting Hispanic adults.

Access to mobile phone and willingness to receive mHealth services among patients with diabetes in Northwest Ethiopia: a cross-sectional study

OBJECTIVES

This study aimed at determining access to mobile phone and willingness to receive mobile phone-based diabetes health services as well as identify associated factors in Northwest Ethiopia.

DESIGN

An institution-based cross-sectional survey was conducted from February to March 2016.

PARTICIPANTS

Systematic randomly selected 423 patients with diabetes.

SETTING

University of Gondar Hospital diabetic clinic.

MAIN OUTCOME MEASURES

The main outcome measure was willingness to receive diabetic health service via mobile phone voice call or messaging services.

RESULTS

Out of 423 patients with diabetes, 329 (77.8%) had access to a mobile phone. Among the latter, 232 (70.5%) were willing to receive mobile phone-based health services. The educational status of patients (adjusted OR (AOR): 2.6 (95% CI: 1.2 to 5.58)), route of medication (AOR: 3.2 (95% CI: 1.44 to 7.1)), transportation mechanism (AOR: 4.1 (95% CI: 1.2 to 13.57)), travel time to health facility (AOR: 0.3 (95% CI: 0.12 to 0.82)), current use of mobile phone as appointment reminder (AOR: 2.6 (95% CI: 1.07 to 6.49)) and locking mobile phone with passwords (AOR: 4.6 (95% CI: 1.63 to 12.95)) were significantly associated with the willingness to receive mobile phone-based diabetic health services.

CONCLUSION

Access to a mobile phone and willingness to receive mobile phone-based health services were high. Educational status, route of medication, transportation mechanism, time to reach the service, using mobile phone as appointment reminder and locking mobile phone with passwords were significantly associated factors. Given the high proportion of access and willingness of patients to receive mobile phone-based health services, mHealth interventions could be helpful.

Capturing the trend of mHealth research using text mining

BACKGROUND

With the increasing development and use of mobile technologies, an increasing amount of research on mobile health is being conducted. The purpose of the study was to capture the trends in mHealth research by mining terms related to medical conditions, interventions, study populations, and the relationships between these terms.

METHODS

This study analyzed 5,600 journal articles published in Web of Science from 2008 to 2018. Using text mining techniques, a total of 39,292 terms extracted from the titles and abstracts of the journal articles were independently reviewed to identify meaningful terms related to medical conditions, interventions, and study populations.

RESULTS

A total of 48 different types of medical conditions were identified in the dataset. Mood disorders appeared to be the most frequently identified medical condition in mHealth research. Thirty interventions were identified. Cell phone-, SMS-, and Internet-based interventions appeared to be the most prominent types, and "female" appeared to be the most frequently identified term related to the studied population. Females appeared to have been studied in the widest range of medical conditions, including pregnancy issues, overnutrition, neoplasms, and AIDS. Older adults were the least studied population in mHealth.

CONCLUSIONS

Knowledge gaps that have not been explored in previous studies in mHealth research were identified, which should be addressed by researchers.

Prototypes of User Interfaces for Mobile Applications for Patients with Diabetes

We live in a heavily technologized global society. It is therefore not surprising that efforts are being made to integrate current information technology into the treatment of diabetes mellitus. This paper is dedicated to improving the treatment of this disease through the use of well-designed mobile applications. Our analysis of relevant literature sources and existing solutions has revealed that the current state of mobile applications for diabetics is unsatisfactory. These limitations relate both to the content and the Graphical User Interface (GUI) of existing applications. Following the analysis of relevant studies, there are four key elements that a diabetes mobile application should contain. These elements are: (1) blood glucose levels monitoring; (2) effective treatment; (3) proper eating habits; and (4) physical activity. As the next step in this study, three prototypes of new mobile applications were designed. Each of the prototypes represents one group of applications according to a set of given rules. The most optimal solution based on the users’ preferences was determined by using a questionnaire survey conducted with a sample of 30 respondents participating in a questionnaire after providing their informed consent. The age of participants was from 15 until 30 years old, where gender was split to 13 males and 17 females. As a result of this study, the specifications of the proposed application were identified, which aims to respond to the findings discovered in the analytical part of the study, and to eliminate the limitations of the current solutions. All of the respondents expressed preference for an application that includes not only the key functions, but a number of additional functions, namely synchronization with one of the external devices for measuring blood glucose levels, while five-sixths of them found suggested additional functions as being sufficient.

Digital diabetes: Perspectives for diabetes prevention, management and research

Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients' symptoms, physiological data, behaviours, and social and environmental contexts through the use of wearables, sensors and smartphone technologies. Moreover, data generated online and by digital technologies - which the authors suggest be grouped under the term 'digitosome' - constitute, through the quantity and variety of information they represent, a powerful potential for identifying new digital markers and patterns of risk that, ultimately, when combined with clinical data, can improve diabetes management and quality of life, and also prevent diabetes-related complications. Moving from a world in which patients are characterized by only a few recent measurements of fasting glucose levels and glycated haemoglobin to a world where patients, healthcare professionals and research scientists can consider various key parameters at thousands of time points simultaneously will profoundly change the way diabetes is prevented, managed and characterized in patients living with diabetes, as well as how it is scientifically researched. Indeed, the present review looks at how the digitization of diabetes can impact all fields of diabetes - its prevention, management, technology and research - and how it can complement, but not replace, what is usually done in traditional clinical settings. Such a profound shift is a genuine game changer that should be embraced by all, as it can provide solid research results transferable to patients, improve general health literacy, and provide tools to facilitate the everyday decision-making process by both healthcare professionals and patients living with diabetes.

Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications

The recent announcement of the production of new low-cost continuous glucose monitoring (CGM) sensors, the approval of marketed CGM sensors for making treatment decisions, and new reimbursement criteria have the potential to revolutionize CGM use. After briefly summarizing current CGM applications, we discuss how, in our opinion, these changes are expected to extend CGM utilization beyond diabetes patients, for example, to subjects with prediabetes or even healthy individuals. We also elaborate on how the integration of CGM data with other relevant information, for example, health records and other medical device/wearable sensor data, will contribute to creating a digital data ecosystem that will improve our understanding of the etiology and complications of diabetes and will facilitate the development of data analytics for personalized diabetes management and prevention.

Diabetes on demand and novel technologies

To date, the use of technology for the management of diabetes represents a promising area of innovation that can dramatically change diabetics' lives. In the past decade, the use of diabetes devices has widely grown and looks to have partially improved diabetes management. The combination of cloud technology with real-expert intervention saves time and improves efficiency, as well as empowering the patient. The application of mathematical models applied to diabetes therapy could lead to significant improvement in life quality and challenge the burden of hypoglycaemia. Events where an individual needs support are instantly achieved, triggering outreach alerts via cloud and wireless connectivity, thereby improving patient compliance and reducing disease costs.

Insights into optimal basal insulin titration in type 2 diabetes: Results of a quantitative survey

AIMS

Basal insulin (BI) treatment initiation and dose titration in type 2 diabetes (T2DM) are often delayed. Such "clinical inertia" results in poor glycaemic control and high risk of long-term complications. This survey aimed to determine healthcare professional (HCP) and patient attitudes to BI initiation and titration.

METHODS

An online survey (July-August 2015) including HCPs and patients with T2DM in the USA, France and Germany. Patients were ≥18 years old and had been on BI for 6 to 36 months, or discontinued BI within the previous 12 months.

RESULTS

Participants comprised 386 HCPs and 318 people with T2DM. While >75% of HCPs reported discussing titration at the initiation visit, only 16% to 28% of patients remembered such discussions, many (32%-42%) were unaware of the need to titrate BI, and only 28% to 39% recalled mention of the time needed to reach glycaemic goals. Most HCPs and patients agreed that more effective support tools to assist BI initiation/titration are needed; patients indicated that provision of such tools would increase confidence in self-titration. HCPs identified fear of hypoglycaemia, failure to titrate in the absence of symptoms, and low patient motivation as important titration barriers. In contrast, patients identified weight gain, the perception that titration meant worsening disease, frustration over the time to reach HbA1c goals and fear of hypoglycaemia as major factors.

CONCLUSION

A disconnect exists between HCP- and patient-perceived barriers to effective BI titration. To optimize titration, strategies should be targeted to improve HCP-patient communication, and provide support and educational tools.

Baseline Characteristics and Technology Training of Underserved Adults With Type 2 Diabetes in the Mobile Diabetes Detective (MoDD) Randomized Controlled Trial

Purpose The purpose of this study is to describe the characteristics and technology training needs of underserved adults with type 2 diabetes mellitus (T2DM) who participated in a health information technology (HIT) diabetes self-management education (DSME) intervention. Methods The baseline physiological, psychosocial, and technology use characteristics for 220 adults with poorly controlled T2DM were evaluated. Intervention participants received a 1-time intervention training, which included basic technology help, introduction to the Mobile Diabetes Detective (MoDD) website and text message features, and account activation that included subject-specific tailoring. Four additional on-site sessions for participants needing computer or Internet access or technology support were made available based on need. Data regarding on-site visits for usual care were collected. Data were analyzed using descriptive statistics and bivariate analysis. Results The participants were predominately Hispanic and female with a baseline mean A1C of 10% (86 mmol/mol). Only half of the participants regularly used computers or text messages in daily life. The average introductory MoDD training session lasted 73.6 minutes. Following training, approximately one-third (35%) of intervention participants returned for basic and MoDD-specific technology assistance at their federally qualified health center. The most frequently reported duration for the extra training sessions was 30 to 45 minutes. Conclusions Training and support needs were greater than anticipated. Diabetes educators should assess technology abilities prior to implementing health information technology (HIT) diabetes self-management education (DSME) in underserved adults. Future research must invest resources in technology access, anticipate subject training, and develop new training approaches to ensure HIT DSME use and engagement.

Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus

Cardiovascular disease is the leading cause of morbidity and mortality globally, with diabetes being an independent risk factor. Adequate diabetes management has proven to be resource-intensive, requiring frequent lab work, primary care and specialist visits, and time-consuming record-keeping by the patient and care team. New mobile health (mHealth) technologies have enhanced how diabetes is managed and care is delivered. While more recent work has investigated mHealth devices as complementary tools in behavioral interventions for diabetes prevention and management, little is still known about the effectiveness of mHealth technology as stand-alone intervention tools for reducing diabetes risk. In addition, more work is needed to identify the role of mHealth technology in treating vulnerable populations to ameliorate cardiovascular health disparities. With advances in mobile health technology development for diabetes prevention and management, these modalities will likely play an increasingly prominent role in reducing cardiometabolic risk for the US population.

Desirable Components for a Customized, Home-Based, Digital Care-Management App for Children and Young People With Long-Term, Chronic Conditions: A Qualitative Exploration

BACKGROUND

Mobile apps for mobile phones and tablet devices are widely used by children and young people aged 0-18 years with long-term health conditions, such as chronic kidney disease (CKD), and their healthy peers for social networking or gaming. They are also poised to become a major source of health guidance. However, app development processes that are coproduced, rigorously developed, and evaluated to provide tailored, condition-specific, practical advice on day-to-day care management are seldom systematic or sufficiently described to enable replication. Furthermore, attempts to extrapolate to the real world are hampered by a poor understanding of the effects of key elements of app components. Therefore, effective and cost-effective novel, digital apps that will effectively and safely support care management are critical and timely. To inform development of such an app for children with CKD, a user requirements-gathering exercise was first needed.

OBJECTIVE

To explore the views of children with CKD, their parents, and health care professionals to inform future development of a child-focused, care-management app.

METHODS

Using age- and developmentally appropriate methods, we interviewed 36 participants: 5-10-year-olds (n=6), 11-14-year-olds (n=6), 15-18-year-olds (n=5), mothers (n=10), fathers (n=2), and health care professionals (n=7). Data were analyzed using Framework Analysis and behavior change theories.

RESULTS

Of the 27 interviews, 19 (70%) interviews were individual and 8 (30%) were joint-5 out of 8 (63%) joint interviews were with a child or young person and their parent, 1 out of 8 (13%) were with a child and both parents, and 2 out of 8 (25%) were with 2 professionals. Three key themes emerged to inform development of a software requirement specification for a future home-based, digital care-management app intervention: (1) Gaps in current online information and support, (2) Difficulties experienced by children with a long-term condition, and (3) Suggestions for a digital care-management app. Reported gaps included the fact that current online information is not usually appropriate for children as it is "dry" and "boring," could be "scary," and was either hard to understand or not relevant to individuals' circumstances. For children, searching online was much less accessible than using a professional-endorsed mobile app. Children also reported difficulty explaining their condition to others, maintaining treatment adherence, coping with feeling isolated, and with trying to live a "normal" life. There was recognition that a developmentally appropriate, CKD-specific app could support the process of explaining the condition to healthy peers, reducing isolation, adhering to care-management plans, and living a "normal" life. Participants recommended a range of media and content to include in a tailored, interactive, age- and developmentally appropriate app. For example, the user would be able to enter their age and diagnosis so that only age-appropriate and condition-specific content is displayed.

CONCLUSIONS

Future development of a digital app that meets the identified information and support needs and preferences of children with CKD will maximize its utility, thereby augmenting CKD caregiving and optimizing outcomes.

Cost of medication adherence and persistence in type 2 diabetes mellitus: a literature review

PURPOSE

To explore published evidence on health care costs associated with adherence or persistence to antidiabetes medications in adults with type 2 diabetes mellitus (T2DM).

METHODS

Primary research studies published between January 2006 and December 2015 on compliance, adherence, or persistence and treatment in patients with T2DM that document a link with health care costs were identified through literature searches in bibliographic databases and 2015 abstract books for relevant DM congresses. Results were assessed for relevance by two reviewers. The review was part of a larger overview evaluating the impact of adherence and persistence on a range of clinical and economic outcomes; only findings from the cost element are reported herein.

RESULTS

A total of 4,662 de-duplicated abstracts were identified and 110 studies included in the wider review. Of these, 19 reported an association between adherence (n=13), persistence (n=5), or adherence and persistence (n=1), and health care costs. All studies were retrospective, with sample sizes ranging from 301 to 740,195. Medication possession ratio was the most commonly employed adherence measure (n=11). The majority of adherence studies (n=9) reported that medication adherence was associated with lower total health care costs. Pharmacy costs were often increased in adherent patients but this was offset by beneficial effects on other costs. Findings were more variable in persistence studies; three reported that higher pharmacy costs in persistent patients were not sufficiently offset by savings in other areas to result in a reduction in total health care costs.

CONCLUSIONS

Few studies have evaluated the relationship between adherence, persistence, and health care costs in T2DM. However, it has been consistently shown that medication nonadherence increases health care costs, suggesting that cost savings from better adherence could be substantial. Available data support the economic case for identification of strategies that facilitate improved medication adherence in patients with T2DM.

Mobile Health Technology in the Prevention and Management of Type 2 Diabetes

Essential steps in diabetes prevention and management include translating research into the real world, improving access to health care, empowering the community, collaborative efforts involving physicians, diabetes educators, nurses, and public health scientists, and access to diabetes prevention and management efforts. Mobile phone technology has shown wide acceptance across various ages and socioeconomic groups and offers several opportunities in health care including self-management as well as prevention of Type 2 diabetes mellitus (T2DM). The future seems to lie in mobile health (mHealth) applications that can use embedded technology to showcase advanced uses of a smartphone to help with prevention and management of chronic disorders such as T2DM. This article presents a narrative review of the mHealth technologies used for the prevention and management of T2DM. Majority (48%) of the studies used short message service (SMS) technology as their intervention while some studies (29%) incorporated applications for medication reminders and insulin optimization for T2DM management. Few studies (23%) showed that, along with mHealth technology, health-care professionals' support resulted in added positive outcomes for the patients. This review highlights the fact that an mHealth intervention need not be restricted to SMS alone.

Exploring educational needs and design aspects of internet-enabled patient education for persons with diabetes: a qualitative interview study

OBJECTIVE

The objective of this article is to explore the educational needs and design aspects of personalised internet-enabled education for patients with diabetes in Iran.

DESIGN

Data were collected using semistructured interviews and then qualitatively analysed using inductive content analysis.

PARTICIPANTS

9 patients with type 2 diabetes were included. Inclusion criteria were access to and knowledge on how to use the internet. The selection ensured representation based on gender, age, occupation and educational background.

SETTING

The sample population was patients with diabetes who were admitted to an outpatient diabetes clinic in Mashhad, a large city of Iran with about 3 million inhabitants.

RESULTS

4 core categories emerged from the data: (1) seeking knowledge about diabetes, including specific knowledge acquisition, patient's interactions and learning requirements; (2) teaching and learning, including using different teaching methods and different ways to learn about the disease; (3) facilitators, including internet and mobile phone use to learn about the disease; and (4) barriers, including lack of internet access, uncertainty of access to the internet and lack of website in the local language and also perceived cultural barriers, such as patients' fears of the internet, lack of time and awareness.

CONCLUSIONS

This study provides a better understanding of the patient's educational expectations and technical needs in relation to internet-enabled education. This knowledge will inform the development of functional mock-ups in the next research phase using a design-based research approach in order to design internet-enabled patient education for self-management of diabetes.

Mobile Applications for Control and Self Management of Diabetes: A Systematic Review

Mobile applications (apps) can be very useful software on smartphones for all aspects of people's lives. Chronic diseases, such as diabetes, can be made manageable with the support of mobile apps. Applications on smartphones can also help people with diabetes to control their fitness and health. A systematic review of free apps in the English language for smartphones in three of the most popular mobile app stores: Google Play (Android), App Store (iOS) and Windows Phone Store, was performed from November to December 2015. The review of freely available mobile apps for self-management of diabetes was conducted based on the criteria for promoting diabetes self-management as defined by Goyal and Cafazzo (monitoring blood glucose level and medication, nutrition, physical exercise and body weight). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was followed. Three independent experts in the field of healthcare-related mobile apps were included in the assessment for eligibility and testing phase. We tested and evaluated 65 apps (21 from Google Play Store, 31 from App Store and 13 from Windows Phone Store). Fifty-six of these apps did not meet even minimal requirements or did not work properly. While a wide selection of mobile applications is available for self-management of diabetes, current results show that there are only nine (5 from Google Play Store, 3 from App Store and 1 from Windows Phone Store) out of 65 reviewed mobile apps that can be versatile and useful for successful self-management of diabetes based on selection criteria. The levels of inclusion of features based on selection criteria in selected mobile apps can be very different. The results of the study can be used as a basis to prvide app developers with certain recommendations. There is a need for mobile apps for self-management of diabetes with more features in order to increase the number of long-term users and thus influence better self-management of the disease.