Challenges in Diabetes Care: Can Digital Health Help Address Them?

Integrating Social Determinants of Health in Machine Learning-Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study

BACKGROUND

The use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes.

OBJECTIVE

This study proposes the development of a data-driven decision-support system incorporating interactions between clinical factors and SDoH into an algorithm for prioritizing who receives case management services. The paper presents a design for prediction validation and preimplementation assessment that uses a mixed methods approach to guide the implementation of the system.

METHODS

Our study setting is a large, tertiary care academic medical center in the Deep South of the United States, where SDoH contribute to disparities in diabetes-specific hospitalizations and emergency department (ED) visits. This project will develop an interpretable artificial intelligence model for a population with diabetes using SDoH and clinical data to identify which posthospitalization cases have a higher likelihood of subsequent ED use. The electronic health record data collected for the study include demographics, SDoH, comorbidities, hospitalization-related factors, laboratory test results, and medication use to predict posthospitalization ED visits. Subsequently, a mixed methods approach will be used to validate prediction outcomes and develop an implementation strategy from insights into patient outcomes from case managers, clinicians, and quality and patient safety experts.

RESULTS

As of December 2023, we had abstracted data on 174,871 inpatient encounters between January 2018 and September 2023, involving 89,355 unique inpatients meeting inclusion criteria. Both clinical and SDoH data items were included for these patient encounters. In total, 85% of the inpatient visits (N=148,640) will be used for training (learning from the data) and the remaining 26,231 inpatient visits will be used for mixed-methods validation (testing).

CONCLUSIONS

By integrating a critical suite of SDoH with clinical data related to diabetes, the proposed data-driven risk stratification model can enable individualized risk estimation and inform health professionals (eg, case managers) about the risk of patients' upcoming ED use. The prediction outcome could potentially automate case management referrals, helping to better prioritize services. By taking a mixed methods approach, we aim to align the model with the hospital's specific quality and patient safety considerations for the quality of patient care and the optimization of case management resource allocation.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56049.

Working Together to Improve Type 2 Diabetes Care: A Participatory Design Project to Address Identified Needs of People With Diabetes and Their Health-care Professionals

OBJECTIVES

Diabetes care in Australia is often fragmented and provider-centred, resulting in suboptimal care. Innovative solutions are needed to bridge the evidence-practice gap, and technology can facilitate the redesign of type 2 diabetes care. We used participatory design to increase the chances of fulfilling stakeholders' needs. Using this method, we explored solutions aimed at redesigning diabetes care, focussing on the previously identified needs.

METHODS

The participatory design project was guided by stakeholders' contributions. Stakeholders of this project included people with type 2 diabetes, health-care professionals, technology developers, and researchers. Information uncovered at each step influenced the next: 1) identification of needs, 2) generation of solutions, and 3) testing of solutions. Here, we present steps 2 and 3. In step 2, we presented previously identified issues and elicited creative solutions. In step 3, we obtained stakeholders' feedback on the solutions from step 2, presented as care pathways.

RESULTS

Suggested solutions included a multidisciplinary wellness centre, a mobile app, increased access to education, improved care coordination, increased support for general practitioners, and a better funding model. The revised care pathways featured accessible community resources, a tailored self-management and educational app, a care coordinator, a digital dashboard, and specialized support for primary care to deal with complex cases.

CONCLUSIONS

Using a participatory design, we successfully identified multiple innovative solutions with the potential to improve person-centred and integrated type 2 diabetes care in Australia. These solutions will inform the implementation and evaluation of a redesigned care model by our team.

Prioritizing Patient Experiences in the Management of Diabetes and Its Complications: An Endocrine Society Position Statement

Diabetes can be an arduous journey both for people with diabetes (PWD) and their caregivers. While the journey of every person with diabetes is unique, common themes emerge in managing this disease. To date, the experiences of PWD have not been fully considered to successfully implement the recommended standards of diabetes care in practice. It is critical for health-care providers (HCPs) to recognize perspectives of PWD to achieve optimal health outcomes. Further, existing tools are available to facilitate patient-centered care but are often underused. This statement summarizes findings from multistakeholder expert roundtable discussions hosted by the Endocrine Society that aimed to identify existing gaps in the management of diabetes and its complications and to identify tools needed to empower HCPs and PWD to address their many challenges. The roundtables included delegates from professional societies, governmental organizations, patient advocacy organizations, and social enterprises committed to making life better for PWD. Each section begins with a clinical scenario that serves as a framework to achieve desired health outcomes and includes a discussion of resources for HCPs to deliver patient-centered care in clinical practice. As diabetes management evolves, achieving this goal will also require the development of new tools to help guide HCPs in supporting PWD, as well as concrete strategies for the efficient uptake of these tools in clinical practice to minimize provider burden. Importantly, coordination among various stakeholders including PWD, HCPs, caregivers, policymakers, and payers is critical at all stages of the patient journey.

Telemedicine interventions in type 2 diabetes management: a protocol for systematic review and network meta-analysis

INTRODUCTION

The consequences of type 2 diabetes mellitus (T2DM) heavily strain individuals and healthcare systems worldwide. Interventions via telemedicine have become a potential tactic to tackle the difficulties in effectively managing T2DM. However, more research is needed to determine how telemedicine interventions affect T2DM management. This study sets out to systematically analyse and report the effects of telemedicine treatments on T2DM management to gain essential insights into the potential of telemedicine as a cutting-edge strategy to improve the outcomes and care delivery for people with T2DM.

METHODS AND ANALYSIS

To uncover relevant research, we will perform a comprehensive literature search across six databases (PubMed, IEEE, EMBASE, Web of Science, Google Scholar and Cochrane Library). Each piece of data will be extracted separately, and any discrepancies will be worked out through discussion or by a third reviewer. The studies included are randomised controlled trial. We chose by predefined inclusion standards. After the telemedicine intervention, glycated haemoglobin will be the primary outcome. The Cochrane risk-of-bias approach will be used to evaluate the quality of the included studies. RevMan V.5.3.5 software and RStiduo V.4.3.1 software can be used to analyse the data, including publication bias.

ETHICS AND DISSEMINATION

Since this research will employ publicly accessible documents, ethical approval is unnecessary. The review is registered prospectively on the PROSPERO database. The study's findings will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42023421719.

Mapping the Cardiometabolic Patient Experience and Self-Care Behaviors to Inform Design, Implementation, and Persistent Use of Digital Health Care Solutions: Mixed Methods Study

BACKGROUND

Cardiometabolic conditions including acute coronary syndrome (ACS) and type 2 diabetes (T2D) require comprehensive care and patient engagement in self-care behaviors, and the drivers of those behaviors at the individual and health system level are still poorly understood.

OBJECTIVE

We aim to gain insights into self-care behaviors of individuals with cardiometabolic conditions.

METHODS

A convenience sample of 98 adult patients with ACS and T2D was recruited in the United States, Germany, and Taiwan to participate in a mixed methods study using ethnographic methods. All participants completed 7-day web-based diaries tracking their level of engagement, and 48 completed 90-minute web-based semistructured interviews between February 4, 2021, and March 27, 2021, focusing on themes including moments of engagement. Qualitative analysis identified factors influencing self-care practices and a Patient Mind States Model prototype.

RESULTS

Patient reports indicate that many patients feel social pressure to adhere to treatment. Patients' experience can be understood within 5 categories defined in terms of their degree of engagement and adherence ("ignoring," "struggling," "juggling," "controlling," and "reframing").

CONCLUSIONS

For people living with ACS and T2D, the self-care journey is defined by patterns of patient experiences, which can identify areas that tailored digital health care interventions may play a meaningful role.

Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review

Digital health is a field that aims to improve patient care through the use of technology, such as telemedicine, mobile health, electronic health records, and artificial intelligence. The aim of this review is to examine the challenges and potential solutions for the implementation and evaluation of digital health technologies. Digital tools are used across the world in different settings. In Australia, the Digital Health Translation and Implementation Program (DHTI) emphasizes the importance of involving stakeholders and addressing infrastructure and training issues for healthcare workers. The WHO's Global Task Force on Digital Health for TB aims to address tuberculosis through digital health innovations. Digital tools are also used in mental health care, but their effectiveness must be evaluated during development. Oncology supportive care uses digital tools for cancer patient intervention and surveillance, but evaluating their effectiveness can be challenging. In the COVID and post-COVID era, digital health solutions must be evaluated based on their technological maturity and size of deployment, as well as the quality of data they provide. To safely and effectively use digital healthcare technology, it is essential to prioritize evaluation using complex systems and evidence-based medical frameworks. To address the challenges of digital health implementation, it is important to prioritize ethical research addressing issues of user consent and addressing socioeconomic disparities in access and effectiveness. It is also important to consider the impact of digital health on health outcomes and the cost-effectiveness of service delivery.

Evaluating Effects of Virtual Diabetes Group Visits in Community Health Centers During the COVID-19 Pandemic

Diabetes is the seventh leading cause of death in the US. Diabetes group visits (GVs), which include group education and individual medical visits have been shown to improve clinical outcomes. However, few studies have evaluated virtual GVs. We conducted a single-arm pilot study to test the impact of virtual diabetes GVs in Midwestern community health centers (CHCs). Adult patients with diabetes participated in monthly virtual GVs for 6 months. Surveys and chart abstraction were used to assess patient-reported and clinical outcomes. Five CHCs implemented virtual GVs with 34 patients attending at least one session. Virtual GVs show promise as evidenced by these findings: (1) Patients had a nonsignificant decrease in A1C. (2) In the subgroup of patients with baseline A1C ≥ 9%, there was a significant decrease in A1C. (3) Patients had significant increases in diabetes knowledge and support as well as a decrease in diabetes distress. Future studies with a larger sample size and a control comparison group are needed to assess the impact of virtual GVs on patient outcomes.

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.

DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions

Objective digital data is scarce yet needed in many domains to enable research that can transform the standard of healthcare. While data from consumer-grade wearables and smartphones is more accessible, there is critical need for similar data from clinical-grade devices used by patients with a diagnosed condition. The prevalence of wearable medical devices in the diabetes domain sets the stage for unique research and development within this field and beyond. However, the scarcity of open-source datasets presents a major barrier to progress. To facilitate broader research on diabetes-relevant problems and accelerate development of robust computational solutions, we provide the DiaTrend dataset. The DiaTrend dataset is composed of intensive longitudinal data from wearable medical devices, including a total of 27,561 days of continuous glucose monitor data and 8,220 days of insulin pump data from 54 patients with diabetes. This dataset is useful for developing novel analytic solutions that can reduce the disease burden for people living with diabetes and increase knowledge on chronic condition management in outpatient settings.

Exploring the underlying mechanisms of obesity and diabetes and the potential of Traditional Chinese Medicine: an overview of the literature

Obesity and diabetes are closely related metabolic disorders that have become major public health concerns worldwide. Over the past few decades, numerous studies have explored the underlying mechanisms of these disorders and identified various risk factors, including genetics, lifestyle, and dietary habits. Traditional Chinese Medicine (TCM) has been increasingly recognized for its potential to manage obesity and diabetes. Weight loss is difficult to sustain, and several diabetic therapies, such as sulfonylureas, thiazolidinediones, and insulin, might make it harder to lose weight. While lifestyle changes should be the primary approach for people interested in lowering weight, drugs are also worth investigating. Since some of the newer glucose-lowering medications that cause weight loss, such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose cotransporter 2 inhibitors (SGLT2i), are additionally utilized or are under consideration for use as anti-obesity drugs, the frontier between glucose-lowering medication and weight loss drugs appears to be shifting. This review provides an overview of the literature on the underlying mechanisms of obesity and diabetes and the prospect of TCM in their management. We discuss the various TCM interventions, including acupuncture, herbal medicine, and dietary therapy, and their effects on metabolic health. We also highlight the potential of TCM in regulating gut microbiota, reducing inflammation, and improving insulin sensitivity. The findings suggest that TCM may provide a promising approach to preventing and managing obesity and diabetes. However, further well-designed studies are needed to confirm the efficacy and safety of TCM interventions and to elucidate their underlying mechanisms of action.

Connected Insulin Pens and Caps: An Expert's Recommendation from the Area of Diabetes of the Spanish Endocrinology and Nutrition Society (SEEN)

Undoubtedly, technological advances have revolutionised diabetes management in recent years. The development of advanced closed hybrid loop insulin pumps or continuous glucose monitoring (CGM) systems, among others, have increased the quality of life and improved glycaemic control of people with diabetes. However, only some patients have access to such technology, and only some want to use it. CGM has become much more widespread, but in terms of insulin delivery, most people with type 1 diabetes (T1D) and almost all people with type 2 diabetes (T2D) on insulin therapy are treated with multiple-dose insulin injections (MDI) rather than an insulin pump. For these patients, using connected insulin pens or caps has shown benefits in reducing missed insulin injections and promoting correct administration over time. In addition, using these devices improves the quality of life and user satisfaction. The integration of insulin injection and CGM data facilitates both users and the healthcare team to analyse glucose control and implement appropriate therapeutic changes, reducing therapeutic inertia. This expert's recommendation reviews the characteristics of the devices marketed or in the process of being marketed and their available scientific evidence. Finally, it suggests the profile of users and professionals who would benefit most, the barriers to its generalisation and the changes in the care model that implementing these devices can bring with it.

Clinical, Economic, and Patient-Reported Benefits of Connected Insulin Pen Systems: A Systematic Literature Review

INTRODUCTION

The objective of this systematic literature review was to evaluate the available literature concerning the clinical, economic, and patient-reported benefits of insulin pen platforms, including connected insulin pens/caps/sleeves and insulin platforms, as well as mobile apps capable of receiving near real-time insulin dosing information.

METHODS

Medline and Embase databases and the Cochrane Library were searched for published literature between January 2015 and May 2021, and manual searches for conference abstracts from 2018 to May 2021 were performed. These searches were supplemented by internet searches for relevant literature and clinical trials. Study selection involved the population, intervention, comparator, outcomes, time frame, and study design outline. Included studies investigated connected insulin systems or connected caps/sleeves enabling pens to be connected, or apps able to connect to these systems, in individuals of all ages with type 1 or type 2 diabetes mellitus.

RESULTS

Searches identified a total of 26 publications (mostly observational studies and conference abstracts) for inclusion, representing ten unique, predominantly small studies. Evidence in this field is still in its early stages, and only two randomized controlled trials met our inclusion criteria. Available results showed that connected insulin pens and their systems potentially helped reduce suboptimal insulin use and may therefore improve glycemic control. Satisfaction of people with diabetes with the technologies used was high, and economic benefits were noted. Features of effective connected insulin pen devices include simplicity of use and data upload/sharing, useful "point-of-care" alerts, and simple and understandable data presentation to facilitate more effective consultations.

CONCLUSIONS

Connected insulin pen systems could be increasingly considered as part of routine clinical care for insulin-treated persons with diabetes who must manage the complexity of their daily insulin routine. Future research focusing on the way data obtained from these devices can be most effectively used alongside other information is urgently needed.

Patients' Preferences for Connected Insulin Pens: A Discrete Choice Experiment Among Patients with Type 1 and Type 2 Diabetes

BACKGROUND

This study quantified how people with diabetes value the unique features of connected insulin pens and related mobile apps, and the underlying reasons for preferring connected versus non-connected insulin pens.

METHODS

A discrete choice experiment (DCE) was conducted in the USA and UK to elicit preferences of adults (≥ 18 years) with type 1 or 2 diabetes for attributes of insulin pens. Attributes included device type, dosing support, glucose monitoring, additional app features, and data sharing. Relative attribute importance (RAI) scores were calculated to capture the relative importance of an attribute. Predicted choice probabilities were obtained to compare different profiles for connected and non-connected insulin pens.

RESULTS

The DCE was completed by 540 participants (58.9% male; 90.7% Caucasian; mean age, 58.3 years; 69.4% type 2 diabetes). Participants most valued the possibility of using a connected insulin pen with dosing support and automated dose logging (RAI = 39.9%), followed by automatic transfer of glucose levels (RAI = 29.0%), additional features of tracking diet and physical activity (RAI = 14.6%), data sharing (RAI = 13.6%), and device type (RAI = 2.9%). All profiles of connected insulin pens were preferred over a non-connected pen (p < 0.001), and pen profiles with advanced features were preferred over those without (p < 0.001). Preferences differed by age but not diabetes type, country of residence, or insulin regimen.

CONCLUSION

People with diabetes in the USA and UK prefer connected over non-connected insulin pens due largely to the availability of automated logging of dose and glucose levels.

A Roadmap to an Equitable Digital Diabetes Ecosystem

OBJECTIVES

Diabetes management presents a substantial burden to individuals living with the condition and their families, health care professionals, and health care systems. Although an increasing number of digital tools are available to assist with tasks such as blood glucose monitoring and insulin dose calculation, multiple persistent barriers continue to prevent their optimal use.

METHODS

As a guide to creating an equitable connected digital diabetes ecosystem, we propose a roadmap with key milestones that need to be achieved along the way.

RESULTS

During the Coronavirus 2019 pandemic, there was an increased use of digital tools to support diabetes care, but at the same time, the pandemic also highlighted problems of inequities in access to and use of these same technologies. Based on these observations, a connected diabetes ecosystem should incorporate and optimize the use of existing treatments and technologies, integrate tasks such as glucose monitoring, data analysis, and insulin dose calculations, and lead to improved and equitable health outcomes.

CONCLUSIONS

Development of this ecosystem will require overcoming multiple obstacles, including interoperability and data security concerns. However, an integrated system would optimize existing devices, technologies, and treatments to improve outcomes.

Effects of mobile health interventions on health-related outcomes in older adults with type 2 diabetes: A systematic review and meta-analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic metabolic condition that is associated with multiple comorbidities. Apart from pharmacological approaches, patient self-management remains the gold standard of care for diabetes. Improving patients' self-management among the elderly with mobile health (mHealth) interventions is critical, especially in times of the COVID-19 pandemic. However, the extent of mHealth efficacy in managing T2DM in the older population remains unknown. Hence, the present review examined the effectiveness of mHealth interventions on cardiometabolic outcomes in older adults with T2DM.

METHODS

A systematic search from the inception till May 31, 2021, in the MEDLINE, Embase, and PubMed databases was conducted, and 16 randomized controlled trials were included in the analysis.

RESULTS

The results showed significant benefits on glycosylated hemoglobin (HbA1c) (mean difference -0.24%; 95% confidence interval [CI]: -0.44, -0.05; p = 0.01), postprandial blood glucose (-2.91 mmol/L; 95% CI: -4.78, -1.03; p = 0.002), and triglycerides (-0.09 mmol/L; 95% CI: -0.17, -0.02; p = 0.010), but not on low-density lipoprotein cholesterol (-0.06 mmol/L; 95% CI: -0.14, 0.02; p = 0.170), high-density lipoprotein cholesterol (0.05 mmol/L; 95% CI: -0.03, 0.13; p = 0.220), and blood pressure (systolic blood pressure -0.82 mm Hg; 95% CI: -4.65, 3.00; p = 0.670; diastolic blood pressure -1.71 mmHg; 95% CI: -3.71, 0.29; p = 0.090).

CONCLUSIONS

Among older adults with T2DM, mHealth interventions were associated with improved cardiometabolic outcomes versus usual care. Its efficacy can be improved in the future as the current stage of mHealth development is at its infancy. Addressing barriers such as technological frustrations may help strategize approaches to further increase the uptake and efficacy of mHealth interventions among older adults with T2DM.

Anthropometric Measurements and Laboratory Investigations in Children and Youth With Type 1 Diabetes Before and During the COVID-19 Pandemic

OBJECTIVES

Our aim in this study was to compare rates of anthropometric, blood pressure (BP) and glycated hemoglobin (A1C) measurements and laboratory screening for hypothyroidism, nephropathy and dyslipidemia in children and youth with type 1 diabetes (T1D), 1 year before and after the onset of COVID-19.

METHODS

Clinical data were analyzed from a voluntary registry of children and youth with T1D followed at the BC Children's Hospital between March 2019 and 2021. Logistic and Poisson mixed-effect models were used.

RESULTS

Four hundred forty patients with a median (interquartile range) age and time since diagnosis of 12.7 (9.5 to 15.4) and 4.7 (2.6 to 7.9) years, respectively, were included. Clinic visits were all in-person before March 2020, and 99% via telemedicine afterward. The median number of visits per patient was 2 (interquartile range, 2 to 3), with a 6% increase during the pandemic (relative risk [RR], 1.06; 95% confidence interval [CI], 1.01 to 1.10). There was a substantial decrease in height, weight and BP measurements (RR, 0.32; 95% CI, 0.28 to 0.36; RR, 0.34, 95% CI, 0.31 to 0.38; RR, 0.005, 95% CI, 0.002 to 0.014, respectively); only 49% of patients had anthropometric data and 1% had BP data during the pandemic year, compared with >97% before the pandemic. A1C measurements dropped from 3 (interquartile range, 2 to 4) to 1 (interquartile range, 1 to 2) per patient per year (RR, 0.53; 95% CI, 0.48 to 0.57). Rates of screening investigations were suboptimal before the pandemic, and these rates continued to decline.

CONCLUSIONS

Shifting to telemedicine allowed ongoing care during the pandemic, but the frequency of anthropometric, BP and A1C measurements decreased dramatically. A combined telemedicine/in-person model may be needed to ensure adequate care for this population.

Investigating the prevalence of diabetic complications in overweight/obese patients: a study in a tertiary hospital in Malaysia

Background

In Malaysia, although diabetes accounts for more than 70% of all deaths, it is unclear how it relates to BMI and diabetic complications. This study aimed to investigate the prevalence of obesity and diabetic complications among diabetic patients in Malaysia.

Materials and methods

A cross-sectional study using an existing clinical registry was performed from 1 January 2020 to 31 December 2020 at Hospital Serdang, Malaysia. Adult patients with type 2 diabetes mellitus had their medical records examined for disease complications, as reported by the patient at first contact with the DMTAC pharmacist.

Results

The study comprised a total of 495 participants with an average HbA1c of 10.5%. About 91% (n = 451) of the 495 patients were obese/overweight. Around 37.8% (n = 187) of diabetic patients are between the ages of 50 and 59, and 59% (n = 292) have had diabetes for less than 10 years. A total of 8.5% (n = 42) and 9.7% (n = 48) consume alcohol and smoke, respectively. Around 29.9% (n = 148) had one other comorbidity (hypertension or dyslipidemia), and 63.4% (n = 314) had two comorbidities. Regarding the prevalence of complications, there were 18.9% (n = 94) who had myocardial infarction, 11.1% (n = 55) who had stroke, and 9% (n = 45) who had CKD. Age (adjusted OR = 1.03; 95% CI 1.00 to 1.07; p = 0.041) and hypertension (adjusted OR = 4.06; 95% CI 1.21 to 13.60; p = 0.023) were significantly related with the prevalence of complications in patients with diabetes.

Conclusion

In our study, a BMI of more than 23 kg/m2 (obese/overweight) does not seem to be associated with the prevalence of complications. Age and hypertension, on the other hand, appear to be strong risk predictors of the incidence of complications. With the understanding of the recent outlook on diabetes, it is recommended that public education on the targeted population should be encouraged to negate these complications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13410-022-01131-x.

Hybrid molecules based on caffeic acid as potential therapeutics: A focused review

Caffeic acid-based compounds possess a high degree of structural diversity and show a variety of pharmacological properties, providing a useful framework for the discovery of new therapeutic agents. They are well-known analogues of antioxidants found in many natural products and synthetic compounds. The present review surveys the recent developments in structure-activity relationships (SAR) and mechanism of action (MOA) of various caffeic acid-containing compounds that play important roles in the design and synthesis of new bioactive molecules with antioxidant, antidiabetic, antiviral, antibacterial, anticancer, anti-inflammatory, and other properties. This review should provide inspiration to scientists in the research fields of organic synthesis and medicinal chemistry related to the development of new antioxidants with versatile therapeutic potential.

Factors Influencing the Desirability, Acceptability, and Adherence of Patients with Diabetes to Telemedicine

Background and Objectives: Telemedicine solutions have proven their value and efficacy in augmenting diabetes care. In addition to the availability of tools needed to implement telemedicine solutions for patients with diabetes, the patients’ desirability, acceptance, and adherence represent major burdens in implementing them. The main aim of this research is to evaluate which factors are influencing the desirability, acceptance, and adherence of patients with diabetes to telemedicine interventions in diabetes care. Materials and Methods: QTelemeDiab, a previously validated instrument for assessing patients’ desirability, acceptance, and adherence to telemedicine in diabetes care, was used on 114 enrolled patients with diabetes mellitus, in parallel with demographic, socio-economic, disease history, and psychometric data from all patients. Results: Left-skewed score distributions were observed for the QTelemeDiab total score (median = 166; skewness = −1.738), as well as all its components, thus denoting a high desirability, acceptance, and adherence towards telemedicine use. The presence of severe depression was associated with significant decreases in the QTelemeDiab score (148 vs. 167; p < 0.001), as well as on the desirability sub-score (101 vs. 115; p < 0.001) and adherence sub-score (30 vs. 35; p < 0.001). The presence of severe anxiety was associated with significant decreases in QTelemeDiab score (150 vs. 166), as well as the desirability sub-score (104 vs. 114; p = 0.008) and adherence sub-score (30 vs. 34; p = 0.012). Conclusions: There is a high desirability, acceptance, and adherence to the use of telemedicine interventions in patients with diabetes, both in special and in normal epidemiological settings. The presence of severe anxiety decreases the patient’s desirability, acceptance, and adherence, while the presence of severe depression decreases the patient’s desirability and adherence to the use of telemedicine interventions in diabetes care.

Investigating Temporal Patterns of Glycemic Control around Holidays

Maintaining good glycemic control is a central part of diabetes care. However, it can be a tedious task because many factors in daily living can affect glycemic control. To support management, a growing number of people living with diabetes are now being prescribed continuous glucose monitors (CGMs) for real-time tracking of their blood glucose levels. However, routine use of CGMs is also an invaluable source of patient-generated data for individual and population-level studies. Prior research has shown that festive periods such as holidays can be a notable contributor to overeating and weight gain. Thus, in this work, we sought to investigate patterns of glycemic control around the holidays, particularly Thanksgiving, Christmas, and New Year, by using 3-months of CGM data from 14 patients with Type 1 Diabetes. We leveraged clinically validated metrics for quantifying glycemic control from CGM data and well-established statistical tests to compare diabetes management on holiday weeks versus non-holiday weeks. Based on our analysis, we found that 86% of subjects (12 out of 14) had worse glycemic control (i.e., more ad-verse glycemic events) during holiday weeks compared to non-holiday weeks. This general trend was prevalent amongst most subjects, however, we also observed unique individual patterns of glycemic control. Our findings provide a basis for further research on temporal patterns in diabetes management and data-driven interventions to support patients and caregivers with maintaining good glycemic control all year round.

Effectiveness of a healthcare-based mobile intervention on sedentary patterns, physical activity, mental well-being and clinical and productivity outcomes in office employees with type 2 diabetes: study protocol for a randomized controlled trial

BACKGROUND

Prolonged sedentary time is associated with an increased incidence of chronic disease including type 2 diabetes mellitus (DM2). Given that occupational sedentary time contributes significantly to the total amount of daily sedentariness, incorporating programmes to reduce occupational sedentary time in patients with chronic disease would allow for physical, mental and productivity benefits. The aim of this study is to evaluate the short-, medium- and long-term effectiveness of a mHealth programme for sitting less and moving more at work on habitual and occupational sedentary behaviour and physical activity in office staff with DM2. Secondary aims. To evaluate the effectiveness on glycaemic control and lipid profile at 6- and 12-month follow-up; anthropometric profile, blood pressure, mental well-being and work-related post-intervention outcomes at 3, 6 and 12 months.

METHODS

Multicentre randomized controlled trial. A sample size of 220 patients will be randomly allocated into a control (n = 110) or intervention group (n = 110), with post-intervention follow-ups at 6 and 12 months. Health professionals from Spanish Primary Health Care units will randomly invite patients (18-65 years of age) diagnosed with DM2, who have sedentary office desk-based jobs. The control group will receive usual healthcare and information on the health benefits of sitting less and moving more. The intervention group will receive, through a smartphone app and website, strategies and real-time feedback for 13 weeks to change occupational sedentary behaviour.

VARIABLES

(1) Subjective and objective habitual and occupational sedentary behaviour and physical activity (Workforce Sitting Questionnaire, Brief Physical Activity Assessment Tool, activPAL3TM); 2) Glucose, HbA1c; 3) Weight, height, waist circumference; 4) Total, HDL and LDL cholesterol, triglycerides; (5) Systolic, diastolic blood pressure; (6) Mental well-being (Warwick-Edinburgh Mental Well-being); (7) Presenteeism (Work Limitations Questionnaire); (8) Impact of work on employees´ health, sickness absence (6th European Working Conditions Survey); (9) Job-related mental strain (Job Content Questionnaire). Differences between groups pre- and post- intervention on the average value of the variables will be analysed.

DISCUSSION

If the mHealth intervention is effective in reducing sedentary time and increasing physical activity in office employees with DM2, health professionals would have a low-cost tool for the control of patients with chronic disease.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04092738. Registered September 17, 2019.

Willingness to Receive mHealth Messages Among Diabetic Patients at Mizan Tepi University Teaching Hospital: Implications for Digital Health

Background

The growing access and use of mobile technology provide new tools for diabetic care and management. Mobile-based technology (mHealth) is considered as a useful tool to deliver healthcare services as a makeshift alternative for consultations and follow-up of diabetic patients. Therefore, this study aimed to scrutinize the willingness to receive mHealth messages and its associated factors among diabetic patients at Mizan Tepi University Teaching Hospital (MTUTH).

Methods

A cross-sectional study was conducted among two hundred thirty-three diabetic patients. Data were collected using a structured and pre-tested interviewer-administered questionnaire. Epidata manager and SPSS software were used to enter and analyze the data, respectively. Multivariable logistic regression analysis was carried out to identify the independent factors associated with patients' willingness to receive mHealth messages.

Results

Two hundred and thirty-three patients participated in this study with a 95% response rate. Majority of the patients (213, 91.4%) had a mobile phone. Among those who had mobile phones, 59.1%, (95% CI: 48-64) of patients were willing to receive mHealth messages from providers, if they were offered the opportunity. In the multivariable binary logistic regression analysis, monthly income >3000 ETB (AOR = 2.43; 95% CI (1.36-3.81)), owning smartphone (AOR = 3.85; 95% CI (1.67-4.89)), internet access in their mobile phone (AOR = 2.74; 95% CI (1.42-4.61)), perceived usefulness (AOR = 4.66; 95% CI (2.38-6.83)) and perceived ease to use (AOR = 3.87; 95% CI (1.57-5.46)) were identified as significant factors associated with diabetic patients' willingness to receive mHealth messages.

Conclusion

A high proportion of patients who had mobile phones were willing to receive mHealth messages. Monthly income, type of mobile phone, access to the internet on the mobile phone, perceived ease of use, and perceived usefulness were associated with willingness to receive mHealth messages. Therefore, focusing on these factors could provide insight for designing and implementing mHealth messages for diabetic patients.

Analysis of "Glycemic Outcomes During Real-World Hybrid Closed-Loop System Use by Individuals With Type 1 Diabetes in the United States"

In an article in the Journal of Diabetes Science and Technology, Arunachalum et al retrospectively analyzed glycemic outcomes, regarding the use of hybrid closed-loop (HCL) systems in individuals with type-1 diabetes (T1D) in the United States in a real-world evidence (RWE) setting. In clinical trials, diabetes technology has shown to improve time in range (TIR) as well as other glucose metrics. In the light of increasing the use of diabetes technology in the T1D population, why do we not see improvement in clinical outcomes? Is it cost-effective to increase the use diabetes technology? Does access to diabetes technology vary in the United States? There is a need for additional clinical studies evaluating the effectiveness of diabetes technology in T1D including health economic aspects.

Key Considerations for Understanding Usability of Digital Health Initiatives for Adults With Type 2 Diabetes: A Systematic Qualitative Literature Review

AIMS

The rapidly growing number of adults with type 2 diabetes globally means the uses and benefits of digital health initiatives to enhance self-management of diabetes warrant review. This systematic qualitative literature review aimed to understand usability of digital health initiatives for adults with type 2 diabetes.

METHODS

This systematic qualitative literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, the PRISMA 2020 Statement methodology. Three databases were used (SCOPUS, Medline, and CINAHL) to identify studies published from 2016 to 2021 that focused on experiences, evaluations, and usability of digital health initiatives aimed at helping adults with type 2 diabetes to self-manage their condition.

RESULTS

From the 407 studies identified, 35 studies were assessed for eligibility with 10 studies included in the final synthesis. Five main themes emerged: (1) unmet emotional needs, (2) enhancing self-management, (3) desire for education, (4) usability/user-experience, and (5) risk of biomedical marker reductionism.

CONCLUSIONS

This review identified 5 key themes for consideration to understand usability of digital health initiatives. If these unmet psychosocial needs of adults with type 2 diabetes are better addressed in digital health initiatives, enhanced daily self-management will lead to more optimal diabetes management which can increase overall health outcomes, reduce the risk of longer-term complications, enhance quality of life for type 2 diabetes and improve more widespread adoption of digital health initiatives.

Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

Background

Self-monitoring of blood glucose levels, food intake, and physical activity supports self-management of patients with type 2 diabetes mellitus (T2DM). There has been an increase in the development and availability of mobile health apps for T2DM.

Objective

The aim of this study is to explore the actual use of mobile health apps for diabetes among patients with T2DM and the main barriers and drivers among app users and nonusers.

Methods

An explanatory sequential design was applied, starting with a web-based questionnaire followed by semistructured in-depth interviews. Data were collected between July and December 2020. Questionnaire data from 103 respondents were analyzed using IBM SPSS Statistics (version 25.0). Descriptive statistics were performed for the actual use of apps and items of the Unified Theory of Acceptance and Use of Technology (UTAUT). The UTAUT includes 4 key constructs: performance expectancy (the belief that an app will help improve health performance), effort expectancy (level of ease associated with using an app), social influence (social support), and facilitating conditions (infrastructural support). Differences between users and nonusers were analyzed using chi-square tests for individual items. Independent 2-tailed t tests were performed to test for differences in mean scores per the UTAUT construct. In total, 16 respondents participated in the interviews (10 users and 6 nonusers of apps for T2DM). We performed content analysis using a deductive approach on all transcripts, guided by the UTAUT.

Results

Regarding actual use, 55.3% (57/103) were nonusers and 44.7% (46/103) were users of apps for T2DM. The main driver for the use of apps was the belief that using apps for managing diabetes would result in better personal health and well-being. The time and energy required to keep track of the data and understand the app were mentioned as barriers. Mean scores were significantly higher among users compared with nonusers of apps for T2DM for the constructs performance expectancy (4.06, SD 0.64 vs 3.29, SD 0.89; P<.001), effort expectancy (4.04, SD 0.62 vs 3.50, SD 0.82; P<.001), social influence (3.59, SD 0.55 vs 3.29, SD 0.54; P=.007), and facilitating conditions (4.22, SD 0.48 vs 3.65, SD 0.70; P<.001). On the basis of 16 in-depth interviews, it was recognized that health care professionals play an important role in supporting patients with T2DM in using apps. However, respondents noticed that their health care professionals were often not supportive of the use of apps for managing diabetes, did not show interest, or did not talk about apps. Reimbursement by insurance companies was mentioned as a missing facilitator.

Conclusions

Empowering health care professionals’ engagement is of utmost importance in supporting patients with T2DM in the use of apps. Insurance companies can play a role in facilitating the use of diabetes apps by ensuring reimbursement.

A 12-Month Follow-Up of the Effects of a Digital Diabetes Prevention Program (VP Transform for Prediabetes) on Weight and Physical Activity Among Adults With Prediabetes: Secondary Analysis

Background

The prevalence of diabetes is increasing rapidly. Previous research has demonstrated the efficacy of a diabetes prevention program (DPP) in lifestyle modifications that can prevent or delay the onset of type 2 diabetes among individuals at risk. Digital DPPs have the potential to use technology, in conjunction with behavior change science, to prevent prediabetes on a national and global scale.

Objective

The aim of this study is to investigate the effects of a digital DPP (Virgin Pulse [VP] Transform for Prediabetes) on weight and physical activity among participants who had completed 12 months of the program.

Methods

This study was a secondary analysis of retrospective data of adults with prediabetes who were enrolled in VP Transform for Prediabetes for 12 months of the program. The program incorporates interactive mobile computing, remote monitoring, an evidence-based curriculum, behavior tracking tools, health coaching, and online peer support to prevent or delay the onset of type 2 diabetes.

Results

The sample (N=1095) was comprised of people with prediabetes who completed at least 9 months of the VP Transform for Prediabetes program. Participants were 67.7% (n=741) female, with a mean age of 53.6 (SD 9.75) years. After 12 months, participants decreased their weight by an average of 10.9 lbs (5.5%; P<.001) and increased their physical activity by 91.2 (P<.001) minutes.

Conclusions

These results suggest that VP Transform for Prediabetes is effective at preventing type 2 diabetes through a significant reduction in body weight and increase of physical activity. Furthermore, these results suggest that the DPP remains effective 12 months after beginning the program. A prospective randomized controlled clinical study is warranted to validate these findings.

Association of the Coronavirus Disease 2019 Outbreak on the Diabetes Self-Management in Chinese Patients: An Analytical Cross-Sectional Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) outbreak has seriously affected people's lives, especially those with chronic diseases. Diabetes self-management, which plays an important role in glycaemic control and reducing the risk of acute and long-term complications, may be discouraged by social distancing.

PURPOSE

To evaluate the level of self-management activities in Chinese patients with type 2 diabetes mellitus (T2DM) during the COVID-19 pandemic.

PATIENTS AND METHODS

A survey of with 872 patients with T2DM in the inpatient and outpatient departments through face-to-face interviews was conducted from 1 July, 2020 to 30 September, 2020. The main outcome measures were glycaemic control status and level of self-management activities during the pandemic.

RESULTS

In terms of glycaemic control, the data showed that patients with fasting plasma glucose (FPG) < 7.0 mmol/L (36.4%), postprandial plasma glucose (PPG) < 10.0 mmol/L (26.3%), or glycosylated haemoglobin (HbA1c) < 7.0% (18.6%) in our investigation has well-controlled blood glucose level, and 11.9% of patients experienced blood glucose <3.9 mmol/L during the outbreak. The diabetes self-management of Chinese patients decreased and the final diabetes self-management score of the Chinese patients was 3.4 ± 1.45. Patients with higher education, diabetes education, comorbidities, and online consultations had higher diabetes self-management scores (P <0.05). Adherence to diabetes self-management in the normal glycaemic control group was higher than that in the substandard glycaemic control group (P<0.05). Among all participants, 72.1% of the patients reduced the frequency of hospital visits, and 44.8% considered that they had diabetes-related stress during the pandemic. The mean anxiety level score rated by 286 patients was 5.3±2.8.

CONCLUSION

The COVID-19 pandemic has affected diabetes self-management, including substandard glycemic control, increased diabetes-related stress, limited exercise range and medical visits. Therefore, future interventions should focus on the online management of chronic diseases and support online consultation' development and promotion, which can overcome physical distance and provide personalized services conveniently.

A Novel User Utility Score for Diabetes Management Using Tailored Mobile Coaching: Secondary Analysis of a Randomized Controlled Trial

Background

Mobile health applications have been developed to support diabetes self-management, but their effectiveness could depend on patient engagement. Therefore, patient engagement must be examined through multifactorial tailored behavioral interventions from an individual perspective.

Objective

This study aims to evaluate the usefulness of a novel user utility score (UUS) as a tool to measure patient engagement by using a mobile health application for diabetes management.

Methods

We conducted a subanalysis of results from a 12-month randomized controlled trial of a tailored mobile coaching (TMC) system among insurance policyholders with type 2 diabetes. UUS was calculated as the sum of the scores for 4 major core components (range 0-8): frequency of self-monitoring blood glucose testing, dietary and exercise records, and message reading rate. We explored the association between UUS for the first 3 months and glycemic control over 12 months. In addition, we investigated the relationship of UUS with blood pressure, lipid profile, and self-report scales assessing diabetes self-management.

Results

We divided 72 participants into 2 groups based on UUS for the first 3 months: UUS:0-4 (n=38) and UUS:5-8 (n=34). There was a significant between-group difference in glycated hemoglobin test (HbA_1c) levels for the 12-months study period (P=.011). The HbA_1c decrement at 12 months in the UUS:5-8 group was greater than that of the UUS:0-4 group [–0.92 (SD 1.24%) vs –0.33 (SD 0.80%); P=.049]. After adjusting for confounding factors, UUS was significantly associated with changes in HbA_1c at 3, 6, and 12 months; the regression coefficients were –0.113 (SD 0.040; P=.006), –0.143 (SD 0.045; P=.002), and –0.136 (SD 0.052; P=.011), respectively. Change differences in other health outcomes between the 2 groups were not observed throughout a 12-month follow-up.

Conclusions

UUS as a measure of patient engagement was associated with changes in HbA_1c over the study period of the TMC system and could be used to predict improved glycemic control in diabetes self-management through mobile health interventions.

Trial Registration

ClinicalTrial.gov NCT03033407; https://clinicaltrials.gov/ct2/show/NCT03033407

Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology

The COVID-19 pandemic has resulted in massive disruptions within health care, both directly as a result of the infectious disease outbreak, and indirectly because of public health measures to mitigate against transmission. This disruption has caused rapid dynamic fluctuations in demand, capacity, and even contextual aspects of health care. Therefore, the traditional face-to-face patient-physician care model has had to be re-examined in many countries, with digital technology and new models of care being rapidly deployed to meet the various challenges of the pandemic. This Viewpoint highlights new models in ophthalmology that have adapted to incorporate digital health solutions such as telehealth, artificial intelligence decision support for triaging and clinical care, and home monitoring. These models can be operationalised for different clinical applications based on the technology, clinical need, demand from patients, and manpower availability, ranging from out-of-hospital models including the hub-and-spoke pre-hospital model, to front-line models such as the inflow funnel model and monitoring models such as the so-called lighthouse model for provider-led monitoring. Lessons learnt from operationalising these models for ophthalmology in the context of COVID-19 are discussed, along with their relevance for other specialty domains.

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 and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are not limited anymore to a descriptive analysis of the data, as we can obtain greater value by identifying and predicting patterns resulting from inductive reasoning. Machine learning software programs that disclose the reasoning behind a prediction allow for “what-if” models by which it is possible to understand if and how, by changing certain factors, one may improve the outcomes, thereby identifying the optimal behavior. Currently, diabetes care is facing several challenges: the decreasing number of diabetologists, the increasing number of patients, the reduced time allowed for medical visits, the growing complexity of the disease both from the standpoints of clinical and patient care, the difficulty of achieving the relevant clinical targets, the growing burden of disease management for both the health care professional and the patient, and the health care accessibility and sustainability. In this context, new digital technologies and the use of artificial intelligence are certainly a great opportunity. Herein, we report the results of a careful analysis of the current literature and represent the vision of the Italian Association of Medical Diabetologists (AMD) on this controversial topic that, if well used, may be the key for a great scientific innovation. AMD believes that the use of artificial intelligence will enable the conversion of data (descriptive) into knowledge of the factors that “affect” the behavior and correlations (predictive), thereby identifying the key aspects that may establish an improvement of the expected results (prescriptive). Artificial intelligence can therefore become a tool of great technical support to help diabetologists become fully responsible of the individual patient, thereby assuring customized and precise medicine. This, in turn, will allow for comprehensive therapies to be built in accordance with the evidence criteria that should always be the ground for any therapeutic choice.

The Challenges of COVID-19 for People Living With Diabetes: Considerations for Digital Health

The coronavirus disease (COVID-19) is a global pandemic that significantly impacts people living with diabetes. Diabetes-related factors of glycemic control, medication pharmacodynamics, and insulin access can impact the severity of a COVID-19 infection. In this commentary, we explore how digital health can support the diabetes community through the pandemic. For those living with diabetes, digital health presents the opportunity to access care with greater convenience while not having to expose themselves to infection in an in-person clinic. Digital diabetes apps can increase agency in self-care and produce clinically significant improvement in glycemic control through facilitating the capture of diabetes device data. However, the ability to share these data back to the clinic to inform virtual care and enhance diabetes coaching and guidance remains a challenge. In the end, it requires an unnecessarily high level of technical sophistication on the clinic’s part and on those living with diabetes to routinely use their diabetes device data in clinic visits, virtual or otherwise. As the world comes together to fight the COVID-19 pandemic, close collaboration among the global diabetes community is critical to understand and manage the sustained impact of the pandemic on people living with diabetes.

Users' acceptability of a mobile application for persons with type 2 diabetes: a qualitative study

Background

The use of mobile health apps is now common in diabetes self-management and acceptability of such tools could help predict further use. There is limited research on the acceptability of such apps: use over time, the factors and features that influence self-management, how to overcome barriers, and how to use an app in relation to health-care personnel.

In this study, we aimed to obtain an in-depth understanding of users’ acceptability of a mobile app for diabetes self-management, and to explore their communication with health-care personnel concerning the app.

Methods

The study had a qualitative descriptive design. Two researchers conducted 24 semi-structured in-depth interviews with adults with type 2 diabetes who had used a digital diabetes diary app for 1 year, during participation in the Norwegian Study in the EU project RENEWING HeALTH. We recruited the participants in a primary health-care setting. The transcripts of the interviews were analyzed using qualitative content analysis on developing themes, which we interpreted according to a theory of acceptability. We used NVivo 11 Pro during the process.

Results

The users’ acceptability of the app diverged. Overall, the responses indicated that the use of a digital diabetes diary requires hard work, but could also ease the effort involved in following a healthy lifestyle and better-controlled levels of blood glucose. Crucial to the acceptability was that a routine use could give an overview of diabetes registration and give new insights into self-management. In addition, support from health-care personnel with diabetes knowledge was described as necessary, either to confirm the decisions made based on use of the app, or to get additional self-management support. There were gradual transitions between practical and social acceptability, where utility of the app seems to be necessary for both practical and social acceptability. Lack of acceptability could cause both digital and clinical distress.

Conclusions

Both practical and social acceptability were important at different levels. If the users found the utility of the app to be acceptable, they could tolerate some lack of usability. We need to be aware of both digital and clinical distress when diabetes apps form a part of relevant health-care.

Trial registrations

Self-management in Type 2 Diabetes Patients Using the Few Touch Application, NCT01315756, https://clinicaltrials.gov/show/NCT01315756 March 15, 2011.

Advances in Type 1 Diabetes Technology Over the Last Decade

The past 10 years have witnessed rapid advances in the technology used to treat patients with type 1 diabetes (T1D). While the disease burden is still high, these advances have contributed to improvements in both glycaemic control and quality of life for many of those affected. New technologies allow for individualisation of care, as patients are able to work with their providers to determine which systems best fit their lifestyle and needs. In addition, thanks to improved glucose monitoring technologies, patients can now simultaneously improve glycaemic control and reduce hypoglycaemia, thereby mitigating risk for acute and chronic complications. Technological advances in T1D care are rapidly moving us toward increasingly automated devices, which offer the promise of reduced disease burden. In this article, we review advances in glucose monitoring, insulin and glucagon delivery, and the applications and algorithms seeking to integrate novel technologies.

Rethinking Models of Outpatient Specialist Care in Type 2 Diabetes Using eHealth: Study Protocol for a Pilot Randomised Controlled Trial

Conventional outpatient services are unlikely to meet burgeoning demand for diabetes services given increasing prevalence of diabetes, and resultant impact on the healthcare workforce and healthcare costs. Disruptive technologies (such as smartphone and wireless sensors) create an opportunity to redesign outpatient services. In collaboration, the Department of Diabetes and Endocrinology at Brisbane Princess Alexandra Hospital, the University of Queensland Centre for Health Services Research and the Australian e-Health Research Centre developed a mobile diabetes management system (MDMS) to support the management of complex outpatient type 2 diabetes mellitus (T2DM) adults. The system comprises of a mobile App, an automated text-messaging feedback and a clinician portal. Blood glucose levels (BGL) data are automatically transferred by Bluetooth-enabled glucose meter to the clinician portal via the mobile App. The primary aim of the study described here is to examine improvement in glycaemic control of a new model of care employing MDMS for patients with complex T2DM attending a tertiary level outpatient service. A two-group, 12-month, pilot pragmatic randomised control trial will recruit 44 T2DM patients. The control group will receive routine care. The intervention group will be supported by the MDMS enabling the participants to potentially better self-manage their diabetes, and the endocrinologists to remotely monitor BGL and to interact with patients through a variety of eHealth modalities. Intervention participants will be encouraged to complete relevant pathology tests, and report on current diabetes management through an online questionnaire. Using this information, the endocrinologist may choose to reschedule the appointment or substitute it with a telephone or video-consultation. This pilot study will guide the conduct of a large-scale study regarding the capacity for a new model of care. This model utilises multimodal eHealth strategies via the MDMS to primarily improve glycaemic control with secondary aims to improve patient experience, reduce reliance on physical clinics, and decrease service delivery cost.

An expandable approach for design and personalization of digital, just-in-time adaptive interventions

Objective

We aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized intervention delivery strategies to support self-management by optimizing various intervention components tailored to people's individual needs, momentary contexts, and psychosocial variables.

Materials and Methods

We propose a template-based digital intervention design mechanism enabling the configuration of evidence-based, just-in-time, adaptive intervention components. The design mechanism incorporates a rule definition language enabling experts to specify triggering conditions for interventions based on momentary and historical contextual/personal data. The framework continuously monitors and processes personal data space and evaluates intervention-triggering conditions. We benefit from reinforcement learning methods to develop personalized intervention delivery strategies with respect to timing, frequency, and type (content) of interventions. To validate the personalization algorithm, we lay out a simulation testbed with 2 personas, differing in their various simulated real-life conditions.

Results

We evaluate the design mechanism by presenting example intervention definitions based on behavior change taxonomies and clinical guidelines. Furthermore, we provide intervention definitions for a real-world care program targeting diabetes patients. Finally, we validate the personalized delivery mechanism through a set of hypotheses, asserting certain ways of adaptation in the delivery strategy, according to the differences in simulation related to personal preferences, traits, and lifestyle patterns.

Conclusion

While the design mechanism is sufficiently expandable to meet the theoretical and clinical intervention design requirements, the personalization algorithm is capable of adapting intervention delivery strategies for simulated real-life conditions.

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.

A Prospective Cohort Study on the Management of Young Patients with Newly Diagnosed Type 2 Diabetes Using Mobile Medical Applications

INTRODUCTION

The aim of this study was to evaluate the effect of using a mobile medical application (app) for self-monitoring of blood glucose (SMBG) and blood glucose control in young patients with newly diagnosed type 2 diabetes mellitus (T2DM).

METHODS

This was a prospective cohort study involving young patients with newly diagnosed T2DM. On a voluntary basis, the patients chose to be included in a group in which they were followed up for 24 weeks with a mobile medical app and the changes in laboratory data and frequency of SMBG observed via the app, or in a group in which they received traditional medical treatment and follow-up. The results between the two groups were compared.

RESULTS

A total of 126 patients signed the informed consent form and were enrolled in the study, of whom 66 chose the mobile medical group, which used the mobile medical app, and the remaining 60 patients chose the traditional medical treatment model. The differences in the physical and chemical indicators between the app-using group and the traditional medical model group were not statistically significant at baseline (p  > 0.05). At 24 weeks of treatment, the levels of glycosylated hemoglobin A1c (HbA1c), total cholesterol, triglycerides, and low-density lipoprotein cholesterol were significantly reduced in all patients compared to before treatment (p  < 0.05). The app-using group had a higher HbA1c compliance rate and higher frequency of both SMBG and doctor-patient communication than the traditional medical model group (p  < 0.01). The HbA1c compliance rate of patients using the mobile medical app was 1.53-fold higher than that of the traditional medical model group. At 24 weeks, HbA1c was negatively correlated with the frequency of SMBG (r  = - 0.208, p  = 0.020) and the frequency of doctor-patient communication (r  = - 0.323, p  = 0.000). Additionally, there was a positive correlation between the frequency of SMBG and doctor-patient communication (r  = 0.579, p  = 0.000).

CONCLUSION

A mobile medical app is helpful to young patients with newly diagnosed T2DM for monitoring their blood glucose level and improving their blood glucose control to meet the standard.