The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 Study)

Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial

Background

Mental health problems are prevalent among people with diabetes, yet often under-diagnosed. Smart sensing, utilizing passively collected digital markers through digital devices, is an innovative diagnostic approach that can support mental health screening and intervention. However, the acceptance of this technology remains unclear. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aimed to investigate (1) the acceptance of smart sensing in a diabetes sample, (2) the determinants of acceptance, and (3) the effectiveness of an acceptance facilitating intervention (AFI).

Methods

A total of N = 132 participants with diabetes were randomized to an intervention group (IG) or a control group (CG). The IG received a video-based AFI on smart sensing and the CG received an educational video on mindfulness. Acceptance and its potential determinants were assessed through an online questionnaire as a single post-measurement. The self-reported behavioral intention, interest in using a smart sensing application and installation of a smart sensing application were assessed as outcomes. The data were analyzed using latent structural equation modeling and t-tests.

Results

The acceptance of smart sensing at baseline was average (M = 12.64, SD = 4.24) with 27.8% showing low, 40.3% moderate, and 31.9% high acceptance. Performance expectancy (γ = 0.64, p < 0.001), social influence (γ = 0.23, p = .032) and trust (γ = 0.27, p = .040) were identified as potential determinants of acceptance, explaining 84% of the variance. SEM model fit was acceptable (RMSEA = 0.073, SRMR = 0.059). The intervention did not significantly impact acceptance (γ = 0.25, 95%-CI: -0.16-0.65, p = .233), interest (OR = 0.76, 95% CI: 0.38-1.52, p = .445) or app installation rates (OR = 1.13, 95% CI: 0.47-2.73, p = .777).

Discussion

The high variance in acceptance supports a need for acceptance facilitating procedures. The analyzed model supported performance expectancy, social influence, and trust as potential determinants of smart sensing acceptance; perceived benefit was the most influential factor towards acceptance. The AFI was not significant. Future research should further explore factors contributing to smart sensing acceptance and address implementation barriers.

A randomized controlled trial of medication adherence and management of risk factors for secondary prevention of stroke (MaMoRS) using a smartphone-based application

BACKGROUND

There are little data on the use of smartphone-based applications for medication adherence and risk-factor control for the secondary prevention of stroke in low-and-middle-income countries (LMICs).

AIMS

The aim was to determine whether a smartphone-based app improved medication adherence, risk-factor control, and provided health education to stroke survivors for lifestyle and behavioral modifications.

METHODS

An unblinded, single-center randomized controlled double arm trial with 1:1 allocation among stroke survivors was performed in South India. The primary outcome was medication adherence, with co-primary outcomes of lifestyle and behavioral factors and control of vascular risk factors, at 3 and 6 months.

RESULTS

Among 351 stroke survivors screened, 209 were recruited. The mean (standard deviation (SD)) age of the intervention (n = 105) group was 60 (12) years and that of the control (n = 104) group was 60 (10) years. In the primary outcome, mean medication adherence significantly improved in the intervention group with a between group difference of 0.735 (95% confidence interval (CI) = 0.419 to 1.050), p < 0.001. Being in intervention group (OR = 4.5; 95% CI = 2.3 to 8.9), stroke recurrence (OR = 3.3 (95% CI = 1.9 to 7.8)), and regular physician visits (OR = 2.1; 95% CI = 1.0 to 4.4) were significant predictors of good medication adherence. Considering the co-primary outcomes, compared to the control group, participants in the intervention group had a greater improvement in self-reported healthy diet intake (p = 0.003), intake of fruits (p = 0.005), and were physically more active (p = 0.001). At 6 months, mean fasting blood sugar (p = 0.005) and high-density lipoprotein cholesterol higher (p = 0.024) in the intervention group.

CONCLUSIONS

The use of a mobile app is an effective method to improve medication adherence and risk-factor control in stroke survivors and is feasible in LMICs like India.

DATA ACCESS STATEMENT

Data used during the study are available from the corresponding author on request.

TRIAL REGISTRATION

The study is registered in Clinical Trial Registry of India (CTRI/2022/06/042980).

Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Self-management is pivotal in addressing noncommunicable diseases, such as diabetes. The increased availability of digital behaviour change interventions (DBCIs) delivered through mobile health apps offers unprecedented opportunities to enhance self-management and improve health outcomes. However, little is known about the characteristics of DBCIs for diabetes that significantly impact glycaemic control. Therefore, our systematic review with meta-analysis aimed to summarize characteristics and behaviour change components in DBCIs for diabetes self-management and explore potential associations with metabolic outcomes.

METHODS

A systematic search was conducted in PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Scopus to identify randomized controlled trials published until November 2023. The main outcome variable was the change in the mean difference of HbA1c levels between baseline and follow-up across intervention and control groups. Random-effects meta-regression was used to explore variation in glycaemic control as a function of prespecified characteristics of study designs and app interventions.

FINDINGS

A total of 57 studies was included in the analysis, showing a statistically significant percentage point reduction in HbA1c for the intervention group compared to the control arm (-0.36, 95% CI = -0.46 to -0.26, p < 0.001). The inclusion of "self-monitoring of behaviour" as a behaviour change technique (β = -0.22, p = 0.04) and "taking medication" as a target behaviour (β = -0.20, p = 0.05) was associated with improved metabolic outcomes.

INTERPRETATION

Our analyses endorse the use of diabetes self-management apps, highlighting characteristics statistically associated with intervention effectiveness and guiding the design of more effective DBCIs.

FUNDING

This project received funding from the European Union's Horizon 2020 programme.

Clinical impact of an integrated e-health system for diabetes self-management support and shared decision making (POWER2DM): a randomised controlled trial

AIMS/HYPOTHESIS

There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management.

METHODS

Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire - Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately.

RESULTS

A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) (p<0.001) compared with no change in HbA1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p=0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed.

CONCLUSIONS/INTERPRETATION

POWER2DM improves HbA1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03588104.

FUNDING

This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444).

European Survey on Adult People With Type 1 Diabetes and Their Caregivers: Insights Into Perceptions of Technology

BACKGROUND

Type 1 diabetes (T1D) is a complex condition requiring constant monitoring and self-management. The landscape of diabetes management is evolving with the development of new technologies. This survey aimed to gain insight into the perceptions and experiences of people with T1D (PWD) and their caregivers on the use of technology in diabetes care, and identify future needs for T1D management.

METHODS

PWD and caregivers (≥18 years) living in five European countries (France, Germany, Italy, Spain, and the United Kingdom) completed an online survey. Data were collected during July and August 2021.

RESULTS

Responders included 458 PWD and 54 caregivers. More than 60% of PWD perceived devices/digital tools for diabetes management as useful and 63% reported that access to monitoring device data made their life easier. Nearly half of participants hoped for new devices and/or digital tools. While approximately one-third of all PWD had used teleconsultation, perceptions and usage varied significantly between countries and by age (both P < .0001), with the lowest use in Germany (20%) and the highest in Spain (48%). The proportions of PWD contributing to diabetes care costs varied by device and were highest for smart insulin pen users at 83% compared with 44% for insulin pen users and 37% for insulin pump users. One-quarter (24%) of PWD and 15% of caregivers felt they lacked knowledge about devices/digital tools for T1D.

CONCLUSIONS

Most PWD and caregivers had positive perceptions and experiences of new technologies/digital solutions for diabetes management, although improved support and structured education for devices/digital tools are still required.

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

BACKGROUND

There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations.

OBJECTIVES

To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care.

SEARCH METHODS

We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section.

SELECTION CRITERIA

We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy.

DATA COLLECTION AND ANALYSIS

We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.  Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available.

MAIN RESULTS

We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.  Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.  Combinations of the three most effective QI strategies were estimated to lead to the below effects:  - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;  - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;  - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other).

AUTHORS' CONCLUSIONS

There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.

Experiences with telemedicine among family medicine residents at king saud university medical city during the COVID-19 pandemic: a cross-sectional study

BACKGROUND

The healthcare system experienced various challenges during the coronavirus disease 2019 (COVID-19) pandemic, and a wide range of safety measures were implemented, including limiting the number of patients allowed to visit primary care clinics and follow-up through telemedicine clinics. These changes have accelerated the growth of telemedicine in medical education and affected the training of family medicine residents throughout Saudi Arabia. Therefore, this study aimed to evaluate the experiences of family medicine residents with telemedicine clinics as a part of their clinical training during the COVID-19 pandemic.

METHODS

A cross-sectional study was conducted with 60 family medicine residents at King Saud University Medical City, Riyadh, Saudi Arabia. An anonymous 20-item survey was administered between March and April 2022.

RESULTS

The participants included 30 junior and 30 senior residents, with a 100% response rate. The results revealed that most (71.7%) participants preferred in-person visits during residency training, and only 10% preferred telemedicine. In addition, 76.7% of the residents accepted the inclusion of telemedicine clinics in training if such clinics constituted not more than 25% of the training program. Moreover, most participants reported receiving less clinical experience, less supervision, and less discussion time with the attending supervisor when training in telemedicine clinics compared with in-person visits. However, most (68.3%) participants gained communication skills through telemedicine.

CONCLUSIONS

Implementing telemedicine in residency training can create various challenges in education and influence clinical training through less experience and less clinical interaction with patients if it is not structured well. With the growth of digital healthcare, further structuring and testing of a paradigm that involves using telemedicine in residents' training programs prior to implementation should be considered for better training and patient care.

Effect of smartphone apps on glycemic control in young patients with type 1 diabetes: A meta-analysis

Objectives

Achieving glycemic control is a great challenge for young patients with type 1 diabetes (T1D), especially during the transition from childhood to adulthood. As various smartphone apps have been developed to improve glycemic control in T1D, we performed a meta-analysis of randomized controlled trials to assess the effect of smartphone apps on glycemic control in young patients with T1D.

Methods

We systematically searched PubMed, Embase, and the Cochrane Library for randomized controlled trials comparing combined usual care and smartphone app treatment to usual care alone. This meta-analysis is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The primary outcomes were the weighted difference in means (WMD) of HbA1c change from baseline and the person-years incidence of mild hypoglycemia or severe hypoglycemia between intervention and control groups. We assessed pooled data by use of a random-effects model.

Results

Of 1,190 identified studies, nine were eligible and included in our analysis (N = 748 participants). Relative to the control, using smartphone apps yielded a non-significant reduction in glycated hemoglobin (HbA1c) (WMD = −0.26, 95% CI: −0.56 to 0.05; p = 0.10) and no increased frequency of mild hypoglycemia (WMD = 1.87, 95% CI: −1.52 to 5.27; p = 0.49) or severe hypoglycemia (WMD = −0.04, 95% CI: −0.35 to 0.27; p = 0.80). In further subgroup analysis, compared with the recording-style app group, the auxiliary-style app group exhibited a significant reduction in HbA1c (WMD = −0.83, 95% CI: −1.10 to −0.56, p &lt; 0.001).

Conclusion

The current pooled data analysis did not reveal a significant reduction in HbA1c in young patients with T1D undergoing treatment with smartphone apps and usual care in combination. However, auxiliary-style apps with insulin or carbo calculators were beneficial in reducing HbA1c.

Clinical evaluation of the implementation of the first pilot Russian integrated program for an integrated approach to the management of diabetes mellitus “NORMA”

BACKGROUND: Despite progress in the treatment of patients with diabetes mellitus (DM), the problem of achieving target values of glycemic control remains relevant. In this regard, the search for new integrated solutions that could strengthen disease control and improve clinical outcomes becomes relevant.

AIM: To assess the impact of the developed integrated approach to disease management on the clinical and metabolic outcomes of patients with type 1 (T1DM) and type 2 diabetes mellitus (T2DM) participating in the “NORMA” pilot program for 3 and 6 months.

MATERIALS AND METHODS: “NORMA” is the first Russian program designed to implement an integrated approach to DM management combines structured online education, blood glucose monitoring, supervision by endocrinologist, and administrative support. Interium retrospective analysis analysis of pre-existing data generated in the Program was performed from October 2020 to November 2021. Adults (≥18 years) with uncontrolled T1DM or T2DM on insulin (HbA1c>7,0%) with duration of DM ≥6 months were included. The following characteristics were considered: social-demographic parameters, duration of DM, complications, HbA1c, hypoglycemia events, daily insulin dose, patients’ perception of DM checklist (scaled 1-10), level of DM knowledge (questionnaire of 20 points).

RESULTS: Data from 185 persons were analyzed: 132 with T1DM and 53 with T2DM, 67% women, the mean age was 41.3±14.4 years; the median DM duration was 12.0 [6.0; 19.0] years, 30 persons (16.3%) were free of any DM complications. Mean HbA1c decreased from 8.8±1.5% to 7.4±1.2% at month 3, and to 7.6±1.5% at month 6 (p<0.001). HbA1c <7.0% was achieved in 38.9% and 38.1% participants after 3 and 6 months, respectively. The total insulin dose has not changed within the program. The DM knowledge level after 3 months of Program increased significantly by 25.4±15.0% (p<0.001). The mean scores of patients’ perceptions of DM after 3 and 6 months increased by 2.1±10.2 % and 2.4±11.0 % (p<0.01), but the median scores (interquartile range) did not change: 0.00% (-3.00–6.00%) and 0.50% (-3.00–9.00%) respectively.

CONCLUSION: In a real-life setting, the implementation of an integrated approach to the diabetes management was associated with the improvement of glycemic control without significant changes of total insulin dose.

Increase Access, Reduce Disparities: Recommendations for Modifying Medicaid CGM Coverage Eligibility Criteria

Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency's CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.

Rural Telehealth Visits in the Management of Type 1 Diabetes

INTRODUCTION

Despite advances in and increased adoption of technology, glycemic outcomes for individuals with type 1 diabetes (T1D) have not improved. Access to care is limited for many, in part due to a shortage of endocrinologists and their concentration in urban areas. Managing T1D via telehealth has potential to improve glycemic outcomes, as the barriers of travel-related time and cost are mitigated.

METHODS

Our endocrine telehealth program started in 2013 and currently provides care to nine rural community hospitals in Nebraska and Iowa. A retrospective cohort study was performed to evaluate glycemic outcomes in people with T1D who received care at these telehealth clinics from 2013-2019. Data were collected on age, race, gender, prior diabetes provider, use of diabetes technology, and A1c values over time.

RESULTS

One hundred thirty-nine individuals were followed for an average duration of 32 months (range 4-69 months). Sixty-six percent of people were previously under the care of an endocrinologist. The most common therapeutic action, in addition to insulin adjustment, was addition of a CGM (52%). Each year in telemedicine care was associated with a decline of 0.13% in A1c (95% CI: -0.20, -0.06). There was no association between A1c and age or gender. When stratifying by previous diabetes provider, all groups had a statistically significant decline in A1c, even those with a previous endocrine provider. There was no statistically significant decline in A1c based on addition of technology.

CONCLUSION

We have shown that traditional telehealth visits are an effective way to provide care for people with T1D long-term and may provide distinct advantages to home telehealth visits.

Information and Communication Technologies in Lung Transplantation: Perception of Patients and Medical Teams

Optimal therapeutic management is a major determinant of patient prognosis and healthcare costs. Information and communication technologies (ICTs) represent an opportunity to enhance therapeutic management in complex chronic diseases, such as lung transplantation (LT). The objective of this study was to assess the preferences of LT patients and healthcare professionals regarding ICTs in LT therapeutic management. A cross-sectional opinion survey was conducted among lung transplant patients and healthcare professionals from the French lung transplantation centers. Five ICTs were defined (SMS, email, phone, internet, and smartphone application) in addition to face-to-face communication. An unsupervised approach by Principal Component Analysis (PCA) identified lung transplant patient profiles according to their preferences for ICTs. Fifty-three lung transplant patients and 15 healthcare professionals of the French LT centers were included. Both expected ICTs for treatment management and communication. Phone call, face-to-face, and emails were the most preferred communication tools for treatment changes and initiation. PCA identified four ICTs-related profiles (“no ICT”, “email”, “SMS”, and “oral communication”). “Email” and “oral communication” profiles are mainly concerned with treatment changes and transmission of new prescriptions. The “SMS” profile expected reminders for healthcare appointments and optimizing therapeutic management. This study provides practical guidance to enhance LT therapeutic management by ICT intervention. The type of ICT used should take into account patient profiles to improve adherence and thereby the prognosis. A combination of strategies including information, education by a multidisciplinary team, and reminders is a promising approach to ensure an optimal management of our patients.

High engagement in mobile peer support is associated with better glycemic control in type 1 diabetes: a real-world study

AIMS

Peer support for diabetes has become convenient and interactive following the emergence of mobile health (mHealth). We aimed to evaluate the association between engagement in peer support via mHealth app and glycemic control in type 1 diabetes (T1D).

METHODS

This retrospective study included adults with T1D who had joined the mobile community "TangTangQuan (TTQ)" since May 2018 for at least one year. "Like", "comment" and "share" were the major interaction indicators of mobile community and were used to assess engagement in peer support. The patients were divided into four engagement groups by quartile. The primary outcome was the change in HbA_1c , mean fasting blood glucose (FBG) and postprandial blood glucose (PBG) from baseline to the 12th month. Other outcomes included the change of self-monitoring of blood glucose frequency, hypoglycemia frequency, and the proportion of reaching optimal glycemic control.

RESULTS

Among the 693 individuals, the HbA_1c , mean FBG and PBG improved in the 12th month. Multiple regression analysis showed that higher engagement in peer support was associated with a greater reduction of HbA_1c (β=-0.45, P<0.001) and mean FBG (β=-0.82, P<0.001). In the subgroup of poor glycemic control, the association between engagement in peer support and glycemic improvement still remained (HbA_1c : β=-0.86, P=0.002; FBG: β=-1.36, P=0.001). The engagement in mobile peer support was positively correlated with educational level (OR=1.42, P=0.042), household income (OR=1.43, P=0.013), and the use of continuous subcutaneous insulin infusion (OR=1.73, P=0.009).

CONCLUSION

High engagement in mobile peer support was associated with better glycemic control in adults with T1D.

IBD Monitor: Romanian National Mobile Application for Inflammatory Bowel Disease Personalized Treatment and Monitoring

Background: In the last 30 years, we have seen an increase in the incidence of inflammatory bowel disease (IBD). Most cases are diagnosed in the 2nd and 3rd decades of life, a population group that is most familiar with the latest innovations in technology. Patients want to obtain more information about their disease and have complete control over the pathology, while reducing physical meetings with their doctor. Starting from these ideas, the present study aimed to develop a mobile application (app) to support IBD patients on symptoms/events reporting and on treatment administration monitoring. Methods: A multidisciplinary team was created to document and develop the app requirements and design its functionality. The app was beta-tested by several IBD patients. Their feedback was used to further refine the app. Results: We developed connected apps for both smartphones and smartwatches, with dedicated sections for event reporting and medication administration reminders/reporting. Conclusions: The development of apps dedicated to IBD patients is still in early progress. By creating this app, we aim to improve the evolution and compliance of IBD patients and to obtain new information that will have a beneficial impact on the management of these patients and open the door for personalized medicine.

Type 1 diabetes and the challenges of emotional support in crisis situations: results from a feasibility study of a multidisciplinary teleintervention

The association between type 1 diabetes and mental health disorders could be exacerbated in a stressful environment. This study aimed to evaluate the feasibility of a teleguided intervention on emotional disorders in patients with type 1 diabetes during the COVID-19 outbreak. This study was performed during the social distancing period in the COVID-19 outbreak in Brazil. Individuals with type 1 diabetes aged ≥ 18 years were selected to receive a teleguided multidisciplinary intervention or the usual care plus an educational website access. The proposed intervention aimed addressing aspects of mental health, diabetes care and lifestyle habits during the pandemic. The feasibility outcome included the assessment of recruitment capability and adherence to the proposed intervention. Moreover, we evaluated the presence of positive screening for emotional disorders (Self Report Questionnaire 20) after a 16-week intervention, patients' perceptions of pandemic-related changes, diabetes-related emotional distress, eating disorders, and sleep disorders. Data were analyzed with the intent-to-treat principle. Fifty-eight individuals (mean age, 43.8 ± 13.6 years) were included (intervention group, n = 29; control group, n = 29). At the end of the study, a total of 5 participants withdrew from the study in the intervention group compared to only 1 in the control group. Participants who dropout from the study had similar mean age, sex and income to those who remained in the study. The analysis of mental health disorders was not different between the groups at the follow up: a positive screening result was found in 48.3% and 34.5% of participants in the intervention and control groups, respectively (P = 0.29). The intervention group felt more supported in their diabetes care during the social distancing period (82.8% vs. 48.3% in the control group, P < 0.01). Our study identified a disproportionate higher number of withdrawals in the intervention group when compared to the control group. This difference may have compromised the power of the study for the proposed assessments and should be reevaluated in future studies.Trial registration: ClinicalTrials.gov (NCT04344210). Date of registration: 14/04/2020.

How use of continuous glucose monitoring can address therapeutic inertia in primary care

A significant proportion of individuals with diabetes have suboptimal glycemic management. Studies have shown that persistent hyperglycemia significantly increases the risks for both acute and long-term microvascular and macrovascular complications of diabetes. A key contributor to suboptimal glycemic management is therapeutic inertia in which clinicians delay intensifying therapy when patients are not meeting their glycemic goals. During the past five years, an increasing number of individuals with type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D) have adopted use of continuous glucose monitoring (CGM) for daily measurement of glucose levels. As demonstrated in numerous clinical trials and real-world observational studies, use of CGM improves glycated hemoglobin (HbA1c) and reduces the occurrence and severity of hypoglycemia. However, for primary care clinicians who are unfamiliar with using CGM, integrating this technology into clinical practice can be daunting. In this article, we discuss the benefits and rationale for using CGM compared with traditional blood glucose monitoring (BGM), review the evidence supporting the clinical value of CGM in patients with T1D and T2D, and describe how use of CGM in primary care can facilitate appropriate and more timely therapy adjustments.

Telemedicine for the Clinical Management of Diabetes; Implications and Considerations After COVID-19 Experience

Telemedicine is a clinical approach that was seldom used in the day-to-day practice, if not only in certain settings, before the COVID-19 pandemic. As stated by the WHO, telemedicine is: the delivery of health care services, where distance is a critical factor, by all health care professionals using information and communication technologies (ICT) for the exchange of valid information for diagnosis, treatment and prevention of disease and injuries, …. Telemedicine has actually represented the most useful and employed tool to maintain contacts between patients and physicians during the period of physical distance imposed by the pandemic, especially during the lockdown. Diabetes in particular, a chronic disease that often needs frequent confronting between patient and health professionals has taken advantage of the telehealth approach. Nowadays, technological tools are more and more widely used for the management of diabetes. In this review results obtained by telemendicine application in type 1 and type 2 diabetic individuals during COVID-19 are revised, and future perspectives for telemedicine use to manage diabetes are discussed.

Type 1 diabetes and the challenges of emotional support in crisis situations: results from a randomized clinical trial of a multidisciplinary teleintervention

The association between type 1 diabetes and mental health disorders could be exacerbated in a stressful environment. This study aimed to evaluate the effectiveness of a teleguided intervention on emotional disorders in patients with type 1 diabetes during the COVID-19 outbreak. An open-label clinical trial was performed during the social distancing period in the COVID-19 outbreak in Brazil. Individuals with type 1 diabetes aged ≥ 18 years were randomized to receive a teleguided multidisciplinary intervention or the usual care plus an educational website access. The primary outcome was a positive screening for emotional disorders (Self Report Questionnaire 20) after a 16-week intervention. Secondary outcomes included evaluation of patients’ perceptions of pandemic-related changes, diabetes-related emotional distress, eating disorders, and sleep disorders. Data were analyzed with the intent‐to‐treat principle. Fifty-eight individuals (mean age, 43.8 ± 13.6 years) were included (intervention group, n = 29; control group, n = 29). The primary outcome was not different between the groups. The intervention group felt more supported in their diabetes care during the social distancing period (82.8% vs. 48.3% in the control group, P < 0.01). Both groups reported a similar self-perceived worsening of physical activity habits and mental health during the outbreak. There was no benefit to using the telehealth strategy proposed for emotional disorders in patients with type 1 diabetes during the COVID-19 outbreak. Further studies are needed to determine the impact on metabolic parameters and to understand why it is so difficult to emotionally support these patients.

Trail Registration: ClinicalTrials.gov (NCT04344210), 14/04/2020.

The Effectiveness of Telemedicine Solutions in Type 1 Diabetes Management: A Systematic Review and Meta-analysis

BACKGROUND

Telemedicine holds a potential to strengthen self-management support outside health care settings in the everyday management of type 1 diabetes (T1D). However, existing effectiveness reviews are older or include a relatively narrow focus on specific definitions of telemedicine or included databases.

OBJECTIVE

To conduct a systematic review of the effectiveness of telemedicine solutions versus any comparator on diabetes-related outcomes among people with T1D.

METHODS

Studies including adults (≥18 years) with T1D published before October 14, 2020, were eligible. Primary outcome was glycated hemoglobin (HbA1c, %). The Cochrane Library, PubMed, EMBASE, and CINAHL were searched. Meta-analysis based on the mean difference in HbA1c% was used to pool effects. The Cochrane tool was applied to assess risk-of-bias, and the certainty of evidence was graded using the GRADE approach.

RESULTS

A total of 22 studies were included (with 1615 participants). Treatment effect for HbA1c% favored telemedicine (mean difference of -0.26% [95% confidence interval:-0.37% to -0.15%]) with moderate effect certainty. Heterogeneity was moderate (I² = 33.30%). Although not significant, secondary outcomes were all in favor of telemedicine except number of severe hypoglycemic events and diabetes knowledge, but the certainty of the evidence for those outcomes was all low or very low.

DISCUSSION

Reducing average HbA1c% levels are important to combat the risk of diabetic complications and premature death. However, the evidence mostly consist of small studies with a relative short duration and the estimated pooled effect is smaller than could be expected from quality improvement strategies in general for diabetes management.

PROSPERO NUMBER

CRD42020123565.

Remote Pharmacist-Assisted Flash Continuous Glucose Monitoring Improves Glycemic Outcomes in Patients With Poorly Controlled Diabetes: A Retrospective Case Series

This article reports on a retrospective case series evaluating glycemic outcomes using a flash continuous glucose monitoring (CGM) system in pharmacist-managed diabetes cases. The flash CGM system was used during initial assessment of patients' diabetes control and then continued throughout the intervention to ensure the safety and efficacy of the glycemic interventions. The Cloud-based CGM software was used to monitor patients remotely and assess their glycemic metrics. Action plans were created to address areas of most pressing concern, ensuring reduction or elimination of hypoglycemia, correction of hyperglycemia, and minimization of glycemic variability. In these complex cases, use of the flash CGM system in conjunction with lifestyle and medication interventions safely and effectively improved diabetes management and achieved targeted glucose outcomes.

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

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

Glycemic Disorder Risk Remote Monitoring Program in the COVID-19 Very Elderly Patients: Preliminary Results

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. This was the basis for the “GER-e-TEC COVID study,” an experiment involving the use of the smart MyPredi^TM e-platform to automatically detect the exacerbation of glycemic disorder risk in COVID-19 older diabetic patients.

Methods: The MyPredi^TM platform is connected to a medical analysis system that receives physiological data from medical sensors in real time and analyzes this data to generate (when necessary) alerts. An experiment was conducted between December 14th, 2020 and February 25th, 2021 to test this alert system. During this time, the platform was used on COVID-19 patients being monitored in an internal medicine COVID-19 unit at the University Hospital of Strasbourg. The alerts were compiled and analyzed in terms of sensitivity, specificity, positive and negative predictive values with respect to clinical data.

Results: 10 older diabetic COVID-19 patients in total were monitored remotely, six of whom were male. The mean age of the patients was 84.1 years. The patients used the telemedicine solution for an average of 14.5 days. 142 alerts were emitted for the glycemic disorder risk indicating hyperglycemia, with an average of 20.3 alerts per patient and a standard deviation of 26.6. In our study, we did not note any hypoglycemia, so the system emitted any alerts. For the sensitivity of alerts emitted, the results were extremely satisfactory, and also in terms of positive and negative predictive values. In terms of survival analysis, the number of alerts and gender played no role in the length of the hospital stay, regardless of the reason for the hospitalization (COVID-19 management).

Conclusion: This work is a pilot study with preliminary results. To date, relatively few projects and trials in diabetic patients have been run within the “telemedicine 2.0” setting, particularly using AI, ICT and the Web 2.0 in the era of COVID-19 disease.

[Mobile applications to improve drug adherence: Review and quality analysis]

OBJECTIVE

To review the mobile apps in the Spanish market to improve adherence to medications and evaluate their characteristics and quality to identify high-quality applications.

METHOD

A review was carried out following a stepwise procedure similar to a systematic review of the scientific literature. Apple Apps Store and Google Play Store mobile application digital distribution platforms. Applications aimed at supporting self-management of treatment, which generate reminders, in Spanish, updated in the last 2 years and free. We evaluate the applications according to a set of characteristics considered desirable and the quality with the Mobile App Rating Scale tool.

RESULTS

Out of 708 applications, 3 applications were selected. The Medisafe and Mytherapy applications had 89% and 78% of the desirable characteristics, respectively. Sergio Licea's application only had 56%. The highest global quality score was obtained by the MyTherapy application (3.79/5, IQR: 3-4), followed by Medisafe (3.72/5, (IQR: 3-4) and, finally, Sergio Licea (2.87/5, IQR: 2-4). The quality assessment coincides with the user assessment. There are many available applications, however, most did not meet the selection criteria.

CONCLUSIONS

A systematic stepwise process was able to identify the quality application to be tested in a future study that will provide evidence on the use of a multicomponent intervention to improve medication adherence.

Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials

COVID-19 pandemic challenges have accelerated the reliance on digital health fuelling the expanded incorporation of mobile apps into healthcare services, particularly for the management of long-term conditions such as chronic diseases (CDs). However, the impact of health apps on outcomes for CD remains unclear, potentially owing to both the poor adoption of formal development standards in the design process and the methodological quality of studies. A systematic search of randomised trials was performed on Medline, ScienceDirect, the Cochrane Library and Scopus to provide a comprehensive outlook and review the impact of health apps on CD. We identified 69 studies on diabetes (n = 29), cardiovascular diseases (n = 13), chronic respiratory diseases (n = 13), cancer (n = 10) or their combinations (n = 4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Apps differed significantly in content, with a median of eight behaviour change techniques adopted, most frequently pertaining to the ‘Feedback and monitoring’ (91%) and ‘Shaping knowledge’ (72%) categories. As for the study methodologies, all studies adopted a traditional randomised control trial (RCT) design, with relatively short follow-ups and limited sample sizes. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias. To support the adoption of apps for CD management, this review reinforces the need for more robust development and appropriate study characteristics to sustain evidence generation and elucidate whether study results reflect the true benefits of apps or a biased estimate due to unsuitable designs.

Introduction of digital therapeutics

BACKGROUND AND OBJECTIVES

Digital therapeutics are an emerging type of medical therapy and are defined as evidence-based therapeutic interventions for patients by means of qualified software programs to prevent, manage, or treat medical conditions. Today, digital therapeutics products are on the market or under development for a wide range of medical conditions such as diabetes, oncology treatment management, and neuropsychiatric disorders including anxiety disorder, depression, and substance use disorder. Digital therapeutics can be more flexible than other treatment methods to address patients' individual needs.

METHODS AND RESULTS

The advantages of digital therapeutics fall in line with market demand; thus, the digital therapeutics market is expanding globally, focusing on advanced medical markets. There are many digital therapeutics products such as Sleepio for insomnia, Daylight for anxiety, Livongo and Omada products for diabetes, pre-diabetes, hypertension, etc. None of these are cleared by the Food and Drug Administration (FDA), but all are commercially available through health insurance or employers. The EU, including Germany, and a number of Asian countries, including Korea, Japan, and China, are also introducing policies for the regulation of new fields and digital therapeutics.

CONCLUSIONS

The adoption of digital therapeutics is intricate and often involves various interests in numerous fields, decision-making processes, and individual or organizational value judgments. For digital therapeutics to be thoroughly introduced into real life, technical aspects must be supported, and an approach that considers users must be further investigated.

Exploring the human factors for mindfulness in mHealth service usage: An Elaboration Likelihood Model

MHealth service is widely accepted as a good path towards healthcare promotion. However, patients’ low-level usage restricted its effectiveness. This work draws upon the elaboration likelihood model and mindfulness theory to investigate the mindfulness mechanism in mHealth service usage, which highlights: First, both perceived information quality and mindfulness positively affect mHealth service usage. Also, perceived information quality is observed to affect the establishment of mindfulness positively. These findings stress that both perceived information quality and mindfulness are essential for mHealth service usage. Second, peer patient influence and physicians’ recommendations positively affect the establishment of mindfulness. These findings stress that human factors are essential for consumers’ establishment of mindfulness. Third, mindfulness mediates the relationship between human factors and mHealth service usage. This phenomenon indicates that when consumers adopt a mHealth service, both peer patient influence and physicians’ recommendations have a positive impact on mHealth service usage indirectly. Fourth, the effects of both peer patient influence and physicians’ recommendations on mindfulness depend on patients’ perceived eHealth literacy levels. This finding illustrates that while peer patient influence is especially crucial for improving mindfulness in a cohort with a high-level perceived eHealth literacy, physicians’ recommendations are especially crucial for improving mindfulness in a cohort with low-level perceived eHealth literacy.

The Challenge of Sustainable Access to Telemonitoring Tools for People with Diabetes in Europe: Lessons from COVID-19 and Beyond

Telemedicine in diabetes care has been evolving over several years, particularly since the advent of cloud-connected technologies for diabetes management, such as glucose monitoring devices, including continuous glucose monitoring (CGM) systems, that facilitate sharing of glucose data between people with diabetes and their healthcare professionals in near-real time. Extreme social distancing and shielding in place for vulnerable patients during the COVID-19 pandemic has created both the challenge and the opportunity to provide care at a distance on a large scale. Available evidence suggests that glucose control has in fact improved during this period for people with diabetes who are able to use CGM devices for remote glucose monitoring. The development of telemedicine as part of the standard of care in diabetes faces significant challenges in the European context, particularly in terms of providing consistent and effective care at a distance to large populations of patients while using robust systems that can be supported by large regional and national healthcare services. These challenges include a fragmented approach to healthcare technology assessment and reimbursement, lack of eHealth education and literacy, particularly amongst healthcare professionals, lack of data integration, as well as concerns about electronic health records, patient consent and privacy. Here we review the benefits of and challenges to wider application of telemedicine and telemonitoring in the post-pandemic future, with the aim to ensure that the value of these eHealth services is provided to patients, healthcare providers and health systems.

Continuous Glucose Monitoring Integration for Remote Diabetes Management: Virtual Diabetes Care with Case Studies

Use of telemedicine and remote monitoring technologies can significantly improve glycemic control in patients with type 1 diabetes and type 2 diabetes. Patients' ability to interact remotely with their health care providers via smartphones and other communication devices can increase their access to clinical care and online coaching and support programs. The establishment of metrics for clinical use of continuous glucose monitoring data and standardization of data reporting has enabled clinicians to maintain high-quality diabetes care through remote monitoring and telemedicine visits during the COVID-19 pandemic. This article discusses our experiences using remote monitoring and telemedicine visits during this time.

What's Wrong with This Picture? A Critical Review of Current Centers for Medicare & Medicaid Services Coverage Criteria for Continuous Glucose Monitoring

Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes and type 2 diabetes populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. This article discusses the limitations and inconsistencies of the CMS eligibility criteria relative to current scientific evidence and proposes workable solutions to address this issue and improve the safety and care of all individuals with diabetes.

Continuous Glucose Monitoring (CGM) Is a Tool, Not a Reward: Unjustified Insurance Coverage Criteria Limit Access to CGM

Recent studies have demonstrated the clinical utility of continuous glucose monitoring (CGM) use in type 2 diabetes (T2D) patients who are treated with intensive insulin management. Large retrospective database analyses of T2D patients treated with less-intensive therapies have also shown that CGM use was associated with significant reductions in hemoglobin A1c levels and health resource utilization, including diabetes-related hospitalizations and emergency room care. Despite the growing body of evidence supporting CGM use in the broader T2D population, current eligibility criteria required by public and many private insurers are denying millions of individuals with T2D access to this valuable technology. In this article, we discuss an evidence-based rationale for modifying current eligibility requirements for CGM coverage.

Impact of deprivation on glycaemic control in youth with type 1 diabetes in the southwestern region of France

OBJECTIVES

The objective of this multicenter cross-sectional study was to determine predictors of poor glycaemic control in children with type 1 diabetes mellitus (T1DM), particularly with respect to socioeconomic status (SES).

METHODS

Our study population consisted of 1154 children who attended T1DM follow-up consultation with a pediatric diabetes specialist. Clinical and demographic data were retrieved retrospectively from patients' records. Individual deprivation was defined by an EPICES (Evaluation of the Deprivation and Inequalities of Health in Healthcare Centers) score ≥ 30. Patients were assigned to quintiles of the European Deprivation Index (EDI) based on their area deprivation scores. We used multivariable linear regression models to detect potential associations between glycaemic control and indicators of low SES.

RESULTS

In total, 33% (n = 376) of patients had an EPICES score ≥ 30 and 23% (n = 268) were in the 5th EDI quintile. Multivariable linear regression analysis showed that poor glycaemic control was associated with both individual (β 0.38; 95%CI 0.26-0.5; p < 0.001) and area deprivation (β 0.26; 95%CI 0.08-0.43; p = 0.004). Demographic factors, body mass index (BMI) and insulin regimen were also independently associated with poor glycaemic control (p < 0.001). Interestingly, access to diabetes technologies was not related to SES or either glycaemic control.

CONCLUSION

Low SES is associated with a higher risk of poor glycaemic control, independently of insulin regimen. BMI, age at the time of consultation, duration of diabetes, and insulin regimen. Also have an impact on HbA1c. These parameters need to be considered when developing novel treatment strategies for children with T1DM to better target at-risk patients.

Comparative effectiveness of team-based care with a clinical decision support system versus team-based care alone on cardiovascular risk reduction among patients with diabetes: Rationale and design of the D4C trial

BACKGROUND

Diabetes has become a major public health challenge worldwide, especially in low- and middle-income countries (LMICs). Uncontrolled hyperglycemia, hypertension, and dyslipidemia major risk factors for all-cause mortality and cardiovascular disease (CVD) are common in patients with diabetes in China. We propose to compare the effectiveness of team-based care plus a clinical decision support system (CDSS) with team-based care alone on glycemic, blood pressure (BP), and lipid control, and clinical CVD reduction among patients with type-2 diabetes and at high risk for CVD.

METHODS

The Diabetes Complication Control in Community Clinics (D4C) study is a cluster-randomized trial conducted among 38 community health centers in Xiamen City, China. Nineteen clinics have been randomly assigned to team-based care plus CDSS and 19 to team-based care alone. Team-based care includes primary care providers, health coaches, and diabetes specialists working collaboratively with patients to achieve shared treatment goals for CVD risk factor reduction. The CDSS integrates guideline-based treatment algorithms for glycemic, BP, and lipid control, along with a patient's medical history and insurance policy, to recommend treatment and follow-up plans. In phase 1, the co-primary outcomes are mean reduction in glycated hemoglobin (HbA1c), systolic BP (SBP), and low-density lipoprotein (LDL)-cholesterol over 18 months, and the proportion of patients with controlled HbA1c, SBP, and LDL-cholesterol at 18 months' between the 2 comparison groups. In phase 2, the primary outcome is the difference in major CVD incidence (non-fatal stroke, non-fatal myocardial infarction, hospitalized heart failure, and CVD mortality) between the 2 comparison groups. Mean reduction in HbA1c, SBP, and LDL-cholesterol levels will be simultaneously modeled for a single overall treatment effect.

CONCLUSION

The D4C trial will generate evidence on whether a CDSS will further reduce the CVD burden among patients with diabetes beyond team-based care at community clinics. If proven effective, this implementation strategy could be scaled up within primary care settings in China and other LMICs to reduce CVD incidence and mortality among patients with diabetes.

Impact of a Remote Monitoring Programme Including Lifestyle Education Software in Type 2 Diabetes: Results of the Educ@dom Randomised Multicentre Study

INTRODUCTION

Telemonitoring in type 2 diabetes (T2D) is mainly based on glucose monitoring. A new type of connected device which routinely gathers data on weight, physical activity and food intake could improve patients' diabetes control. The main aim of this study was to assess the efficacy of an at-home interventional programme incorporating such devices and lifestyle education software on diabetes control, i.e., change in HbA1c, compared to standard care.

METHODS

This multicentre study randomly assigned 282 people with T2D to either a telemonitoring group (TMG) or a control group (CG) for a 1-year intervention period. While routine follow-up was maintained in the CG, TMG subjects were provided with interactive lifestyle educational software (with artificial intelligence algorithms) and connected objects (blood glucose meters, scales and actimeters) for use in their own homes and were remotely monitored by their diabetologists. Changes in HbA_1c were compared between groups using a mixed linear model.

RESULTS

The mean HbA_1c dropped from 7.8 ± 0.8% (62 mmol/mol) to 7.4 ± 1.0% (57 mmol/mol) in the TMG and from 7.8 ± 0.8% (62 mmol/mol) to 7.6 ± 1.0% (60 mmol/mol) in the CG, resulting in an intergroup difference of - 0.16 (p = 0.06) in favour of TMG, after adjustment for confounding factors. Within TMG, the decrease in HbA_1c was greater in frequent users: - 0.23% (p = 0.03) in the case of connections to telemonitoring synthesis above the median and - 0.21% (p = 0.05) in the case of connections to tele-education software above the median compared to the CG. Significant weight loss was observed in the TMG but only in women (p = 0.01).

FINDINGS

The EDUC@DOM telemonitoring and tele-education device did not highlight a significant decrease in HbA1c levels compared to routine management although a slight, albeit significant improvement in glycaemic control was observed in the frequent user subgroup as well as significant weight loss but only in women. A high level of satisfaction with the connected device was recorded amongst all participants.

TRIAL REGISTRATION

This trial was registered in the Clinical Trials Database on September 27, 2013, under no. NCT01955031 and bears ID-RCB number 2013-A00391-44.

On the efficacy of behavior change techniques in mHealth for self-management of diabetes: A meta-analysis

BACKGROUND

Diabetes prevalence has become a global crisis. Due to the substantial rise in smartphone use, a variety of mobile interventions have been developed to help improve the clinical outcomes of diabetes patients.

OBJECTIVES

This study seeks to examine specific behavior change theories and techniques used in the design of self-management mobile app-based interventions aimed at achieving glycemic control in type 1 and type 2 diabetes.

METHODS

A meta-analysis of randomized control trials published in PubMed/Medline and Web of Science between January 2010 and October 2020 was conducted using studies that included diabetes patients, reported on well-described mobile app-based interventions, compared mHealth to usual care, and evaluated glycated hemoglobin (HbA1c) at baseline and follow-up.

RESULTS

We reported on 21 studies with a total of 1,920 diabetes patients. Our findings show that mHealth apps led to statistically significant clinical outcomes as compared to standard care for glycemic control (-0.38, 95% CI = -0.50 to -0.25, p < 0.0001) indicating that such interventions result in a reduction in HbA1c. Interventions that used behavior theory for developing mHealth apps were not statistically different from those that did not (p = 0.18). However, increased use of behavior change techniques (BCTs) may result in slightly higher HbA1c reduction. Among all BCTs, the most effective ones appear to be "Action planning" and "Self-monitoring of outcome(s) of behavior.

CONCLUSIONS

The current meta-analysis provides evidence that mHealth is likely to be beneficial for diabetes patients when the right behavior change techniques are applied to realize the full advantage of the intervention. Further investigation of the role of theory in the design of mHealth app-based interventions is warranted.

Effects of remote care of patients with poorly controlled type 1 diabetes included in an experimental telemonitoring programme

AIM

To assess, in a real-life setting, the effectiveness of telemonitoring adults with type 1 diabetes (T1D) using continuous glucose monitoring in a telemedicine experiment.

METHODS

Experimentation in Telemedicine for the Improvement of Healthcare Pathways (ETAPES), an experimental telehealth programme for five chronic diseases, is supported by the French national healthcare system to promote telemedical care. Using data from a single university hospital centre, 72 adults were studied, including 42 subjects (58%) receiving insulin pump therapy and 30 (42%) receiving multiple daily injections, with a median age of 35.5 years [28.0; 45.0] and poorly controlled type 1 diabetes (T1D) with a mean ± standard error of mean (SEM) HbA1c value of 8.69 ± 0.13%. The primary study outcome was the difference in HbA1c values between baseline and the end of a 6-month follow-up. Other end points of interest were mean blood glucose, glucose management indicator (GMI) level and % time in range (3.9-10 mmol/L) or below or above range.

RESULTS

At month 6, mean HbA1c levels were significantly reduced by -0.5% (P < 0.001) as were also mean blood glucose levels (P = 0.015), with a significant increase of 6.75 ± 1.36% of time in range at month 3 and of 4.98 ± 1.4% at month 6. Such improvements did not depend on age, gender or type of insulin therapy, but were inversely correlated to initial HbA1c values on multivariate analysis (P < 0.001).

CONCLUSION

Although the use of telehealth monitoring offers efficacy and safety in the metabolic control of patients with T1D, it does not fulfil all of these patients' clinical needs. As such, this new healthcare pathway cannot replace, but is a useful complement to, face-to-face in-person clinical visits.

Diabetology 4.0: Scoping Review of Novel Insights and Possibilities Offered by Digitalization

Background

The increasing prevalence of diabetes mellitus and associated morbidity worldwide justifies the need to create new approaches and strategies for diabetes therapy. Therefore, the ongoing digitalization offers novel opportunities in this field.

Objective

The aim of this study is to provide an updated overview of available technologies, possibilities, and novel insights into diabetes therapy 4.0.

Methods

A scoping review was carried out, and a literature search was performed using electronic databases (MEDLINE [PubMed], Cochrane Library, Embase, CINAHL, and Web of Science). The results were categorized according to the type of technology presented.

Results

Different types of technology (eg, glucose monitoring systems, insulin pens, insulin pumps, closed-loop systems, mobile health apps, telemedicine, and electronic medical records) may help to improve diabetes treatment. These improvements primarily affect glycemic control. However, they may also help in increasing the autonomy and quality of life of people who are diagnosed with diabetes mellitus.

Conclusions

Diabetes technologies have developed rapidly over the last few years and offer novel insights into diabetes therapy and a chance to improve and individualize diabetes treatment. Challenges that need to be addressed in the following years relate to data security, interoperability, and the development of standards.

Safety and Feasibility of the PEPPER Adaptive Bolus Advisor and Safety System: A Randomized Control Study

Background: The Patient Empowerment through Predictive Personalized Decision Support (PEPPER) system provides personalized bolus advice for people with type 1 diabetes. The system incorporates an adaptive insulin recommender system (based on case-based reasoning, an artificial intelligence methodology), coupled with a safety system, which includes predictive glucose alerts and alarms, predictive low-glucose suspend, personalized carbohydrate recommendations, and dynamic bolus insulin constraint. We evaluated the safety and efficacy of the PEPPER system compared to a standard bolus calculator. Methods: This was an open-labeled multicenter randomized controlled crossover study. Following 4-week run-in, participants were randomized to PEPPER/Control or Control/PEPPER in a 1:1 ratio for 12 weeks. Participants then crossed over after a washout period. The primary end-point was percentage time in range (TIR, 3.9-10.0 mmol/L [70-180 mg/dL]). Secondary outcomes included glycemic variability, quality of life, and outcomes on the safety system and insulin recommender. Results: Fifty-four participants on multiple daily injections (MDI) or insulin pump completed the run-in period, making up the intention-to-treat analysis. Median (interquartile range) age was 41.5 (32.3-49.8) years, diabetes duration 21.0 (11.5-26.0) years, and HbA1c 61.0 (58.0-66.1) mmol/mol. No significant difference was observed for percentage TIR between the PEPPER and Control groups (62.5 [52.1-67.8] % vs. 58.4 [49.6-64.3] %, respectively, P = 0.27). For quality of life, participants reported higher perceived hypoglycemia with the PEPPER system despite no objective difference in time spent in hypoglycemia. Conclusions: The PEPPER system was safe, but did not change glycemic outcomes, compared to control. There is wide scope for integrating PEPPER into routine diabetes management for pump and MDI users. Further studies are required to confirm overall effectiveness. Clinical trial registration: ClinicalTrials.gov NCT03849755.

Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review

Background

According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited.

Objective

The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM.

Methods

A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA_1c).

Results

In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA_1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of –0.54% (95% CI –0.8 to –0.28) for T2DM and –0.63% (95% CI –0.93 to –0.32) for T1DM.

Conclusions

DM-specific mHealth apps improved the glycemic control by significantly reducing HbA_1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.

Smartphone distraction during nursing care: Systematic literature review

AIM

To investigate the impact of smartphone distraction on the quality and safety of care provided by the nursing population during work.

BACKGROUND

About 80% of nurses use the smartphone in the workplace both for personal purposes and as a useful support to improve the quality of care. Distraction from smartphones during care is a phenomenon that should be known and managed within each health service.

METHODS

A systematic review of the literature was conducted using the PRISMA methodology. The sources included in the review study were subjected to a qualitative assessment using the GRADE method.

RESULTS

Sixteen articles were included in the review. Studies included highlight the positive and negative consequences of using mobile devices during nursing practice. Findings identify the smartphone as a generator of stimuli capable of diverting the attention of the person from the priority activities and absorbing the cognitive resources useful for carrying out these activities. Some studies aimed to show the restriction policies and/or the strategies for reducing disruptions. This review highlights how the free and indiscriminate use of the smartphone can negatively affect patient safety and the nurse-patient relationship through the dehumanization and depersonalization of care.

CONCLUSIONS

Mobile technology can improve nurses' performance and the quality of care provided. However, the application of regulations and policies by healthcare facilities is desirable to avoid inappropriate use of these devices by nurses. The available data do not provide a precise estimate of the effect that distraction from smartphones has on the outcomes of nursing care.

The Digital/Virtual Diabetes Clinic: The Future Is Now-Recommendations from an International Panel on Diabetes Digital Technologies Introduction

The increasing prevalence of diabetes, combined with a growing global shortage of health care professionals (HCP), necessitates the need to develop new approaches to diabetes care delivery to expand access to care, lessen the burden on people with diabetes, improve efficiencies, and reduce the unsustainable financial liability on health systems and payers. Use of digital diabetes technologies and telehealth protocols within a digital/virtual diabetes clinic has the potential to address these challenges. However, several issues must be resolved to move forward. In February 2020, organizers of the Advanced Technologies & Treatments for Diabetes Annual Conference convened an international panel of HCP, researchers, patient advocates, and industry representatives to review the status of digital diabetes technologies, characterize deficits in current technologies, and identify issues for consideration. Since that meeting, the importance of using telehealth and digital diabetes technologies has been demonstrated amid the global coronavirus disease (COVID-19) pandemic. This article summarizes the panel's discussion of the opportunities, obstacles, and requisites for advancing the use of these technologies as a standard of care for the management of diabetes.

Use of eHealth by Patients With Rheumatoid Arthritis: Observational, Cross-sectional, Multicenter Study

Background

The use of eHealth tools (eg, the internet, mobile apps, and connected devices) in the management of chronic diseases and for rheumatoid arthritis is growing. eHealth may improve the overall quality of care provided to patients with chronic diseases.

Objective

The primary objective of this study was to describe eHealth use by patients with rheumatoid arthritis in France. The secondary objectives were to identify associations between patient demographics and disease characteristics and the use of eHealth tools, and assess their expectations of eHealth.

Methods

In this cross-sectional, multicenter study, patients with rheumatoid arthritis, according to the 2010 ACR/EULAR classification criteria, were recruited from 5 university hospitals (Bordeaux, Clermont-Ferrand, Limoges, Montpellier, and Toulouse). Patients completed an anonymous self-questionnaire, including demographic data, evaluating their eHealth use (ie, access, support, frequency of use, type of use, and reason for use). The rheumatologist in charge of each patient completed an independent medical questionnaire on disease characteristics, activity of rheumatoid arthritis, and treatments. Data were collected between December 2018 and July 2019.

Results

Questionnaires were completed by 575 participants, with a mean age of 62 (SD 13) years, 447 (77.7%) of whom were female. Overall, 82.2% (473/575) of the participants had access to eHealth through a computer (402/467, 86.1%), tablet (188/467, 40.2%), or smartphone (221/467, 47.3%). Of these, 36.4% (170/467) of the participants used the internet for health in general, and 28.7% (134/467) used it specifically for rheumatoid arthritis–related reasons. All these 134 patients used eHealth to learn about disease pathology, and 66.4% (89/134) of them used it as a tool to help monitor rheumatoid arthritis. Most patients (87/125, 69.6%) had a paper file, 19.2% (24/125) used a digital tool (spreadsheets, 10/125, 8%; mobile app, 9/125, 7.2%; or website, 5/125, 4%), and 24.8% (31/125) did not use any tools for monitoring. Few patients (16/125, 12.8%) used tools for treatment reminders. About 21.6% (27/125) of the patients using eHealth used a specific app for rheumatoid arthritis. Univariate analysis showed that age, education level, employment status, treatment, comorbidities, membership of a patient association, and patient education program were associated with eHealth use for rheumatoid arthritis. Multivariate analysis showed that membership of a patient association (odds ratio [OR] 5.8, 95% CI 3.0-11.2), use of biologic disease-modifying antirheumatic drugs (OR 0.6, 95% CI 0.4-1.0), and comorbidities (OR 0.7, 95% CI 0.6-0.8) remained associated with eHealth use for rheumatoid arthritis. Recommendation by a doctor (225/330, 68.2%), ease of use (105/330, 31.8%), and data security (69/330, 20.9%) were factors favoring the use of eHealth.

Conclusions

To date, few patients have used eHealth for disease management. The use of a reliable and validated eHealth tool for rheumatoid arthritis could therefore be promoted by rheumatologists and could optimize therapeutic adherence.

Feasibility and Efficiency of a Novel Bolus Calculator (IF-DIABETE) for Patients With Type 1 Diabetes: A Nonrandomized Single-Arm Pilot Study

Background The IF-DIABETE system is an insulin bolus dose support, considered as the first bolus calculator dedicated to people with type 1 diabetes, designed in the Arabic language, and adapted to the large Arabic food culture. Our aims were to assess the proof of concept and efficiency of the IF-DIABETE system in improving clinical and metabolic outcomes in individuals with type 1 diabetes. Methods This is a prospective nonrandomized single-arm pilot study. Our patients used the IF-DIABETE smartphone application as a novel bolus calculator. Over six months period of the study, the primary outcome considered was hemoglobin glycated (HbA1c), and we identified hypoglycemic events, body mass index (BMI), and the frequency of blood glucose measurements as secondary outcomes. Results Twenty-one patients with type 1 diabetes were enrolled. The average age was 21 ± 3 years. Over a six months' period of the study, the mean HbA1c level decreased from 8.3 ± 0.8% to 7.0 ± 0.5 % with a reduction in mild hypoglycemic events' frequency from 5 ± 3 to 1 ± 0.7 episodes/3 months. We did not observe any change in BMI and the frequency of the blood glucose testing improved from 2 ± 0.5 to 5 ± 1 tests per day. Conclusion The IF-DIABETE system was safe and effective to support individuals who have type 1 diabetes to improve their metabolic control. At six months, patients were able to improve their glycemic control without increasing the risk of hypoglycemic events.

Evaluation of Patient Willingness to Adopt Remote Digital Monitoring for Diabetes Management

Importance

Patients will decide whether to adopt remote digital monitoring (RDM) for diabetes by weighing its health benefits against the inconvenience it may cause.

Objective

To identify the minimum effectiveness patients report they require to adopt 36 different RDM scenarios.

Design, Setting, and Participants

This survey study was conducted among adults with type 1 or type 2 diabetes living in 30 countries from February to July 2019.

Exposures

Survey participants assessed 3 randomly selected scenarios from a total of 36. Scenarios described different combinations of digital monitoring tools (glucose, physical activity, food monitoring), duration and feedback loops (feedback in consultation vs real-time telefeedback by a health care professional or by artificial intelligence), and data handling modalities (by a public vs private company), reflecting different degrees of RDM intrusiveness in patients' personal lives.

Main Outcomes and Measures

Participants assessed the minimum effectiveness for 2 diabetes-related outcomes (reducing hypoglycemic episodes and preventing ophthalmologic complications) for which they would adopt each RDM (from much less effective to much more effective than their current monitoring).

Results

Of 1577 individuals who consented to participate, 1010 (64%; 572 [57%] women, median [interquartile range] age, 51 [37-63] years, 524 [52%] with type 1 diabetes) assessed at least 1 vignette. Overall, 2860 vignette assessments were collected. In 1025 vignette assessments (36%), participants would adopt RDM only if it was much more effective at reducing hypoglycemic episodes compared with their current monitoring; in 1835 assessments (65%), participants would adopt RDM if was just as or somewhat more effective. The main factors associated with required effectiveness were food monitoring (β = 0.32; SE, 0.12; P = .009), real-time telefeedback by a health care professional (β = 0.49; SE, 0.15; P = .001), and perceived intrusiveness (β = 0.36; SE, 0.06; P < .001). Minimum required effectiveness varied among participants; 34 of 36 RDM scenarios (94%) were simultaneously required to be just as or less effective by at least 25% of participants and much more effective by at least 25% of participants. Results were similar for participant assessments of scenarios regarding the prevention of ophthalmologic complications.

Conclusions and Relevance

The findings of this study suggest that patients require greater health benefits to adopt more intrusive RDM modalities, food monitoring, and real-time feedback by a health care professional. Patient monitoring devices should be designed to be minimally intrusive. The variability in patients' requirements points to a need for shared decision-making.

Effects of mobile health interventions on improving glycemic stability and quality of life in patients with type 1 diabetes: A meta-analysis

This meta-analysis aimed to examine the effects of mobile-health-based (mHealth) interventions on improving glycemic stability and quality of life (QOL) in patients with type 1 diabetes (T1D). Various databases, including PubMed, Embase, CINAHL, Cochrane Library, ProQuest, Chinese Electronic Periodical Services, and China Knowledge Resource Integrated, were used to search for relevant articles. A fixed-effects model or random-effects model was used to examine the overall effect. Various methods, including Egger's test, Begg's test, and trim-and-fill, were adopted to examine publication bias. In total, 26 studies were recruited. Results of the random-effects model showed that the use of mHealth-based interventions significantly decreased glycated hemoglobin (HbA1c) (mean difference = -0.37, 95% confidence interval (CI) = -0.53 to -0.22, p < .001), and improved life satisfaction (Hedges' g = 0.30, 95% CI = 0.10 to 0.50, p = .003), worry of diabetes (Hedges' g = -0.25, 95% CI = -0.41 to 0.08, p = .004), and mental health (Hedges' g = 0.36, 95% CI = 0.08 to 0.64, p = .012). Both adults and youths with T1D can benefit from mHealth-based interventions to improve HbA1c (Hedges' g = -0.44, p = .002 vs. -0.30, p = .003). The effect of mHealth-based interventions on improving QOL in both adults and youths could not be examined due to only one study published in adults with T1D. Moreover, those studies that included the function of feedback from professionals showed a significant effect of decreasing HbA1c compared to those without that function (Hedges' g = -0.48 vs. -0.16, p = .019). Mobile devices are convenient, instantaneous, and easy to use to communicate. Applying mHealth-based interventions with the function of feedback from professionals can be considered an alternative healthcare service to achieve optimal glycemic stability in adults and youths with T1D.

Community health programs delivered through information and communications technology in high-income countries: a scoping review (Preprint)

Background

The COVID-19 pandemic has required widespread and rapid adoption of information and communications technology (ICT) platforms by health professionals. Transitioning health programs from face-to-face to remote delivery using ICT platforms has introduced new challenges.

Objective

The objective of this review is to scope for ICT-delivered health programs implemented within the community health setting in high-income countries and rapidly disseminate findings to health professionals.

Methods

The Joanna Briggs Institute’s scoping review methodology guided the review of the literature.

Results

The search retrieved 7110 unique citations. Each title and abstract was screened by at least two reviewers, resulting in 399 citations for full-text review. Of these 399 citations, 72 (18%) were included. An additional 27 citations were identified through reviewing the reference lists of the included studies, resulting in 99 citations. Citations examined 83 ICT-delivered programs from 19 high-income countries. Variations in program design, ICT platforms, research design, and outcomes were evident.

Conclusions

Included programs and research were heterogeneous, addressing prevalent chronic diseases. Evidence was retrieved for the effectiveness of nurse and allied health ICT-delivered programs. Findings indicated that outcomes for participants receiving ICT-delivered programs, when compared with participants receiving in-person programs, were either equivalent or better. Gaps included a paucity of co-designed programs, qualitative research around group programs, programs for patients and carers, and evaluation of cost-effectiveness. During COVID-19 and beyond, health professionals in the community health setting are encouraged to build on existing knowledge and address evidence gaps by developing and evaluating innovative ICT-delivered programs in collaboration with consumers and carers.

DIABEO System Combining a Mobile App Software With and Without Telemonitoring Versus Standard Care: A Randomized Controlled Trial in Diabetes Patients Poorly Controlled with a Basal-Bolus Insulin Regimen

Background: The DIABEO^® system (DS) is a telemedicine solution that combines a mobile app for patients with a web portal for health care providers. DS allows real-time monitoring of basal-bolus insulin therapy as well as therapeutic decision-making, integrating both basal and bolus dose calculation. Real-life studies have shown a very low rate of use of mobile health applications by patients. Therefore, we conducted a large randomized controlled trial study to investigate the efficacy of DS in conditions close to real life (TELESAGE study). Methods: TELESAGE was a multicenter, randomized, open study with three parallel arms: arm 1 (standard care), arm 2 (DIABEO alone), and arm 3 (DIABEO+telemonitoring by trained nurses). The primary outcome assessed the reduction in HbA_1c levels after a 12-month follow-up. Results: Six hundred sixty-five patients were included in the study. Participants who used DIABEO once or more times a day (DIABEO users) showed a significant and meaningful reduction of HbA_1c versus standard care after a 12-month follow-up: mean difference -0.41% for arm 2-arm 1 (P = 0.001) and -0.51% for arm 3-arm 1 (P ≤ 0.001). DIABEO users included 25.1% of participants in arm 2 and 37.6% in arm 3. In the intention-to-treat population, HbA_1c changes and incidence of hypoglycemia were comparable between arms. Conclusions: A clinical and statistically significant reduction in HbA_1c levels was found in those patients who used DIABEO at least once a day.

Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial

Background

The role of mobile health care (mHealth) in glycemic control has been investigated, but its impact on self-management skills and its psychological aspects have not been studied.

Objective

We evaluated the efficacy of mHealth-based diabetes self-management education and the effect of voluntary participation on its effects.

Methods

This study was a randomized controlled open-label trial conducted for 6 months at Kangbuk Samsung Hospital. Participants in the control group (n=31) maintained their previous diabetes management strategies. Participants in the intervention group (n=41) additionally received mHealth-based diabetes self-management education through a mobile app and regular individualized feedback from health care professionals. The primary outcome was change in glycated hemoglobin (HbA_1c) level over 6 months between the 2 groups (intervention versus control) and within each group (at 6 months versus baseline). The secondary outcomes were changes in body mass index, blood pressure, lipid profile, and questionnaire scores (the Korean version of the Summary of Diabetes Self-Care Activities Questionnaire, an Audit of Diabetes Dependent Quality of Life, the Appraisal of Diabetes Scale, and Problem Areas in Diabetes) over 6 months between groups and within each group.

Results

A total of 66 participants completed this study. HbA_1c (P=.04), total cholesterol level (P=.04), and Problem Areas in Diabetes scores (P=.02) significantly decreased; total diet (P=.03) and self-monitoring of blood glucose level scores (P=.01), based on the Summary of Diabetes Self-Care Activities Questionnaire, markedly increased within the intervention group. These significant changes were observed in self-motivated participants who were recruited voluntarily via advertisements.

Conclusions

mHealth-based diabetes self-management education was effective at improving glycemic control and diabetes self-management skills and lowering diabetes-related distress in voluntary participants.

Trial Registration

ClinicalTrials.gov NCT03468283; http://clinicaltrials.gov/ct2/show/NCT03468283

An android smartphone-based randomized intervention improves the quality of life in patients with type 2 diabetes in Mysore, Karnataka, India

BACKGROUND AND AIMS

Associated with severe complications and morbidity, Diabetes Mellitus is a significant public health burden. The need for regular monitoring and adherence to treatment and lifestyle changes have a high impact on the quality of life of the patients. This study attempts to assess the effect of smartphone-based lifestyle modification intervention in the quality of life of patients with type 2 Diabetes through a randomized filed trial.

METHODS

A randomized field trial was performed among the patients attending the outpatient department of a tertiary care hospital in Mysuru city. A mobile application named DIAGURU, mainly focusing on the lifestyle modification and medication management was used for a period of 6 months from April 2019 to September 2019 by 150 patients in the intervention group while another 150 participants served as controls. The quality of life was assessed using the WHO QOL BREF questionnaire at the beginning of the study and after six months.

RESULTS

The change in the quality of life in a positive direction was significantly higher in the intervention group compared to the non-intervention group after six months. The differences in the change in scores of quality of life of participants recruited in intervention and non-intervention groups were statistically significant in all the four domains after the intervention with a p value < 0.001.

CONCLUSION

The evidence generated in this study suggest that such technological approaches can be used as a public health measure to improve the quality of life of patients with type 2 Diabetes Mellitus.