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

Effectiveness of digital health interventions for telemedicine/telehealth for managing blood pressure in adults: a systematic review and meta-analysis

This systematic review and meta-analysis included randomized controlled trials or observational studies that compare digital health interventions (DHIs) for telemedicine/telehealth versus usual care for managing blood pressure (BP) in adults. We searched PubMed, Cochrane CENTRAL, and IchuShi-Web, and used a random-effects meta-analysis of the weighted mean difference (MD) between the comparison groups to pool data from the included studies. The outcome included the pooled MD of office BP from baseline to each follow-up period. This meta-analysis considered 117 studies with 68677 participants as eligible. The 3-month intervention period reduced office systolic BP (SBP) compared with usual care in 38 studies (MD: -3.21 mmHg [95% confidence interval: -4.51 to -1.90]), with evidence of heterogeneity. Office SBP across intervention periods demonstrated comparable effects (3-, 6- [54 studies], 12- [43 studies], and >12-month periods [9 studies]). The benefits for office diastolic BP were similar to those for office SBP. Additionally, the interventions significantly reduced the office SBP compared with the control, regardless of the mode of intervention delivery (smartphone apps [38 studies], text messages [35 studies], and websites [34 studies]) or type of facility (medical [74 studies] vs. non-medical [33 studies]). The interventions were more effective in 41 hypertension cohorts compared with 66 non-hypertension cohorts (-4.81 mmHg [-6.33, -3.29] vs. -2.17 mmHg [-3.15, -1.19], P = 0.006 for heterogeneity). In conclusion, DHIs for telemedicine/telehealth improved BP management compared with usual care. The effectiveness with heterogeneity should be considered, as prudent for implementing evidence-based medicine. This meta-analysis considered 117 studies with 68677 participants eligible. The DHIs for telemedicine/telehealth reduced office BP compared with usual care, regardless of intervention duration, intervention delivery mode, facility type, and cohort type. Additionally, the DHIs reduced the risk of uncontrolled BP compared with usual care, regardless of intervention duration, intervention delivery mode, and facility type. BP blood pressure, DHI digital health intervention, MD mean difference, RR risk ratio, SBP systolic blood pressure.

Effect of m-Health-Based Interventions on Blood Pressure: An Updated Systematic Review with Meta-Analysis

Background: In recent years, the integration of mobile health (m-Health) interventions has garnered increasing attention as a potential means to improve blood pressure (BP) management in adults. This updated systematic review with meta-analysis aimed to identify the effect of m-Health-based interventions on BP in adults and to evaluate the effect of m-Health on BP according to the characteristics of subjects, interventions, and countries. Methods: The search was carried out in PubMed, Embase, ResearchGate, and Cochrane databases in January 2022. Study selection and data extraction were performed by two independent reviewers. For analysis, random effects models were used with a confidence interval (CI) of 95% and p < 0.05. Results: Fifty studies were included in this review and in the meta-analysis. Interventions with m-Health reduced systolic BP in 3.5 mmHg (95% CI -4.3; -2.7; p < 0.001; I2 = 85.8%) and diastolic BP in 1.8 mmHg (95% CI -2.3; -1.4; p < 0.001; I2 = 78.9%) compared to usual care. The effects of m-Health interventions on BP were more evident in men and in older adults, in interventions lasting 6-8 weeks, with medication reminders, with the possibility of insertion of BP values (p < 0.05). Conclusion: The results of this study support the effectiveness of m-Health in reducing BP when compared to standard care. However, these effects are dependent on the characteristics of the subjects and interventions. Given the substantial heterogeneity among the results of this systematic review with meta-analysis, its interpretation should be cautious. Future research on this topic is warranted.

The Key Digital Tool Features of Complex Telehealth Interventions Used for Type 2 Diabetes Self-Management and Monitoring With Health Professional Involvement: Scoping Review

BACKGROUND

Therapeutic education and patient self-management are crucial in diabetes prevention and treatment. Improving diabetes self-management requires multidisciplinary team intervention, nutrition education that facilitates self-management, informed decision-making, and the organization and delivery of appropriate health care services. The emergence of telehealth services has provided the public with various tools for educating themselves and for evaluating, monitoring, and improving their health and nutrition-related behaviors. Combining health technologies with clinical expertise, social support, and health professional involvement could help persons living with diabetes improve their disease self-management skills and prevent its long-term consequences.

OBJECTIVE

This scoping review's primary objective was to identify the key digital tool features of complex telehealth interventions used for type 2 diabetes or prediabetes self-management and monitoring with health professional involvement that help improve health outcomes. A secondary objective was to identify how these key features are developed and combined.

METHODS

A 5-step scoping review methodology was used to map relevant literature published between January 1, 2010 and March 31, 2022. Electronic searches were performed in the MEDLINE, CINAHL, and Embase databases. The searches were limited to scientific publications in English and French that either described the conceptual development of a complex telehealth intervention that combined self-management and monitoring with health professional involvement or evaluated its effects on the therapeutic management of patients with type 2 diabetes or prediabetes. Three reviewers independently identified the articles and extracted the data.

RESULTS

The results of 42 studies on complex telehealth interventions combining diabetes self-management and monitoring with the involvement of at least 1 health professional were synthesized. The health professionals participating in these studies were physicians, dietitians, nurses, and psychologists. The digital tools involved were smartphone apps or web-based interfaces that could be used with medical devices. We classified the features of these technologies into eight categories, depending on the intervention objective: (1) monitoring of glycemia levels, (2) physical activity monitoring, (3) medication monitoring, (4) diet monitoring, (5) therapeutic education, (6) health professional support, (7) other health data monitoring, and (8) health care management. The patient-logged data revealed behavior patterns that should be modified to improve health outcomes. These technologies, used with health professional involvement, patient self-management, and therapeutic education, translate into better control of glycemia levels and the adoption of healthier lifestyles. Likewise, they seem to improve monitoring by health professionals and foster multidisciplinary collaboration through data sharing and the development of more concise automatically generated reports.

CONCLUSIONS

This scoping review synthesizes multiple studies that describe the development and evaluation of complex telehealth interventions used in combination with health professional support. It suggests that combining different digital tools that incorporate diabetes self-management and monitoring features with a health professional's advice and interaction results in more effective interventions and outcomes.

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.

Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a rising global health concern that requires long-term treatment and close monitoring. Telemonitoring has been shown to be a promising tool to facilitate patient-physician interaction and improve glycaemic control.

METHOD

Randomised controlled trials (RCT) of telemonitoring in T2DM published between 1990 and 2021 were searched through multiple electronic databases. The primary outcome variables included HbA1c and fasting blood glucose (FBG), and BMI was a secondary outcome variable.

RESULTS

Thirty RCT with a total of 4,678 participants were included in this study. Twenty-six studies reported on HbA1c, which was shown to be significantly lower in participants on telemonitoring when compared to conventional care. Ten studies investigated FBG which collectively showed no statistically significant difference. Subgroup analysis demonstrated the effect of telemonitoring on glycaemic control is influenced by a range of factors concerning system practicality, user engagement, patient characteristics and disease education.

CONCLUSION

Telemonitoring exhibited a great potential to improve T2DM management. Several technical features and patient factors may influence the effectiveness of telemonitoring. Further studies are needed to verify the findings and address limitations before its implementation into routine practice.

Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Digital health interventions have shown promising results for the management of type 2 diabetes, but a comparison of the effectiveness and implementation of the different modes is not currently available. Therefore, this study aimed to compare the effectiveness of SMS, smartphone application, and website-based interventions on improving glycaemia in adults with type 2 diabetes and report on their reach, uptake, and feasibility.

METHODS

In this systematic review and meta-analysis, we searched CINAHL, Cochrane Central, Embase, MEDLINE, and PsycInfo on May 25, 2022, for randomised controlled trials (RCTs) that examined the effectiveness of digital health interventions in reducing glycated haemoglobin A1c (HbA1c) in adults with type 2 diabetes, published in English from Jan 1, 2009. Screening was carried out using Covidence, and data were extracted following Cochrane's guidelines. The primary endpoint assessed was the change in the mean (and 95% CI) plasma concentration of HbA1c at 3 months or more. Cochrane risk of bias 2 was used to assess risk of bias. Data on reach, uptake, and feasibility were summarised narratively and data on HbA1c reduction were synthesised in a meta-analysis. Grading of Recommendations, Assessment, Development, and Evaluation criteria was used to evaluate the level of evidence. The study was registered with PROSPERO, CRD42021247845.

FINDINGS

Of the 3236 records identified, 56 RCTs from 24 regions (n=11 486 participants), were included in the narrative synthesis, and 26 studies (n=4546 participants) in the meta-analysis. 20 studies used SMS as the primary mode of delivery of the digital health intervention, 25 used smartphone applications, and 11 implemented interventions via websites. Smartphone application interventions reported higher reach compared with SMS and website-based interventions, but website-based interventions reported higher uptake compared with SMS and smartphone application interventions. Effective interventions, in general, included people with greater severity of their condition at baseline (ie, higher HbA1c) and administration of a higher dose intensity of the intervention, such as more frequent use of smartphone applications. Overall, digital health intervention group participants had a -0·30 (95% CI -0·42 to -0·19) percentage point greater reduction in HbA1c, compared with control group participants. The difference in HbA1c reduction between groups was statistically significant when interventions were delivered through smartphone applications (-0·42% [-0·63 to -0·20]) and via SMS (-0·37% [-0·57 to -0·17]), but not when delivered via websites (-0·09% [-0·64 to 0·46]). Due to the considerable heterogeneity between included studies, the level of evidence was moderate overall.

INTERPRETATION

Smartphone application and SMS interventions, but not website-based interventions, were associated with better glycaemic control. However, the studies' heterogeneity should be recognised. Considering that both smartphone application and SMS interventions are effective for diabetes management, clinicians should consider factors such as reach, uptake, patient preference, and context of the intervention when deciding on the mode of delivery of the intervention. Nine in ten people worldwide own a feature phone and can receive SMS and four in five people have access to a smartphone, with numerous smartphone applications being available for diabetes management. Clinicians should familiarise themselves with this modality of programme delivery and encourage people with type 2 diabetes to use evidence-based applications for improving their self-management of diabetes. Future research needs to describe in detail the mediators and moderators of the effectiveness and implementation of SMS and smartphone application interventions, such as the optimal dose, frequency, timing, user interface, and communication mode to both further improve their effectiveness and to increase their reach, uptake, and feasibility.

FUNDING

EU's Horizon 2020 Research and Innovation Programme.

Brief Digital Solutions in Behavior Change Interventions for Type 2 Diabetes Mellitus: A Literature Review

INTRODUCTION

With the advent of the COVID-19 pandemic, health systems increasingly look to digital health solutions to provide support for self-management to people with type 2 diabetes (T2D). This review aimed to assess brief digital behavior change solutions (i.e., solutions that require limited engagement or contact) for T2D, including use of behavior change techniques (BCTs) and their impact on self-care and glycemic control.

METHODS

A review was conducted by searching Embase and gray literature using a predefined search strategy to identify randomized controlled trials (RCT) published between January 1, 2015, and March 21, 2021. BCTs were coded using an internationally established BCT taxonomy v1 (BCTTv1).

RESULTS

Out of 1426 articles identified, 10 RCTs were included in qualitative synthesis. Of these, six reported significant improvements in primary outcome(s), including improved patient engagement, glycemic control, self-efficacy, and physical activity. Interventions as short as 12 min were found to be effective, and users' ability to control their preferences was noted as conducive to engagement. Almost three quarters of BCTs targeted by interventions were under the hierarchical clusters of "Feedback and monitoring," "Goals and planning," and "Shaping knowledge." Interventions that targeted fewer BCTs were at least as effective as interventions that were more comprehensive in their goals.

DISCUSSION

Digital behavior change solutions can successfully improve T2D self-care support and outcomes in a variety of populations including patients with low incomes, limited educational attainment, or living in rural areas. Easy-to-use interventions tailored to patient needs may be as effective as lengthy, complex, and more generalized interventions.

CONCLUSIONS

Brief digital solutions can improve clinical and behavioral outcomes while reducing patient burden, fitting more easily in patients' lives and potentially improving usability. As T2D patients increasingly expect access to self-care assistance between face-to-face encounters, digital support tools will play a greater role in effective diabetes management programs.

The Rapid Implementation of an Innovative Virtual Diabetes Boot Camp Program: Case Study

Background

COVID-19 disrupted health care, causing a decline in the health of patients with chronic diseases and a need to reimagine diabetes care. With the advances in telehealth programs, there is a need to effectively implement programs that meet the needs of patients quickly.

Objective

The aim of this paper was to create a virtual boot camp program for patients with diabetes, in 3 months, from project conception to the enrollment of our first patients. Our goal is to provide practical strategies for rapidly launching an effective virtual program to improve diabetes care.

Methods

A multidisciplinary team of physicians, dieticians, and educators, with support from the telehealth team, created a virtual program for patients with diabetes. The program combined online diabetes data tracking with weekly telehealth visits over a 12-week period.

Results

Over 100 patients have been enrolled in the virtual diabetes boot camp. Preliminary data show an improvement of diabetes in 75% (n=75) of the patients who completed the program. Four principles were identified and developed to reflect the quick design and launch.

Conclusions

The rapid launch of a virtual diabetes program is feasible. A coordinated, team-based, systematic approach will facilitate implementation and sustained adoption across a large multispecialty ambulatory health care organization.

The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

BACKGROUND

Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes. However, such reviews often have a narrow focus, which calls for a more comprehensive systematic review within the field. Hence, the objective of the present systematic review, meta-analysis, and meta-regression is to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with type 2 diabetes (T2D).

METHODS

This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We considered telemedicine randomized controlled trials (RCT) including adults (≥18 years) diagnosed with T2D. Change in glycated hemoglobin (HbA1c, %) was the primary outcome. PubMed, EMBASE, and the Cochrane Library Central Register of Controlled Trials (CENTRAL) were searched on October 14, 2020. An overall treatment effect was estimated using a meta-analysis performed on the pool of included studies based on the mean difference (MD). The revised Cochrane risk-of-bias tool was applied and the certainty of evidence was graded using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

RESULTS

The final sample of papers included a total of 246, of which 168 had sufficient information to calculate the effect of HbA1c%. The results favored telemedicine, with an MD of -0.415% (95% confidence interval [CI] = -0.482% to -0.348%). The heterogeneity was great (I² = 93.05%). A monitoring component gave rise to the higher effects of telemedicine.

CONCLUSIONS

In conclusion, telemedicine may serve as a valuable supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Trial Registration

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

The effect of active occupational stress management on psychosocial and physiological wellbeing: a pilot study

Background

The aim of the study was to address the working population with an occupational stress prevention program using mHealth solution and encourage them for healthy lifestyle choices.

Methods

Seventeen participants were randomized from the corporate setting. A 24alife app with a good compliance program was selected. Test battery has been designed to test the physical readiness, psychological evaluation and biological blood markers for stress. Participants were followed up after 30, 60 and 90 days, respectively, within the intervention period. Weight of participants was tracked three times per month. Univariate analysis compared the continuous variables by One-Way Repeated-Measures ANOVA test when the data were normally distributed, or Wilcoxon rank sum test for abnormal distribution of variables.

Results

Participants used the app with a compliance rate of 94.1%. The psychological evaluation revealed higher motivation for work, lower burnout scores and participants gave subjective responses of better general wellbeing. Some of the participants lost up to four kg of body mass. Physical readiness has also improved.

Conclusions

Results of mHealth projects on corporate could include primary health care institutions and health ministry to extend the existing system to patients’ pockets where they can monitor their disease and increase the ability of self-care.