Telemonitoring of Type 2 Diabetes Mellitus in Italy

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Barriers and Supports in eHealth Implementation among People with Chronic Cardiovascular Ailments: Integrative Review

eHealth interventions use information technology to provide attention to patients with chronic cardiovascular conditions, thereby supporting their self-management abilities.

OBJECTIVE

Identify barriers and aids to the implementation of eHealth interventions in people with chronic cardiovascular conditions from the perspectives of users, health professionals and institutions.

METHOD

An integrative database review of WoS, Scopus, PubMed and Scielo of publications between 2016 and 2020 reporting eHealth interventions in people with chronic cardiovascular diseases. Keywords used were eHealth and chronic disease. Following inclusion and exclusion criteria application, 14 articles were identified.

RESULTS

Barriers and aids were identified from the viewpoints of users, health professionals and health institutions. Some notable barriers include users' age and low technological literacy, perceived depersonalization in attention, limitations in technology access and usability, and associated costs. Aids included digital education and support from significant others.

CONCLUSIONS

eHealth interventions are an alternative with wide potentiality for chronic disease management; however, their implementation must be actively managed.

The Willingness to Pay for Telemedicine Among Patients With Chronic Diseases: Systematic Review

Background

Telemedicine is increasingly being leveraged, as the need for remote access to health care has been driven by the rising chronic disease incidence and the COVID-19 pandemic. It is also important to understand patients’ willingness to pay (WTP) for telemedicine and the factors contributing toward it, as this knowledge may inform health policy planning processes, such as resource allocation or the development of a pricing strategy for telemedicine services. Currently, most of the published literature is focused on cost-effectiveness analysis findings, which guide health care financing from the health system’s perspective. However, there is limited exploration of the WTP from a patient’s perspective, despite it being pertinent to the sustainability of telemedicine interventions.

Objective

To address this gap in research, this study aims to conduct a systematic review to describe the WTP for telemedicine interventions and to identify the factors influencing WTP among patients with chronic diseases in high-income settings.

Methods

We systematically searched 4 databases (PubMed, PsycINFO, Embase, and EconLit). A total of 2 authors were involved in the appraisal. Studies were included if they reported the WTP amounts or identified the factors associated with patients’ WTP, involved patients aged ≥18 years who were diagnosed with chronic diseases, and were from high-income settings.

Results

A total of 11 studies from 7 countries met this study’s inclusion criteria. The proportion of people willing to pay for telemedicine ranged from 19% to 70% across the studies, whereas the values for WTP amounts ranged from US $0.89 to US $821.25. We found a statistically significant correlation of age and distance to a preferred health facility with the WTP for telemedicine. Higher age was associated with a lower WTP, whereas longer travel distance was associated with a higher WTP.

Conclusions

On the basis of our findings, the following are recommendations that may enhance the WTP: exposure to the telemedicine intervention before assessing the WTP, the lowering of telemedicine costs, and the provision of patient education to raise awareness on telemedicine’s benefits and address patients’ concerns. In addition, we recommend that future research be directed at standardizing the reporting of WTP studies with the adoption of a common metric for WTP amounts, which may facilitate the generalization of findings and effect estimates.

A Meta-Analysis of the Effectiveness of Telemedicine in Glycemic Management among Patients with Type 2 Diabetes in Primary Care

Introduction: Telemedicine interventions are gradually being used in primary health care to help patients with type 2 diabetes receive ongoing medical guidance. The purpose of this study was to analyze the effectiveness of using telemedicine in primary health care for the management of patients with type 2 diabetes. Methods: A systematic search was conducted from database inception to August 2021 in nine databases, including PubMed, Web of Science, Cochrane Library, EMBASE, EBSCO, CNKI, Wanfang Data, VIP, and CBM. Data extraction and quality assessment were performed for studies that met the inclusion criteria. The meta-analysis was performed using Review Manager 5.4 (Cochrane) and Stata v.16.0SE (College Station, TX, USA). Results: A total of 32 articles were included in this study. Analysis showed a reduction in glycated hemoglobin, fasting glucose, and postprandial glucose after the telemedicine intervention. Systolic blood pressure and self-efficacy improved significantly, but there was no significant improvement in weight, lipid metabolism, or diabetes awareness. Subgroup analysis based on the duration of intervention showed significant improvement in glycated hemoglobin at 6 months of intervention. Conclusions: Telemedicine interventions may help patients with type 2 diabetes to effectively control blood glucose and improve self-management in primary health care. There is only moderate benefit, and the benefit may not be sustained beyond 6 months. However, the evidence for the improvement in lipid metabolism is insufficient and further studies are needed.

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.

Impact of Telehealth Care among Adults Living with Type 2 Diabetes in Primary Care: A Systematic Review and Meta-Analysis of Randomised Controlled Trials

Primary health care physicians are increasingly offering telehealth services to patients not only for its cost and time saving advantages but for the additional benefits telehealth can provide for patients with type 2 diabetes (T2D) such as improved self-management behaviours. To support the development of telehealth based T2D clinical care models in primary health care settings, a narrative synthesis and meta-analysis of randomised controlled trial studies was completed for 29 studies that evaluated the effect of one or more types of telehealth interventions on HbA1c levels compared to usual care alone. Results from the random effects meta-analysis demonstrated that telehealth interventions had a stronger influence on HbA1c compared to usual care with a mean difference in HbA1c \% -0.18 (CI -0.35, -0.01), p = 0.04. Results from the subgroup meta-analysis demonstrated that telehealth interventions, when grouped by type of telemonitoring (mHealth and telephone communication), all have a stronger effect on lowering HbA1c levels; however, none of these findings were significant. Key findings from this review demonstrate that telehealth interventions that address T2D self-management behaviours and have higher levels of health care provider engagement, have greater effects on lowering HbA1c levels compared to usual care alone.

Can Remote Patient Monitoring Be the New Standard in Primary Care of Chronic Diseases, Post-COVID-19?

Background: One lesson from the current COVID-19 pandemic is the need to optimize health care provision outside of traditional settings, and potentially over longer periods of time. An important strategy is remote patient monitoring (RPM), allowing patients to remain at home, while they transmit health data and receive follow-up services. Materials and Methods: We conducted an overview of the latest systematic reviews that had included randomized controlled trials with adult patients with chronic diseases. We summarized results and displayed these in forest plots, and used GRADE (Grading of Recommendations Assessment, Development, and Evaluation) to assess our certainty of the evidence. Results: We included 4 systematic reviews that together reported on 11 trials that met our definition of RPM, each including patients with diabetes and/or hypertension. RPM probably makes little to no difference on HbA1c levels. RPM probably leads to a slight reduction in systolic blood pressure, with questionable clinical meaningfulness. RPM probably has a small negative effect on the physical component of health-related quality of life, but the clinical significance of this reduction is uncertain. We have low confidence in the finding that RPM makes no difference to the remaining five primary outcomes. Conclusion: Most of our findings are consistent with reviews of other, broader definitions of RPM. The type of RPM examined in this review is as effective as standard treatment for patients with diabetes/hypertension. If this or other types of RPM are to be used for "long covid" patients or for other chronic disease groups post-pandemic, we need to understand why RPM may negatively affect quality of life.

Ambient assisted living technology-mediated interventions for older people and their informal carers in the context of healthy ageing: A scoping review

BACKGROUND AND AIMS

There is a growing demand for health and social care services to provide technology-mediated interventions that promote the health and well-being of older people with health or care needs and of their informal carers. The objectives of this study were to scope and review the nature and extent of prior intervention studies involving ambient assisted living technology-mediated interventions for older people and their informal carers, and how and in what ways (if any) the goals and aims of these interventions reflected the domains of the World Health Organization framework for healthy ageing.

METHODS

We conducted a scoping review. Data were collected between June and October 2018 with an updated search in October 2020. A total of 85 articles were eligible for inclusion.

RESULTS

Nine categories described the aims and content of the included studies. The healthy ageing domain "Ability to meet basic needs" was mirrored in four categories, whereas "Ability to contribute to society" was not addressed at all.

CONCLUSION

The ways in which domains of healthy ageing are mirrored suggest that there is an emphasis on individual factors and individual responsibility, and a lack of attention given to broader, environmental factors affecting healthy ageing. Only a few of the studies used a dyadic approach when assessing health outcomes concerning older people and their informal carers.

Effect of Telemetric Interventions on Glycated Hemoglobin A1c and Management of Type 2 Diabetes Mellitus: Systematic Meta-Review

Background

Diabetes mellitus is a chronic burden, with a prevalence that is increasing worldwide. Telemetric interventions have attracted great interest and may provide effective new therapeutic approaches for improving type 2 diabetes mellitus (T2DM) care.

Objective

The objective of this study was to analyze the clinical effectiveness of telemetric interventions on glycated hemoglobin A_1c (HbA_1c) specifically and T2DM management generally in a systematic meta-review.

Methods

A systematic literature search was performed in PubMed, CINAHL, Cochrane Library, Web of Science Core Collection, and EMBASE databases from January 2008 to April 2020. Studies that addressed HbA_1c, blood pressure, fasting blood glucose, BMI, diabetes-related and health-related quality of life, cost-effectiveness, time savings, and the clinical effectiveness of telemetric interventions were analyzed. In total, 73 randomized controlled trials (RCTs), 10 systematic reviews/meta-analyses, 9 qualitative studies, 2 cohort studies, 2 nonrandomized controlled studies, 2 observational studies, and 1 noncontrolled intervention study were analyzed.

Results

Overall, 1647 citations were identified. After careful screening, 99 studies (n=15,939 patients; n=82,436 patient cases) were selected by two independent reviewers for inclusion in the review. Telemetric interventions were categorized according to communication channels to health care providers: (1) “real-time video” interventions, (2) “real-time audio” interventions, (3) “asynchronous” interventions, and (4) “combined” interventions. To analyze changes in HbA_1c, suitable RCTs were pooled and the average was determined. An HbA_1c decrease of –1.15% (95% CI –1.84% to –0.45%), yielding an HbA_1c value of 6.95% (SD 0.495), was shown in studies using 6-month “real-time video” interventions.

Conclusions

Telemetric interventions clearly improve HbA_1c values in both the short term and the long term and contribute to the effective management of T2DM. More studies need to be done in greater detail.

Efficacy of telemedicine on glycaemic control in patients with type 2 diabetes: A meta-analysis

BACKGROUND

Telemedicine is defined as the delivery of health services via remote communication and technology. It is a convenient and cost-effective method of intervention, which has shown to be successful in improving glyceamic control for type 2 diabetes patients. The utility of a successful diabetes intervention is vital to reduce disease complications, hospital admissions and associated economic costs.

AIM

To evaluate the effects of telemedicine interventions on hemoglobin A1c (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), post-prandial glucose (PPG), fasting plasma glucose (FPG), weight, cholesterol, mental and physical quality of life (QoL) in patients with type 2 diabetes. The secondary aim of this study is to determine the effect of the following subgroups on HbA1c post-telemedicine intervention; telemedicine characteristics, patient characteristics and self-care outcomes.

METHODS

PubMed Central, Cochrane Library, Embase and Scopus databases were searched from inception until 18^th of June 2020. The quality of the 43 included studies were assessed using the PEDro scale, and the random effects model was used to estimate outcomes and I² for heterogeneity testing. The mean difference and standard deviation data were extracted for analysis.

RESULTS

We found a significant reduction in HbA1c [-0.486%; 95% confidence interval (CI) -0.561 to -0.410, P < 0.001], DBP (-0.875 mmHg; 95%CI -1.429 to -0.321, P < 0.01), PPG (-1.458 mmol/L; 95%CI -2.648 to -0.268, P < 0.01), FPG (-0.577 mmol/L; 95%CI -0.710 to -0.443, P < 0.001), weight (-0.243 kg; 95%CI -0.442 to -0.045, P < 0.05), BMI (-0.304; 95%CI -0.563 to -0.045, P < 0.05), mental QoL (2.210; 95%CI 0.053 to 4.367, P < 0.05) and physical QoL (-1.312; 95%CI 0.545 to 2.080, P < 0.001) for patients following telemedicine interventions in comparison to control groups. The results of the meta-analysis did not show any significant reductions in SBP and cholesterol in the telemedicine interventions compared to the control groups. The telemedicine characteristic subgroup analysis revealed that clinical treatment models of intervention, as well as those involving telemonitoring, and those provided via modes of videoconference or interactive telephone had the greatest effect on HbA1c reduction. In addition, interventions delivered at a less than weekly frequency, as well as those given for a duration of 6 mo, and those lead by allied health resulted in better HbA1c outcomes. Furthermore, interventions with a focus on biomedical parameters, as well as those with an engagement level > 70% and those with a drop-out rate of 10%-19.9% showed greatest HbA1c reduction. The patient characteristics investigation reported that Hispanic patients with T2DM had a greater HbA1c reduction post telemedicine intervention. For self-care outcomes, telemedicine interventions that resulted in higher post-intervention glucose monitoring and self-efficacy were shown to have better HbA1c reduction.

CONCLUSION

The findings indicate that telemedicine is effective for improving HbA1c and thus, glycemic control in patients with type 2 diabetes. In addition, telemedicine interventions were also found to significantly improved other health outcomes as well as QoL scores. The results of the subgroup analysis emphasized that interventions in the form of telemonitoring, via a clinical treatment model and with a focus on biomedical parameters, delivered at a less than weekly frequency and 6 mo duration would have the largest effect on HbA1c reduction. This is in addition to being led by allied health, through modes such as video conference and interactive telephone, with an intervention engagement level > 70% and a drop-out rate between 10%-19.9%. Due to the high heterogeneity of included studies and limitations, further studies with a larger sample size is needed to confirm our findings.

Assessment of remote patient monitoring (RPM) systems for patients with type 2 diabetes: a systematic review and meta-analysis

Introduction

The objective of this study is to conduct an assessment of Remote Patient Monitoring (RPM) systems compared to usual care for controlling glycosylated hemoglobin in type 2 diabetes.

Methods

The study was a systematic review with meta-analysis and meta-regression. A systematic search was performed via the most important electronic databases of medical resources, such as PubMed, Scopus and Cochrane library. The main outcome was HbA1C. The heterogeneity sources were examined using Chi-square (Q) and I2 tests. Meta-analyses were done using Stata version 11 software. Statistical significance was defined as P < 0.05. Random effects model was used in meta-analysis, and the heterogeneity more than 50% was considered as significant.

Results

The results of the systematic review and meta-analysis indicated that the effect size index (Difference of Pre-test/Post-test Control Design-2nd method "using pooled pretest SD" (DPPC2)) among users of RPM for type 2 diabetic patients was -0.32 with a confidence interval of 95% (from -0.45 to -0.19) as compared to the control group. The current study declared a vital role of RPM technology in reduction of hemoglobin glycogen levels. The results of the subgroup analysis showed that RPM is more effective for patients who are residents of cities, having intervention lengths less than 6 months, getting the orders from the physician and using the websites as their intervention type.

Conclusion

The current study indicted the efficacy of RPM in reducing HbA1c among type 2 diabetic patients, which could be a base for policymakers to decide on the introduction of this technology in Iran.

Comparison of three meta-analytic methods using data from digital interventions on type 2 diabetes

AIMS

Pooling the effect sizes of randomized controlled trials (RCTs) from continuous outcomes, such as glycated hemoglobin level (HbA1c), is an important method in evidence syntheses. However, due to challenges related to baseline imbalances and pre/post correlations, simple analysis of change scores (SACS) and simple analysis of final values (SAFV) meta-analyses result in under- or overestimation of effect estimates. This study was aimed to compare pooled effect sizes estimated by Analysis of Covariance (ANCOVA), SACS, and SAFV meta-analyses, using the example of RCTs of digital interventions with HbA1c as the main outcome.

MATERIALS AND METHODS

Three databases were systematically searched for RCTs published from 1993 through June 2017. Two reviewers independently assessed titles and abstracts using predefined eligibility criteria, assessed study quality, and extracted data, with disagreements resolved by arbitration from a third reviewer.

RESULTS

ANCOVA, SACS, and SAFV resulted in pooled HbA1c mean differences of -0.39% (95% CI: [-0.51, -0.26]), -0.39% (95% CI: [-0.51, -0.26]), and -0.34% (95% CI: [-0.48-0.19]), respectively. Removing studies with both high baseline imbalance (≥±0.2%) and pre/post correlation of ≥±0.6 resulted in a mean difference of -0.39% (95% CI: [-0.53, -0.26]), -0.40% (95% CI: [-0.54, -0.26]), and -0.33% (95% CI: [-0.48, -0.18]) with ANCOVA, SACS, and SAFV meta-analyses, respectively. Substantial heterogeneity was noted. Egger's test for funnel plot symmetry did not indicate evidence of publication bias for all methods.

CONCLUSION

By all meta-analytic methods, digital interventions appear effective in reducing HbA1c in type 2 diabetes. The effort to adjust for baseline imbalance and pre/post correlation using ANCOVA relies on the level of detail reported from individual studies. Reporting detailed summary data and, ideally, access to individual patient data of intervention trials are essential.

Effectiveness of Digital Interventions for Improving Glycemic Control in Persons with Poorly Controlled Type 2 Diabetes: A Systematic Review, Meta-analysis, and Meta-regression Analysis

BACKGROUND

Digital interventions may assist patients with type 2 diabetes in improving glycemic control. We aimed to synthesize effect sizes of digital interventions on glycated hemoglobin (HbA1c) levels and to identify effective features of digital interventions targeting patients with poorly controlled type 2 diabetes.

MATERIALS AND METHODS

MEDLINE, ISI Web of Science, and PsycINFO were searched for randomized controlled trials (RCTs) comparing the effects of digital interventions with usual care. Two reviewers independently assessed studies for eligibility and determined study quality, using the Cochrane Risk of Bias Assessment Tool. The Behavioral Change Technique Taxonomy V1 (BCTTv1) was used to identify BCTs used in interventions. Mean HbA1c differences were pooled using analysis of covariance to adjust for baseline differences and pre-post correlations. To examine effective intervention features and to evaluate differences in effect sizes across groups, meta-regression and subgroup analyses were performed.

RESULTS

Twenty-three arms of 21 RCTs were included in the meta-analysis (n = 3787 patients, 52.6% in intervention arms). The mean HbA1c baseline differences ranged from -0.2% to 0.64%. The pooled mean HbA1c change was statistically significant (-0.39 {95% CI: [-0.51 to -0.26]} with substantial heterogeneity [I² statistic, 80.8%]) and a significant HbA1c reduction was noted for web-based interventions. A baseline HbA1c level above 7.5%, β = -0.44 (95% CI: [-0.81 to -0.06]), the BCTs "problem solving," β = -1.30 (95% CI: [-2.05 to -0.54]), and "self-monitoring outcomes of behavior," β = -1.21 (95% CI: [-1.95 to -0.46]) were significantly associated with reduced HbA1c levels.

CONCLUSIONS

Digital interventions appear effective for reducing HbA1c levels in patients with poorly controlled type 2 diabetes.

Effect of Health Information Technologies on Glycemic Control Among Patients with Type 2 Diabetes

PURPOSE OF REVIEW

This study was to present meta-analysis findings across selected clinical trials for the effect of health information technologies (HITs) on glycemic control among patients with type 2 diabetes.

RECENT FINDINGS

HITs may be promising in diabetes management. However, findings on effect size of glycated hemoglobin level (HbA1c) yielded from HITs varied across previous studies. This is likely due to heterogeneity in sample size, adherence to standard quantitative method, and/or searching criteria (e.g., type of HITs, type of diabetes, specification of patient population, randomized vs. nonrandomized trials). We systematically searched Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and the Cochrane Library for peer-reviewed randomized control trials that studied the effect of HITs on HbA1c reduction. We also used Google Scholar and a hand search to identify additional studies. Thirty-four studies (40 estimates) met the criteria and were included in the analysis. Overall, introduction of HITs to standard diabetes treatment resulted in a statistically and clinically reduced HbA1c. The bias adjusted HbA1c reduction due to the combined HIT interventions was - 0.56 [Hedges' g = - 0.56 (- 0.70, - 0.43)]. The reduction was significant across each of the four types of HIT intervention under review, with mobile phone-based approaches generating the largest effects [Hedges' g was - 0.67 (- 0.90, - 0.45)]. HITs can be an effective tool for glycemic control among patients with type 2 diabetes. Future studies should examine long-term effects of HITs and explore factors that influence their effectiveness.

Use of Expectation Disconfirmation Theory to Test Patient Satisfaction with Asynchronous Telemedicine for Diabetic Retinopathy Detection

OBJECTIVE

The purpose of the study is to extend research on patient satisfaction with telemedicine services by employing the theoretical framework of Expectation Disconfirmation Theory (EDT) for diabetic retinopathy screenings focusing on rural patients.

METHOD

Adult subjects (n=220) with diabetes were recruited from a single family practice office in rural Iowa. Subjects completed a "pre" survey concerning their forward-looking perceptions of telemedicine prior to using telemedicine for detection of diabetic retinopathy and a "post" survey after they received recommendations from the distant ophthalmologists.

RESULTS

All hypotheses of the EDT model were supported. Patient satisfaction is influenced by both patients' expectations (P<.001) and disconfirmation of expectations (P<.001), and patient satisfaction has a positive impact on patient preference for telemedicine services (P<.001). Overall, patients who received telemedicine services were highly satisfied with telemedicine and developed a favorable disposition towards telemedicine services.

CONCLUSIONS

The EDT model is a viable framework to study patient satisfaction of telemedicine services. While previous feasibility studies have shown that telemedicine for diabetic retinopathy screenings yields diagnostic efficacy, this study applies a theoretical framework to demonstrate the viability of telemedicine for diabetic retinopathy screenings in rural areas.

Effectiveness of Internet-Based Interventions on Glycemic Control in Patients With Type 2 Diabetes: Meta-Analysis of Randomized Controlled Trials

Background

The popularity of internet as an area of research has grown manifold over the years. Given its rapid development and increasing coverage worldwide, internet-based interventions seem to offer a promising option to ameliorate huge burdens brought by type 2 diabetes mellitus. However, studies conducted by different researchers have provided contradictory results on the effect of internet-based interventions in glycemic control.

Objective

This meta-analysis aims to summarize currently available evidence and evaluate the overall impact of internet-based interventions on glycemic management of type 2 diabetic patients.

Methods

A systematic literature search was performed in PubMed, ScienceDirect, and Web of Science. Randomized controlled trials that used glycosylated hemoglobin values as the outcome measure of glycemic control were considered. Risk of bias and publication bias were evaluated.

Results

Of the 492 studies, 35 were included in meta-analysis, and results indicated that the weighted mean difference (WMD) between usual care and internet-based interventions at endpoint was –0.426% (95% CI –0.540 to –0.312; P<.001). Subgroup analyses revealed that intervention duration ≤3 months yielded optimal performance (WMD –0.51%; 95% CI –0.71 to –0.31; P<.001). Combined mobile and website interventions were substantially superior to solely Web-based and mobile-based interventions in glycemic control (combined WMD –0.77%, 95% CI –1.07 to –0.47; P<.001; Web only: WMD –0.48%; 95% CI –0.71 to –0.24, P<.001; mobile only WMD –0.31%, 95% CI –0.49 to –0.14; P<.001). Furthermore, the effect of interventions with automated feedbacks was similar to those with manual feedbacks, and studies with internet-based educational contents were more effective in glycemic control. The assessment revealed a low risk of bias.

Conclusions

In conclusion, utilization of internet-based intervention is beneficial for patients with type 2 diabetes mellitus, and taking full advantage of this type of intervention may substantially reduce the incidence of complications and improve quality of life.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO): CRD42017058032; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=58032 (Archived by WebCite at http://www.webcitation.org/6yY7eQNHr)

The Model for Assessment of Telemedicine (MAST): A scoping review of empirical studies

The evaluation of telemedicine can be achieved using different evaluation models or theoretical frameworks. This paper presents a scoping review of published studies which have applied the Model for Assessment of Telemedicine (MAST). MAST includes pre-implementation assessment (e.g. by use of participatory design), followed by multidisciplinary assessment, including description of the patients and the application and assessment of safety, clinical effectiveness, patient perspectives, economic aspects organisational aspects and socio-cultural, legal and ethical aspects. Twenty-two studies met the inclusion criteria and were included in the review. In this article, research design and methods used in the multidisciplinary assessment are described, strengths and weaknesses are analysed, and recommendations for future research are presented.

Telemonitoring and Health Counseling for Self-Management Support of Patients With Type 2 Diabetes: A Randomized Controlled Trial

Background

The prevalence of diabetes is increasing among adults globally, and there is a need for new models of health care delivery. Research has shown that self-management approaches encourage persons with chronic conditions to take a primary role in managing their daily care.

Objective

The objective of this study was to investigate whether the introduction of a health technology-supported self-management program involving telemonitoring and health counseling had beneficial effects on glycated hemoglobin (HbA_1c), other clinical variables (height, weight, body mass index, blood pressure, blood lipid profile), and health-related quality of life (HRQoL), as measured using the Short Form Health Survey (SF-36) version 2 in patients with type 2 diabetes.

Methods

This was a pragmatic randomized controlled trial of patients with type 2 diabetes. Both the control and intervention groups received usual care. The intervention group also participated in additional health promotion activities with the use of the Prescribed Healthcare Web application for self-monitoring of blood glucose and blood pressure. About every second month or when needed, the general practitioner or the diabetes nurse reviewed the results and the health care activity plan.

Results

A total of 166 patients with type 2 diabetes were randomly assigned to the intervention (n=87) or control (n=79) groups. From the baseline to follow-up, 36 patients in the intervention group and 5 patients in the control group were lost to follow-up, and 2 patients died. Additionally, HbA_1c was not available at baseline in one patient in the intervention group. A total of 122 patients were included in the final analysis after 19 months. There were no significant differences between the groups in the primary outcome HbA_1c level (P=.33), and in the secondary outcome HRQoL as measured using SF-36. A total of 80% (67/87) of the patients in the intervention group at the baseline, and 98% (47/50) of the responders after 19-month intervention were familiar with using a personal computer (P=.001). After 19 months, nonresponders (ie, data from baseline) reported significantly poorer mental health in social functioning and role emotional subscales on the SF-36 (P=.03, and P=.01, respectively).

Conclusions

The primary outcome HbA_1c level and the secondary outcome HRQoL did not differ between groups after the 19-month follow-up. Those lost to follow-up reported significantly poorer mental health than did the responders in the intervention group.

Trial Registration

Clinicaltrials.gov NCT01478672; https://clinicaltrials.gov/ct2/show/NCT01478672 (Archived by WebCite at http://www.webcitation.org/6r4eILeyu)