A Ubiquitous Chronic Disease Care system using cellular phones and the internet

Internet-based digital intervention to support the self-management of hypertension compared to usual care: results of the HALCYON randomized controlled trial

BACKGROUND

Hypertension is a major public health problem. Despite existing treatment options, overall blood pressure control is still insufficient. Digital health interventions have the potential to improve treatment success. We developed liebria, an internet-based digital intervention accessible via smartphones and computers, designed to support the self-management of hypertension.

METHODS

We tested the effectiveness of liebria in reducing systolic blood pressure and improving other relevant endpoints in adults with hypertension using a parallel randomized controlled trial design. Adults with hypertension (mean age 54.5 years, 47.1% male) were recruited via a German health insurance provider and randomized (1:1; concealed allocation; no blinding of participants) to receive liebria in addition to treatment as usual (n = 52), or treatment as usual alone (n=50). Primary outcome was systolic blood pressure after 3 months (T1). Secondary endpoints were diastolic blood pressure, pulse pressure, quality of life, medication adherence, and social and work-related functioning.

RESULTS

The study's statistical power was limited due to a smaller sample size (N = 102) than the a priori target sample size (N=676). Intention-to-treat analyses showed an effect of liebria on systolic blood pressure (baseline-adjusted between-group difference -3.5 mmHg, 95% CI -7.13 to 0.13, p = .053, Cohen's d = 0.36). More participants in the intervention group (78.2% vs. 54.3% in the control group) showed reductions in systolic blood pressure (p = .076). Moreover, liebria had effects on social and work-related functioning. No effects emerged for diastolic blood pressure, pulse pressure, quality of life, or medication adherence. No adverse events or device effects were observed.

CONCLUSIONS

The present study shows first promising results of liebria's effects on systolic blood pressure and social and work-related functioning. Future studies should aim to replicate effects in a larger sample to increase statistical power.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS00025871); https://drks.de/search/en/trial/DRKS00025871 ; date of registration: October 5, 2021.

A scoping review of digital health technologies in multimorbidity management: mechanisms, outcomes, challenges, and strategies

INTRODUCTION

Multimorbidity amplifies healthcare burdens due to the intricate requirements of patients and the pathophysiological complexities of multiple diseases. To address this, digital health technologies play a crucial role in effective healthcare delivery, requiring comprehensive evidence on their applications in managing multimorbidity. Therefore, this scoping review aims to identify various types of digital health technologies, explore their mechanisms, and identify barriers and facilitators within the context of multimorbidity.

METHODS

This scoping review follows the Preferred Reporting Items for Scoping Reviews guidelines. PubMed, Scopus, Web of Science, EMBASE, and Google Scholar were used to search articles. Data extraction focused on study characteristics, types of health technologies, mechanisms, outcomes, challenges, and facilitators. Results were presented using figures, tables, and texts. Thematic analysis was employed to describe mechanisms, impacts, challenges, and strategies related to digital health technologies in managing multimorbidity.

RESULTS

Digital health technology encompasses smartphone apps, wearable devices, and platforms for remote healthcare (telehealth). These technologies work through care coordination, collaboration, communication, self-management, remote monitoring, health data management, and tele-referrals. Digital health technologies improved quality of care and life, cost efficiency, acceptability of care, collaboration, streamlined healthcare delivery, reduced workload, and bridging knowledge gaps. Patients' and healthcare providers' resistance and skills, lack of support (technical, financial, and infrastructure), and ethical concerns (e.g., privacy) barred digital health technologies implementation. Arranging organization, providing technical support, employing care coordination strategies, enhancing acceptability, deploying appropriate technology, considering patient needs, and adhering with ethical principles facilitate digital health technologies implementation.

CONCLUSIONS

Digital health technology holds significant promise in improving care for individuals with multimorbidity by enhancing coordination, self-management, and monitoring. Successful implementation requires addressing challenges such as patient resistance and infrastructure limitations through targeted strategies and investments. It is also essential to consider usability, privacy, and trustworthiness when adopting these tools.

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.

The effectiveness of telemedicine in the management of type 2 diabetes: A systematic review

Background

Type 2 diabetes, a lifestyle-related disease demanding daily self-management, is a significant health concern. In this context, the use of telemedicine as a management tool is a relatively new and promising approach. This study aims to contribute to the growing body of knowledge by identifying the effectiveness of telemedicine in managing type 2 diabetes through a systematic review approach.

Methods

Four databases were searched including PubMed, Virtual Health Library, Global Health Library, and Google Scholar on 27 July 2022. Additionally, a manual search was performed to identify any relevant articles that may have been missed. The quality of the included articles was rigorously assessed using the Study Quality Assessment Tools of the National Institute of Health.

Results

We analyzed data from 134 articles. All 134 studies were published between 2002 and 2022, including 103 controlled intervention trials, 13 cohort studies, 7 before-after (pre-post) studies with no control group, 1 initial trial, 1 case study, 1 pilot study, and 8 two-arm studies that did not report the study design. Accordingly, most studies show positive changes in glycemic index in every group using telemedicine. Overall, although the BMI and weight indices in the studies improved at the end of the course, the improvement values were considered insignificant.

Conclusion

Telemedicine may be a valuable solution for blood sugar management in patients with type 2 diabetes. However, the effectiveness of telemedicine in improving BMI and quality of life is unclear.

Mapping interventional components and behavior change techniques used to promote self-management in people with multimorbidity: a scoping review

Ageing populations and improved survival, have contributed to a rise in the number of people living with multimorbidity, raising issues related to polypharmacy, treatment burden, competing priorities and poor coordination of care. Self-management programs are increasingly included as an essential component of interventions to improve outcomes in this population. However, an overview of how interventions supporting self-management in patients with multimorbidity is missing. This scoping review focused on mapping the literature on patient-centered interventions for people living with multimorbidity. We searched several databases, clinical registries, and grey literature for RCTs published between 1990-2019 describing interventions that supported self-management in people with multimorbidity. We included 72 studies that were found to be very heterogeneous when it comes to the population, delivery modes and modalities, intervention elements and facilitators. The results pointed to an extensive use of cognitive behavioral therapy as a basis for interventions, as well as behavior change theories and disease management frameworks. The most coded behavior change techniques stemmed from the categories Social Support, Feedback and monitoring and Goals and Planning. To allow for implementation of effective interventions in clinical practice, improved reporting of intervention mechanisms in RCTs is warranted.

Digital Health in Diabetes and Cardiovascular Disease

BACKGROUND

Digital health technologies are rapidly evolving and transforming the care of diabetes and cardiovascular disease (CVD).

PURPOSE OF THE REVIEW

In this review, we discuss emerging approaches incorporating digital health technologies to improve patient outcomes through a more continuous, accessible, proactive, and patient-centered approach. We discuss various mechanisms of potential benefit ranging from early detection to enhanced physiologic monitoring over time to helping shape important management decisions and engaging patients in their care. Furthermore, we discuss the potential for better individualization of management, which is particularly important in diseases with heterogeneous and complex manifestations, such as diabetes and cardiovascular disease. This narrative review explores ways to leverage digital health technology to better extend the reach of clinicians beyond the physical hospital and clinic spaces to address disparities in the diagnosis, treatment, and prevention of diabetes and cardiovascular disease.

CONCLUSION

We are at the early stages of the shift to digital medicine, which holds substantial promise not only to improve patient outcomes but also to lower the costs of care. The review concludes by recognizing the challenges and limitations that need to be addressed for optimal implementation and impact. We present recommendations on how to navigate these challenges as well as goals and opportunities in utilizing digital health technology in the management of diabetes and prevention of adverse cardiovascular 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.

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.

Effectiveness of a diabetes program based on digital health on capacity building and quality of care in type 2 diabetes: a pragmatic quasi-experimental study

Health systems in Latin America face many challenges in controlling the increasing burden of diabetes. Digital health interventions are a promise for the provision of care, especially in developing countries where mobile technology has a high penetration. This study evaluated the effectiveness of the implementation of a Diabetes Program (DP) that included digital health interventions to improve the quality of care of persons with type 2 Diabetes (T2DM) in a vulnerable population attending the public primary care network.

MATERIALS AND METHODS

A quasi-experimental pre-post uncontrolled study was conducted in 19 primary care centers and hospitals in the province of Corrientes, Argentina. We included persons with T2DM, age >  = 18 years with access to a mobile phone. The multicomponent intervention included a mobile app with a diabetes registry, a clinical decision support tool for providers and a text messaging intervention for patients.

RESULTS AND DISCUSSION

One thousand sixty-five participants were included, 72.8% had less than 12 years of formal education and 53.5% lacked health coverage. Comorbidities were hypertension (60.8%) and overweight/obesity (88.2%). During follow-up there was a significant increase in the proportion of participants who underwent laboratory check-ups (HbA1c 20.3%-64.4%; p < 0.01) and foot exams (62.1%-87.2%; p < 0.01). No changes were observed at 12 and 24 months in the proportion of participants with poor metabolic control. The proportion of participants with uncontrolled blood pressure (≥ 140/90 mmHg) decreased from 47.2% at baseline to 30.8% at 24 months in those with a follow-up visit.

CONCLUSION

The DP was innovative by integrating digital health interventions in the public primary care level. The study showed improvements in quality indicators related with diabetes care processes and in blood pressure control.

Exercise in Obesity-the Role of Technology in Health Services: Can This Approach Work?

PURPOSE OF REVIEW

Physical activity (PA) is an important strategy to prevent and treat obesity. Electronic health (eHealth) interventions, such as wearable activity monitors and smartphone apps, may promote adherence to regular PA and successful weight loss. This review highlights the evidence for eHealth interventions in promoting PA and reducing weight.

RECENT FINDINGS

Wearables can increase PA and are associated with moderate weight loss in middle/older-aged individuals, with less convincing effects long-term (> 1 year) and in younger people. Data for interventions such as mobile phone applications, SMS, and exergaming are less robust. Investigations of all eHealth interventions are often limited by complex, multi-modality study designs, involving concomitant dietary modification, making the independent contribution of each eHealth intervention on body weight challenging to assess. eHealth interventions may promote PA, thereby contributing to weight loss/weight maintenance; however, further evaluation is required for this approach to be adopted into routine clinical practice.

Efficacy of the mHealth application in patients with type 2 diabetes transitioning from inpatient to outpatient care: A randomized controlled clinical trial

INTRODUCTION

No studies have assessed the efficacy of telemedicine using a platform for recording and adjusting insulin doses in patients with diabetes mellitus type 2 (DM2) transitioning from inpatient to outpatient care. This study aimed to assess, in a population of patients with DM2, discharged from a tertiary referral hospital, whether treatment based on the use of an mHealth application was associated with better glycemic control at the 3-month follow-up, than standard care.

METHODS

This open, randomized, controlled clinical trial included adult DM2 patients who were transitioning from inpatient to outpatient care. The efficacy and safety of patient management with and without mHealth was compared at the 3-month follow-up. The primary outcome was the change in the Glycosylated hemoglobin (HbA1c) levels. The secondary outcomes were the rates of hypoglycemic and hyperglycemic events and treatment satisfaction measured using the Insulin Treatment Satisfaction Questionnaire (ITSQ).

RESULTS

In total, 86 patients (41 using mHealth) were included in the clinical trial. HbA1c levels showed a significant decrease in both groups. The mean HbA1c level was significantly lower in the mHealth group. Patients using mHealth showed decreased incidence rate ratios of hypoglycemia 3.0 mmol/L [<54 mg/dl], hypoglycemia ranging from 3.0 to 3.8 mmol/L [54 to 70 mg/dl] and severe hypoglycemia. The level of satisfaction assessed using the ITSQ was higher in the mHealth group.

CONCLUSION

Using mHealth in patients with DM2 transitioning from inpatient to outpatient care improves metabolic control and may reduce the hypoglycemia rates.

Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review

Background

In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes.

Objective

We performed a systematic review of the literature on consumer BP monitors that collect PGHD for managing hypertension to summarize their clinical impact on health and surrogate outcomes. We focused particularly on studies designed to measure the specific effect of using a BP monitor independent of cointerventions. We have also summarized the process and consumer experience outcomes.

Methods

An information specialist searched PubMed, MEDLINE, and Embase for controlled studies on consumer BP monitors published up to May 12, 2020. We assessed the risk of bias using an adapted 9-item appraisal tool and performed a narrative synthesis of the results.

Results

We identified 41 different types of BP monitors used in 49 studies included for review. Device engineers judged that 38 (92%) of those devices were similar to the currently available consumer BP monitors. The median sample size was 222 (IQR 101-416) participants, and the median length of follow-up was 6 (IQR 3-12) months. Of the included studies, 18 (36%) were designed to isolate the clinical effects of BP monitors; 6 of the 18 (33%) studies evaluated health outcomes (eg, mortality, hospitalizations, and quality of life), and data on those outcomes were unclear. The lack of clarity was due to low event rates, short follow-up duration, and risk of bias. All 18 studies that isolated the effect of BP monitors measured both systolic and diastolic BP and generally demonstrated a decrease of 2 to 4 mm Hg in systolic BP and 1 to 3 mm Hg in diastolic BP compared with non–BP monitor groups. Adherence to using consumer BP monitors ranged from 38% to 89%, and ease of use and satisfaction ratings were generally high. Adverse events were infrequent, but there were a few technical problems with devices (eg, incorrect device alerts).

Conclusions

Overall, BP monitors offer small benefits in terms of BP reduction; however, the health impact of these devices continues to remain unclear. Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers. Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers.

Effectiveness of Remotely Delivered Interventions to Simultaneously Optimize Management of Hypertension, Hyperglycemia and Dyslipidemia in People With Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background

Remotely delivered interventions may be more efficient in controlling multiple risk factors in people with diabetes.

Purpose

To pool evidence from randomized controlled trials testing remote management interventions to simultaneously control blood pressure, blood glucose and lipids.

Data Sources

PubMed/Medline, EMBASE, CINAHL and the Cochrane library were systematically searched for randomized controlled trials (RCTs) until 20th June 2021.

Study Selection

Included RCTs were those that reported participant data on blood pressure, blood glucose, and lipid outcomes in response to a remotely delivered intervention.

Data Extraction

Three authors extracted data using a predefined template. Primary outcomes were glycated hemoglobin (HbA1c), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), systolic and diastolic blood pressure (SBP & DBP). Risk of bias was assessed using the Cochrane collaboration RoB-2 tool. Meta-analyses are reported as standardized mean difference (SMD) with 95% confidence intervals (95%CI).

Data Synthesis

Twenty-seven RCTs reporting on 9100 participants (4581 intervention and 4519 usual care) were included. Components of the remote management interventions tested were identified as patient education, risk factor monitoring, coaching on monitoring, consultations, and pharmacological management. Comparator groups were typically face-to-face usual patient care. Remote management significantly reduced HbA1c (SMD -0.25, 95%CI -0.33 to -0.17, p<0.001), TC (SMD -0.17, 95%CI -0.29 to -0.04, p<0.0001), LDL-c (SMD -0.11, 95%CI -0.19 to -0.03, p=0.006), SBP (SMD -0.11, 95%CI -0.18 to -0.04, p=0.001) and DBP (SMD -0.09, 95%CI -0.16 to -0.02, p=0.02), with low to moderate heterogeneity (I²= 0 to 75). Twelve trials had high risk of bias, 12 had some risk and three were at low risk of bias.

Limitations

Heterogeneity and potential publication bias may limit applicability of findings.

Conclusions

Remote management significantly improves control of modifiable risk factors.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=258433], identifier PROSPERO (CRD42021258433).

Home Telemonitoring of Patients With Type 2 Diabetes: A Meta-Analysis and Systematic Review

Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (-0.10 mmHg [P = 0.0041] and -0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.

Challenges of Telemonitoring Programs for Complex Chronic Conditions: Randomized Controlled Trial With an Embedded Qualitative Study

Background

Despite the growing prevalence of people with complex conditions and evidence of the positive impact of telemonitoring for single conditions, little research exists on telemonitoring for this population.

Objective

This randomized controlled trial and embedded qualitative study aims to evaluate the impact on and experiences of patients and health care providers (HCPs) using a telemonitoring system with decision support to manage patients with complex conditions, including those with multiple chronic conditions, compared with the standard of care.

Methods

A pragmatic, unblinded, 6-month randomized controlled trial sought to recruit 146 patients with ≥1 diagnosis of heart failure (HF), uncontrolled hypertension (HT), and insulin-requiring diabetes mellitus (DM) from outpatient specialty settings in Toronto, Ontario, Canada. Participants were randomized into the control and telemonitoring groups, with the latter being instructed to take readings relevant to their conditions. The telemonitoring system contained an algorithm that generated decision support in the form of actionable self-care directives to patients and alerts to HCPs. The primary outcome was health status (36-Item Short Form Health Survey questionnaire). Secondary outcomes included anxiety and depression, self-efficacy in chronic disease management, and self-reported health service use. HF-related quality of life and self-care measures were also collected from patients followed for HF. Within- and between-group change scores were analyzed for statistical significance (P<.05). A convenience sample of HCPs and patients in the intervention group was interviewed about their experiences.

Results

A total of 96 patients were recruited and randomized. Recruitment was terminated early because of implementation challenges and the onset of the COVID-19 pandemic. No significant within- and between-group differences were found for the main primary and secondary outcomes. However, a within-group analysis of patients with HF found improvements in self-care maintenance (P=.04) and physical quality of life (P=.046). Opinions expressed by the 5 HCPs and 13 patients who were interviewed differed based on the monitored conditions. Although patients with HF reported benefitting from actionable self-care guidance and meaningful interactions with their HCPs, patient and HCP users of the DM and HT modules did not think telemonitoring improved the clinical management of those conditions to the same degree. These differing experiences were largely attributed to the siloed nature of specialty care and the design of the decision support, whereby fluctuations in the status of HT and DM typically required less urgent interventions compared with patients with HF.

Conclusions

We recommend that future research conceive telemonitoring as a program and that self-management and clinical decision support are necessary but not sufficient components of such programs for patients with complex conditions and lower acuity. We conclude that telemonitoring for patients with complex conditions or within multidisciplinary care settings may be best operationalized through nurse-led models of care.

Trial Registration

ClinicalTrials.gov NCT03127852; https://clinicaltrials.gov/ct2/show/NCT03127852

International Registered Report Identifier (IRRID)

RR2-10.2196/resprot.8367

The effectiveness of automated digital health solutions at successfully managing obesity and obesity-associated disorders: A PICO-structured investigation

Most adults in the UK and USA are classified as overweight or obese. Recent studies suggest that the prevalence of obesity has further increased during the SARS-CoV-2 pandemic and associated lockdowns. Digital technologies may be effective at managing obesity and related comorbidities, a potential further justified by social isolation and distancing circumstances.

This review of published literature employed a Patient-Intervention-Comparison-Outcome structured approach on the use of digital solutions to determine the effectiveness of their use in the management and treatment of obesity, hypertension, and type 2 diabetes and included commercially available, automated devices and applications that did not require intervention from a clinician. Our search covered studies published between January 2004 and February 2019, and 18 papers were included in the final analysis. The digital solutions reviewed were smartphone applications, wearable activity trackers, and ‘digital medicine offerings’ (DMO), including ingestible sensors and wearable patches.

This study found that not all interventions were effective at encouraging the lifestyle changes required for the management of obesity. Smartphone applications requiring interaction from the patient appeared to be more effective at encouraging engagement with treatment interventions than more passive wearable activity trackers. Automated feedback from smartphone applications was effective at managing type 2 diabetes, while DMO were effective at reducing blood pressure.

With the advancement of new technologies alongside a rapid increase in the prevalence of obesity and associated disorders, further studies comparing the various technologies available in larger sample populations for longer periods would help determine the most cost-effective preventive and therapeutic strategies.

Comparative effect of eHealth interventions on hypertension management-related outcomes: A network meta-analysis

BACKGROUND

Increasingly, health professionals and patients have begun to be involved in eHealth interventions to assist in the self-management of hypertension. Therefore, this study was aimed at comparing the effect of different types of eHealth interventions (phone calls, blood pressure telemonitoring, emails, web-site, smartphone-app, short message service (SMS) and more than two eHealth interventions) on reducing systolic and diastolic blood pressure, increasing adherence to medication treatment, improving physical activity compliance, controlling blood pressure, and improving quality of life (QoL).

METHODS

A systematic search in MEDLINE (via PubMed), EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science databases was conducted to identify experimental studies addressing the effect of eHealth interventions on the self-management of hypertension. Comparative evaluation of the eHealth interventions effect were performed by conducting a standard pairwise meta-analysis and a network meta-analysis for direct and indirect comparisons between eHealth interventions and control/non-intervention.

RESULTS

Fifty-one studies were included in the analysis showing a moderate effect size for more than two types of eHealth interventions (-0.46; 95%CI: -0.64, -0.27, p < 0.001 and -0.29; 95%CI: -0.46, -0.13, p < 0.001), phone calls (-0.37; 95%CI: -0.57, -0.17, p < 0.001 and -0.29; 95%CI: -0.52, -0.07, p = 0.011) and smartphone-app (-0.26; 95%CI: -0.50, -0.01, p = 0.040 and -0.40; 95%CI: -0.70, -0.10, p = 0.010) on reducing both systolic and diastolic blood pressure, respectively. Additionally, i) smartphone-app improved medication adherence by 45%; ii) more than two types of eHealth interventions and emails improved physical activity compliance by 18% and 57% respectively; ii) more than two types of eHealth interventions, phone calls, blood pressure telemonitoring, website and SMS improved blood pressure control between 16% and 30%; and iv) blood pressure telemonitoring showed a week effect on QoL CONCLUSIONS: Our study reported eHealth to be a suitable intervention for the self-management of hypertension. Considering our results and the population's accessibility to eHealth devices, eHealth could be a useful and largely scalable tool for the self-management of hypertension.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020187468.

Integrating diabetes technologies with team-based primary care for type 2 diabetes: A pilot trial

This pilot trial studied a novel intervention that integrated diabetes technologies into team-based primary care for type 2 diabetes. We found clinically significant reductions in blood pressure, weight, and glucose. The latter two were statistically significant.

Analysis of Effectiveness and Psychological Techniques Implemented in mHealth Solutions for Middle-Aged and Elderly Adults with Type 2 Diabetes: A Narrative Review of the Literature

BACKGROUND

in diabetes, multiple mHealth solutions were produced and implemented for self-management behaviors. However, little research on the effectiveness of psychological techniques implemented within these mHealth solutions was carried out, and even less with the elderly population where technological barriers might exist. Reliable evidence generated through a comprehensive evaluation of mHealth interventions may accelerate its growth for successful long-term implementation and to help to experience mHealth benefits in an enhanced way in all ages.

OBJECTIVE

this study aimed to review mHealth solutions for diabetes self-management in older adults (adherence to treatments and glycemic control) by analyzing the effectiveness of specific psychological techniques implemented.

METHODS

a narrative review was conducted following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed (Medline) and American Psychological Association (APA) PsycInfo databases were searched for published papers that addressed eHealth solutions' effectiveness for diabetes self-management. Studies in English, Spanish, and/or German of any design were screened, with no time constraints regarding the year of publication. A qualitative analysis of the selected papers was conducted in several steps.

RESULTS

this review found 38 studies setting up and analyzing mHealth solutions for older adults. Most research showed improvements in HbA1c, self-management behaviors, and medication adherence in T2DM patients post intervention. However, different mid-to-long term effects were found across studies, specifically concerning the maintenance and adherence to healthy behaviors. The most employed psychological framework was CBT, including techniques such as self-monitoring of outcome behaviors (mostly targeting glycemia measurements and healthy habits as physical activity and/or diet), tailored motivational feedback from medical staff, and psychoeducation or health coaches. The most successful mHealth intervention combined the feature of tailored feedback messages, interactive communication with healthcare professionals, and multifaceted functions.

CONCLUSIONS

there is a lack of elaborate and detailed information in the literature regarding the factors considered in the design and development of mHealth solutions used as interventions for T2DM self-management in the elderly. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of useful and user-friendly self-management apps that can enhance the quality of life for diabetes patients. Further research adapting mHealth solutions to older adults' sensory deficits is necessary.

Effects of nurse-led web-based interventions on people with type 2 diabetes mellitus: A systematic review and meta-analysis

INTRODUCTION

Diabetes mellitus is an expanding global health problem. Currently, the home management of diabetes is mainly led by a multidisciplinary team based on telemedicine. However, the role nurses play in it remains inconclusive. This study aimed to investigate the effectiveness of nurse-led web-based intervention on glycated haemoglobin, blood pressure and lipid profile in patients with type 2 diabetes.

METHODS

An exhaustive systematic literature search was undertaken using the following databases: PubMed, Web of Science, Embase, The Cochrane Central Register of Controlled Trials and CINAHL. Two investigators independently extracted data and assessed the quality of the studies by examining the risk of bias and using Modified Jadad Score system. We conducted a meta-analysis of randomized controlled trials that had been published from inception to July 2020, using Review Manager 5.3.

RESULTS

Eleven randomized controlled trials were selected that included 2063 participants. Meta-analyses results indicated significant effects on not only glycated haemoglobin (pooled mean difference (MD) = -0.40, 95% confidence interval (CI): -0.5 to -0.26, p < 0.00001), but also on systolic blood pressure (pooled MD = -1.91, 95% CI: -3.73 to -0.09, p = 0.04) and low density lipoprotein (pooled standardized MD = -0.29, 95% CI: -0.44 to -0.15, p < 0.0001). There were no effects of nurse-led web-based intervention on fasting blood glucose, diastolic blood pressure, high density lipoprotein, body mass index and triglycerides.

DISCUSSION

Nurse-led web-based intervention is a promising way to complement routine clinical care. However, the specific intervention content and intervention media still need to carry out large-scale well-designed randomized controlled trials. Systematic review registration: PROSPERO CRD 42020204565.

Mobile phone-based interventions for improving adherence to medication prescribed for the primary prevention of cardiovascular disease in adults

BACKGROUND

Cardiovascular disease (CVD) is a major cause of disability and mortality globally. Premature fatal and non-fatal CVD is considered to be largely preventable through the control of risk factors by lifestyle modifications and preventive medication. Lipid-lowering and antihypertensive drug therapies for primary prevention are cost-effective in reducing CVD morbidity and mortality among high-risk people and are recommended by international guidelines. However, adherence to medication prescribed for the prevention of CVD can be poor. Approximately 9% of CVD cases in the EU are attributed to poor adherence to vascular medications. Low-cost, scalable interventions to improve adherence to medications for the primary prevention of CVD have potential to reduce morbidity, mortality and healthcare costs associated with CVD.

OBJECTIVES

To establish the effectiveness of interventions delivered by mobile phone to improve adherence to medication prescribed for the primary prevention of CVD in adults.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and two other databases on 7 January 2020. We also searched two clinical trials registers on 5 February 2020. We searched reference lists of relevant papers. We applied no language or date restrictions.

SELECTION CRITERIA

We included randomised controlled trials investigating interventions delivered wholly or partly by mobile phones to improve adherence to cardiovascular medications prescribed for the primary prevention of CVD. We only included trials with a minimum of one-year follow-up in order that the outcome measures related to longer-term, sustained medication adherence behaviours and outcomes. Eligible comparators were usual care or control groups receiving no mobile phone-delivered component of the intervention.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane. The main outcomes of interest were objective measures of medication adherence (blood pressure (BP) and cholesterol), CVD events, and adverse events. We contacted study authors for further information when this was not reported.

MAIN RESULTS

We included 14 trials with 25,633 randomised participants. Participants were recruited from community-based primary and tertiary care or outpatient clinics. The interventions varied widely from those delivered solely through short messaging service (SMS) to those involving a combination of modes of delivery, such as SMS in addition to healthcare worker training, face-to-face counselling, electronic pillboxes, written materials, and home blood pressure monitors. Some interventions only targeted medication adherence, while others additionally targeted lifestyle changes such as diet and exercise. Due to heterogeneity in the nature and delivery of the interventions and study populations, we reported most results narratively, with the exception of two trials which were similar enough to meaningfully pool in meta-analyses. The body of evidence for the effect of mobile phone-based interventions on objective outcomes of adherence (BP and cholesterol) was of low certainty, due to most trials being at high risk of bias, and inconsistency in outcome effects. Two trials were at low risk of bias. Among five trials (total study enrolment: 5441 participants) recording low-density lipoprotein cholesterol (LDL-C), two studies found evidence for a small beneficial intervention effect on reducing LDL-C (-5.30 mg/dL, 95% confidence interval (CI) -8.30 to -2.30; and -9.20 mg/dL, 95% CI -17.70 to -0.70). The other three studies found results varying from a small reduction (-7.7 mg/dL) to a small increase in LDL-C (0.77 mg/dL). All of which had wide confidence intervals that included no effect. Across 13 studies (25,166 participants) measuring systolic blood pressure, effect estimates ranged from a large reduction (MD -12.45 mmHg, 95% CI -15.02 to -9.88) to a small increase (MD 2.80 mmHg, 95% CI 0.30 to 5.30). We found a similar range of effect estimates for diastolic BP, ranging from -12.23 mmHg (95% CI 14.03 to -10.43) to 1.64 mmHg (95% CI -0.55 to 3.83) (11 trials, 19,716 participants). Four trials showed intervention benefits for systolic and diastolic BP with confidence intervals excluding no effect, and among these were all three of the trials evaluating self-monitoring of blood pressure with mobile phone-based telemedicine. The fourth trial included SMS and provider support (with additional varied features). Seven studies (19,185 participants) reported 'controlled' BP as an outcome, and intervention effect estimates varied from negligible effects (odds ratio (OR) 1.01, 95% CI 0.76 to 1.34) to large improvements in BP control (OR 2.41, 95% CI: 1.57 to 3.68). The three trials of clinician training or decision support combined with SMS (with additional varied features) had confidence intervals encompassing benefits and harms, with point estimates close to zero. Pooled analyses of the two trials of interventions solely delivered through SMS were indicative of little or no beneficial intervention effect on systolic BP (MD -1.55 mmHg, 95% CI -3.36 to 0.25; I2 = 0%) and small increases in controlled BP (OR 1.32, 95% CI 1.06 to 1.65; I2 = 0%). Based on four studies (12,439 participants), there was very low-certainty evidence (downgraded twice for imprecision and once for risk of bias) relating to the intervention effect on combined (fatal and non-fatal) CVD events. Two studies (2535 participants) provided low-certainty evidence for the effect of the intervention on cognitive outcomes, with little or no difference between trial arms for perceived quality of care and satisfaction with treatment. There was moderate-certainty evidence (downgraded due to risk of bias) that the interventions did not cause harm, based on six studies (8285 participants). Three studies reported no adverse events attributable to the intervention. One study reported no difference between groups in experience of adverse effects of statins, and that no participants reported intervention-related adverse events. One study stated that potential side effects were similar between groups. One study reported a similar number of deaths in each arm, but did not provide further information relating to potential adverse events.

AUTHORS' CONCLUSIONS

There is low-certainty evidence on the effects of mobile phone-delivered interventions to increase adherence to medication prescribed for the primary prevention of CVD. Trials of BP self-monitoring with mobile-phone telemedicine support reported modest benefits. One trial at low risk of bias reported modest reductions in LDL cholesterol but no benefits for BP. There is moderate-certainty evidence that these interventions do not result in harm. Further trials of these interventions are warranted.

Application of the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies in Assessing Mobile-Delivered Technologies for the Self-Management of Type 2 Diabetes Mellitus: Scoping Review

BACKGROUND

There is a growing role of digital health technologies (DHTs) in the management of chronic health conditions, specifically type 2 diabetes. It is increasingly important that health technologies meet the evidence standards for health care settings. In 2019, the National Institute for Health and Care Excellence (NICE) published the NICE Evidence Standards Framework for DHTs. This provides guidance for evaluating the effectiveness and economic value of DHTs in health care settings in the United Kingdom.

OBJECTIVE

The aim of this study is to assess whether scientific articles on DHTs for the self-management of type 2 diabetes mellitus report the evidence suggested for implementation in clinical practice, as described in the NICE Evidence Standards Framework for DHTs.

METHODS

We performed a scoping review of published articles and searched 5 databases to identify systematic reviews and primary studies of mobile device-delivered DHTs that provide self-management support for adults with type 2 diabetes mellitus. The evidence reported within articles was assessed against standards described in the NICE framework.

RESULTS

The database search yielded 715 systematic reviews, of which, 45 were relevant and together included 59 eligible primary studies. Within these, there were 39 unique technologies. Using the NICE framework, 13 technologies met best practice standards, 3 met minimum standards only, and 23 technologies did not meet minimum standards.

CONCLUSIONS

On the assessment of peer-reviewed publications, over half of the identified DHTs did not appear to meet the minimum evidence standards recommended by the NICE framework. The most common reasons for studies of DHTs not meeting these evidence standards included the absence of a comparator group, no previous justification of sample size, no measurable improvement in condition-related outcomes, and a lack of statistical data analysis. This report provides information that will enable researchers and digital health developers to address these limitations when designing, delivering, and reporting digital health technology research in the future.

Cost analysis of a remote patient monitoring programme for post-discharge patients with type 2 diabetes

INTRODUCTION

Assessing costs of an evidence-based health promotion programme is crucial to understand the economic feasibility of adopting or sustaining the programme. This study conducted a cost analysis of a remote patient monitoring (RPM) programme to enhance the post-discharge management of type 2 diabetes.

METHODS

Using retrospective data collected during RPM implementation from September 2014 to February 2018, we estimated the costs of implementing an RPM in the primary care setting. Measures included total and average annual costs, costs per participant who was enrolled or completed the programme, and costs per person-day. We further conducted sensitivity and scenario analyses to examine variations in estimated programme costs associated with varying programme efficiencies and alternative personnel compositions of the RPM team.

RESULTS

The total RPM implementation costs were estimated at US$4,374,544 with an average annual programme costs of US$1,249,870, which translated to US$3207 per participant (n = 1364) completing the three-month programme. The per person-day cost was averaged at US$24 (182,932 person-days). Sensitivity and scenario analyses results indicate that the sustainment costs were approximately US$1.6 million annually and the per-person-day costs were between US$21 and US$29 with each nurse coach on average serving a panel of 62-93 patients.

CONCLUSION

The implementation and sustainment costs of an RPM programme, estimated under various assumptions of programme efficiency and care team compositions, as exemplified in this study, will help healthcare organizations make informed decisions in budgeting for and sustaining telehealth programmes to enhance diabetes management.

Optimizing an Obesity Treatment Using the Multiphase Optimization Strategy Framework: Protocol for a Randomized Factorial Trial

Background

Effective weight loss interventions exist, yet few can be scaled up for wide dissemination. Further, none has been fully delivered via text message. We used the multiphase optimization strategy (MOST) to develop multicomponent interventions that consist only of active components, those that have been experimentally determined to impact the chosen outcome.

Objective

The goal of this study is to optimize a standalone text messaging obesity intervention, Charge, using the MOST framework to experimentally determine which text messaging components produce a meaningful contribution to weight change at 6 months.

Methods

We designed a 6-month, weight loss texting intervention based on our interactive obesity treatment approach (iOTA). Participants are randomized to one of 32 experimental conditions to test which standalone text messaging intervention components produce a meaningful contribution to weight change at 6 months.

Results

The project was funded in February 2017; enrollment began in January 2018 and data collection was completed in June 2019. Data analysis is in progress and first results are expected to be submitted for publication in 2021.

Conclusions

Full factorial trials are particularly efficient in terms of cost and logistics when leveraged for standalone digital treatments. Accordingly, MOST has the potential to promote the rapid advancement of digital health treatments. Subject to positive findings, the intervention will be low cost, immediately scalable, and ready for dissemination. This will be of great potential use to the millions of Americans with obesity and the providers who treat them.

Trial Registration

ClinicalTrials.gov NCT03254940; https://clinicaltrials.gov/ct2/show/NCT03254940

International Registered Report Identifier (IRRID)

RR1-10.2196/19506

Digital telemedicine interventions for patients with multimorbidity: a systematic review and meta-analysis

OBJECTIVE

To determine the effectiveness of digital telemedicine interventions designed to improve outcomes in patients with multimorbidity.

DESIGN

Systematic review and meta-analysis of available literature.

DATA SOURCES

MEDLINE, EMBASE, The Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and the Database of Abstracts of Reviews of Effectiveness and hand searching. The search included articles from inception to 19 April 2019 without language restrictions. The search was updated on 7 June 2020 without additional findings.

ELIGIBILITY CRITERIA

Prospective interventional studies reporting multimorbid participants employing interventions with at least one digital telemedicine component were included. Primary outcomes were patient physical or mental health outcomes, health-related quality of life scores and the utilisation of health services.

RESULTS

Out of 5865 studies initially identified, 7 articles, reporting on 6 studies were retained (total of 699 participants). Four of these studies reported interventions including integration with usual care, two studies had interventions with no links to usual patient care. Follow-up periods lasted between 2 and 6 months. Among the studies with links to usual care, the primary outcomes were systolic blood pressure (SBP) (three studies), haemoglobin A1c (HbA1c) (three studies), total cholesterol (two studies) and self-perceived health status (one study). The evidence ranged from very low to moderate certainty. Meta-analysis showed a moderate decrease in SBP (8 mm Hg (95% CI 4.6 to 11.4)), a small to moderate decrease in HbA1c (0.46 mg/dL (95% CI 0.25 to 0.67)) and moderate decrease in total cholesterol (cholesterol 16.5 mg/dL (95% CI 8.1 to 25.0)) in the intervention groups. There was an absence of evidence for self-perceived health status. Among the studies with no links to usual care, time to hospitalisation (median time to hospitalisation 113.4 days intervention and 104.7 days control group, absolute difference 12.7 days) and the Minnesota Living with Heart Failure Questionnaire (intervention group 35.2 score points, control group 23.9 points, absolute difference 11.3, 95% CI 5.5 to 17.1) showed small reductions. The Personal Health Questionnaire (PHQ-8) showed no evidence of improvement (intervention 7.6 points, control 8.6 points, difference 1.0 points, 95% CI -22.9% to 11.9%).

CONCLUSION

Digital telemedicine interventions provided moderate evidence of improvements in measures of disease control but little evidence and no demonstrated benefits on health status. Further research is needed with clear descriptions of conditions, interventions and outcomes based on patients' and healthcare providers' preferences.

PROSPERO REGISTRATION NUMBER

CRD42019134872.

Development and Operation of a Video Teleconsultation System Using Integrated Medical Equipment Gateway: a National Project for Workers in Underserved Areas

Worker health centers and health zones provide occupational healthcare services to workers in underserved areas of industrial health. Health zones cannot counsel workers on occupational disease prevention; worker health center personnel have to provide such services through in-person visits. Video teleconsultation can increase the accessibility of high-quality services to workers who visit health zones and improve professional personnel’s efficiency. This study aimed to develop a system and an infrastructure that could facilitate video teleconsultation services between worker health centers and health zones, and analyze the services’ operation status. A video teleconsultation process based on the role of local and remote institutions was designed. Based on the designed services, a web system supporting teleconsultation and an integrated gateway guaranteeing the interface with medical equipment in the web environment was developed. After analyzing the working environment, an infrastructure consisting of networks, video equipment, medical equipment, and servers necessary for teleconsultation was designed. Statistical results from the developed system and a satisfaction survey conducted by the Korea Occupational Safety and Health Agency were used to analyze the video teleconsultation services’ operation status. A system, gateway, and hardware infrastructure within 21 worker health centers and 21 health zones has been operating this service since January 1, 2018. Over two years, the total number of teleconsultation service users was 4979, and the total number of questionnaire respondents was 1270. The total number of service activities was 6388 and total satisfaction was rated as 4.58 (± 0.59) out of 5. In this study, video teleconsultation services were evaluated as being very satisfactory. In particular, service accessibility and local medical personnel service were rated highly, demonstrating that the developed system and infrastructure were well designed according to the goals of the project.

Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background

Mobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence.

Objective

A systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes.

Methods

We followed the Cochrane Collaboration guidelines and searched MEDLINE, Cochrane Library, EMBASE, and CINAHL Plus for relevant studies published between January 2007 and January 2019. Primary outcomes included changes in hemoglobin A_1c (HbA_1c) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis.

Results

A total of 27 trials were identified and analyzed. For primary outcomes, the use of mobile app-assisted self-care interventions was associated with significant reductions in HbA_1c levels (standardized mean difference [SMD] −0.44, 95% CI −0.59 to −0.29; P<.001), SBP (SMD −0.17, 95% CI −0.31 to −0.03, P=.02), and DBP (SMD −0.17, 95% CI −0.30 to −0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found.

Conclusions

Mobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient–care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination.

How Behavior Change Strategies are Used to Design Digital Interventions to Improve Medication Adherence and Blood Pressure Among Patients With Hypertension: Systematic Review

BACKGROUND

Information on how behavior change strategies have been used to design digital interventions (DIs) to improve blood pressure (BP) control or medication adherence (MA) for patients with hypertension is currently limited.

OBJECTIVE

Hypertension is a major modifiable risk factor for cardiovascular diseases and can be controlled with appropriate medication. Many interventions that target MA to improve BP are increasingly using modern digital technologies. This systematic review was conducted to discover how DIs have been designed to improve MA and BP control among patients with hypertension in the recent 10 years. Results were mapped into a matrix of change objectives using the Intervention Mapping framework to guide future development of technologies to improve MA and BP control.

METHODS

We included all the studies regarding DI development to improve MA or BP control for patients with hypertension published in PubMed from 2008 to 2018. All the DI components were mapped into a matrix of change objectives using the Intervention Mapping technique by eliciting the key determinant factors (from patient and health care team and system levels) and targeted patient behaviors.

RESULTS

The analysis included 54 eligible studies. The determinants were considered at two levels: patient and health care team and system. The most commonly described determinants at the patient level were lack of education, lack of self-awareness, lack of self-efficacy, and forgetfulness. Clinical inertia and an inadequate health workforce were the most commonly targeted determinants at the health care team and system level. Taking medication, interactive patient-provider communication, self-measurement, and lifestyle management were the most cited patient behaviors at both levels. Most of the DIs did not include support from peers or family members, despite its reported effectiveness and the rate of social media penetration.

CONCLUSIONS

This review highlights the need to design a multifaceted DI that can be personalized according to patient behavior(s) that need to be changed to overcome the key determinant(s) of low adherence to medication or uncontrolled BP among patients with hypertension, considering different levels including patient and healthcare team and system involvement.

The Association of Health Literacy with High-Quality Home Blood Pressure Monitoring for Hypertensive Patients in Outpatient Settings

Worldwide hypertension (HT) guidelines recommend use of home blood pressure monitoring (HBPM) in patients with persistent suboptimal blood pressure (BP) readings. It is not clear how patients with limited health literacy could perform HBPM to assist BP control. This study aimed at finding the association between HBPM and patients from lower socioeconomic classes, particularly on the effect of health literacy or educational level. Three electronic databases (MEDLINE, EMBASE, and PubMed) were searched for primary studies with keywords including educational level, health literacy, numeracy, home blood pressure monitoring, accuracy, and quality. The PRISMA guideline was followed. The quality of the literature was assessed by the Cochrane tool and modified Newcastle-Ottawa Scale. Nineteen interventional studies and 29 cross-sectional studies were included. Different populations used different cutoffs to report patients' educational level, whereas health literacy was rarely measured. Three studies used psychometric validated tools to assess health literacy. The quality of HBPM could be assessed by the completion of the procedures' checklist or the number of HBPM readings recorded. The association between subjects' health literacy or educational level and the quality of HBPM was variable. The interventional studies showed that increasing professional-patient contact time could improve patients' knowledge, efficacy, and quality of HBPM. Conclusion. Patients' educational level and literacy were not the limiting factors to acquire high-quality HBPM. High-quality HBPM could be achieved by the structured educational intervention. The quality and amount of evidence on this topic are limited. Therefore, further studies are warranted.

Mobile Application Interventions and Weight Loss in Type 2 Diabetes: A Meta-Analysis

OBJECTIVE

This meta-analysis aimed to assess the effect of mobile application (app) interventions on weight loss in patients with type 2 diabetes.

METHODS

Electronic databases were searched for randomized controlled trials examining the use of mobile app interventions with outcomes on weight loss evaluated by body weight or other measures such as BMI or waist circumference. A random-effects model was applied to obtain weight mean differences and 95% CIs.

RESULTS

Fourteen studies enrolling 2,129 patients with type 2 diabetes were included. Mobile app interventions could significantly reduce body weight (weight mean difference, -0.84 kg; 95% CI: -1.51 to -0.17 kg) and lower waist circumference (-1.35 cm; 95% CI: -2.16 to -0.55 cm) but may not decrease BMI (-0.08 kg/m² ; 95% CI: -0.41 to 0.25 kg/m² ). The reductions appeared to be more pronounced in patients with obesity or among studies using mobile app interventions combined with other behavior components. However, weight loss was not moderated by the functionalities of the mobile apps (all P_interaction  > 0.05) or by the intervention duration (all P > 0.87).

CONCLUSIONS

Mobile app interventions lead to weight loss in patients with type 2 diabetes and are worth recommending for weight loss promotion.

Efficacy, acceptability and feasibility of daily text-messaging in promoting glycaemic control and other clinical outcomes in a low-resource setting of South Africa: A randomised controlled trial

South Africa is confronted with a high burden of diabetes, the majority of which are poorly controlled. The use of mHealth, specifically text messaging for fostering health, is evolving and studies on its efficacy, the majority of which were conducted in developed countries, have documented mixed findings. There is no such study done amongst patients living with diabetes in the resource-poor settings of South Africa. The aim of this study is to determine the efficacy, acceptability and feasibility of text-messaging in improving glycaemic control and other clinical outcomes among individuals living with diabetes in low-resource settings in Eastern Cape, South Africa. The study adopted a multi-centre, two-arm, parallel, randomised-controlled trial design. The study was conducted amongst patients with an uncontrolled glycaemic status. Participants were randomly assigned to the intervention (n = 108) and the control arm (n = 108). Participants in the intervention arm received daily educational text messages on diabetes for six months. Data was collected at baseline and six months post-intervention. Blood glucose, blood pressure and anthropometric measurements followed standard procedure. Mixed-model analysis was used to assess the impact of the text messages on blood glucose while linear regression was used to assess its effect on other clinical outcomes such as weight, body mass index, systolic and diastolic blood pressure. The mean age of the participants was 60.64 (SD± 11.58) years. The majority of the participants had a secondary level of education (95.3%) and earned 104.80 to 991.42 USD per month (67.7%). Both arms of the study showed improvement in their blood glucose levels, but the intervention did not have any significant effect, the mean adjusted change in blood glucose was 0.26 (-0.81 to 1.32), p = 0.634. Also, the intervention did not have any significant effect on weight, body mass index, systolic and diastolic blood pressure. Almost all participants (90.74%) were pleased with the intervention and felt it was helpful. Of those who participated in the intervention, 91% completed the follow-up after 6 months. Unidirectional text-messaging was acceptable and feasible amongst adults living with diabetes in this setting. However, its efficacy in improving glycaemic status and other clinical outcomes remains doubtful. Trial Registration: Pan African Clinical Trial Registry PACTR201810599931422.

Features, outcomes, and challenges in mobile health interventions for patients living with chronic diseases: A review of systematic reviews

BACKGROUND

Mobile health (mHealth) technology has the potential to play a key role in improving the health of patients with chronic non-communicable diseases.

OBJECTIVES

We present a review of systematic reviews of mHealth in chronic disease management, by showing the features and outcomes of mHealth interventions, along with associated challenges in this rapidly growing field.

METHODS

We searched the bibliographic databases of PubMed, Scopus, and Cochrane to identify systematic reviews of mHealth interventions with advanced technical capabilities (e.g., Internet-linked apps, interoperation with sensors, communication with clinical platforms, etc.) utilized in randomized clinical trials. The original studies included the reviews were synthesized according to their intervention features, the targeted diseases, the primary outcome, the number of participants and their average age, as well as the total follow-up duration.

RESULTS

We identified 5 reviews respecting our inclusion and exclusion criteria, which examined 30 mHealth interventions. The highest percentage of the interventions targeted patients with diabetes (n = 19, 63%), followed by patients with psychotic disorders (n = 7, 23%), lung diseases (n = 3, 10%), and cardiovascular disease (n = 1, 3%). 14 studies showed effective results: 9 in diabetes management, 2 in lung function, and 3 in mental health. Significantly positive outcomes were reported in 8 interventions (n = 8, 47%) from 17 studies assessing glucose concentration, one intervention assessing physical activity, 2 interventions (n = 2, 67%) from 3 studies assessing lung function parameters, and 3 mental health interventions assessing N-back performance, medication adherence, and number of hospitalizations. Divergent features were adopted in 14 interventions with significantly positive outcomes, such as personalized goal setting (n = 10, 71%), motivational feedback (n = 5, 36%), and alerts for health professionals (n = 3, 21%). The most significant found challenges in the development and evaluation of mHealth interventions include the design of studies with high quality, the construction of robust interventions in combination with health professional inputs, and the identification of tools and methods to improve patient adherence.

CONCLUSIONS

This review found mixed evidence regarding the health benefits of mHealth interventions for patients living with chronic diseases. Further rigorous studies are needed to assess the outcomes of personalized mHealth interventions toward the optimal management of chronic diseases.

The effects of mobile health interventions on lipid profiles among patients with metabolic syndrome and related disorders: A systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

The current systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to summarize the effect of mobile health (m-health) interventions on lipid profiles among patients with metabolic syndrome and related disorders.

METHODS

Cochrane Library, EMBASE, PubMed, and Web of Science databases were searched to indentify the relevant randomized clinical trials published up April 30^th, 2018. Two reviewers examined study eligibility, extracted data, and assessed risk of bias of included clinical trials, individually. Heterogeneity was measured using I-square (I²) statistic and Cochran's Q test. Data were pooled the standardized mean difference (SMD) effect size by the random-effect model.

RESULTS

18 trials of 1681 citations were identified to be appropriate for the current meta-analysis. Findings random-effects model indicated that m-health interventions significantly decreased total- (SMD -0.54; 95% CI, -1.05, -0.03) and LDL-cholesterol levels (SMD -0.66; 95% CI, -1.18, -0.15). M-health interventions had no significant effect on triglycerides (SMD -0.14; 95% CI, -0.56, 0.28) and HDL-cholesterol levels (SMD -0.35; 95% CI, -0.81, 0.11).

CONCLUSION

Overall, the current meta-analysis demonstrated that m-health interventions resulted in an improvement in total- and LDL-cholesterol, but did not affect triglycerides and HDL-cholesterol levels.

Effect of Health Information Technologies on Cardiovascular Risk Factors among Patients with Diabetes

PURPOSE OF REVIEW

To identify a common effect of health information technologies (HIT) on the management of cardiovascular disease (CVD) risk factors among people with type 2 diabetes (T2D) across randomized control trials (RCT).

RECENT FINDINGS

CVD is the most frequent cause of morbidity and mortality among patients with diabetes. HIT are effective in reducing HbA1c; however, their effect on cardiovascular risk factor management for patients with T2D has not been evaluated. We identified 21 eligible studies (23 estimates) with measurement of SBP, 20 (22 estimates) of DBP, 14 (17 estimates) of HDL, 14 (17 estimates) of LDL, 15 (18 estimates) of triglycerides, and 10 (12 estimates) of weight across databases. We found significant reductions in SBP, DBP, LDL, and TG, and a significant improvement in HDL associated with HIT. As adjuvants to standard diabetic treatment, HIT can be effective tools for improving CVD risk factors among patients with T2D, especially in those whose CVD risk factors are not at goal.

[Tools to improve efficiency in the clinical management of hypertensive patients]

OBJECTIVE

To create a tool to evaluate the efficiency of the clinical management of hypertensive patients in Primary Care.

MATERIAL AND METHODS

A web-based questionnaire was designed for Primary Care centres to self-evaluate the management of hypertension in five specific areas: information systems, diagnostic and analytical tests, organisational aspects, use of resources, and continuous training programmes for patients and healthcare professionals. A committee of experts previously defined these questions and their ideal responses or "control", based on the scientific literature or, if there were no published references, by consensus of the committee. A descriptive analysis was performed on the data, and an adherence score was created that ranged from 0 (no adherence) to 1 (total adherence).

RESULTS

A total of 35 Primary Care centres entered their data into the website for the clinical management of hypertensive patients. The highest adherence to the ideal algorithm was observed in the area "Diagnostic and analytical tests" (0.69±0.10), and the lowest in "Continuous training programmes for patients and professionals" (0.42±0.21).

CONCLUSIONS

The efficiency of clinical management in hypertensive patients can be analysed using the website tool created for this purpose. Its use allows an internal audit to detect the areas that need improvement, and also serves to make comparative evaluations in the different areas of management over time.

Effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life and clinical outcomes in patients with type 2 diabetes: A systematic review and meta-analysis

OBJECTIVES

To review the evidence and determine the effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life, glycated hemoglobin, body mass index (BMI), and blood pressure (BP) levels of adults with type 2 diabetes mellitus .

METHODS

A systematic search of five databases (PubMed, Embase, Cochrane, CINAHL and Scopus) was conducted. Studies published in English from January 2007 to January 2018 were considered. Only randomized controlled trials (RCTs) of smartphone-based self-management interventions for patients with type 2 diabetes mellitus that reported any of the study outcomes were included. Two reviewers independently screened the studies, extracted data and assessed the quality of the studies. Meta-analyses were conducted for the different study outcomes.

RESULTS

A total of 26 articles, consisting of 22 studies with 2645 participants, were included in the review. The results from meta-analysis on the studies revealed that as compared to control group, participants received smartphone-based self-management intervention had better self-efficacy with large effect size of 0.98 (P <  0.001), self-care activities with effect size of 0.90 (P <  0.001), health related quality of life with effect size of 0.26 (p=0.01), and lower glycated hemoglobin (pooled MD=-0.55; p<0.001). Subgroup analyses were also conducted for self-efficacy as significant heterogeneity was present among the studies. The effects on BMI and BP were not statistically significant.

CONCLUSIONS

Smartphone-based self-management interventions appear to have beneficial effects on self-efficacy, self-care activities and health-relevant outcomes for patients with type 2 diabetes mellitus. However, more research with good study design is needed to evaluate the effectiveness of smartphone-based self-care interventions for T2DM.

The Efficacy of Mobile Phone Apps for Lifestyle Modification in Diabetes: Systematic Review and Meta-Analysis

Background

Diabetes and related complications are estimated to cost US $727 billion worldwide annually. Type 1 diabetes, type 2 diabetes, and gestational diabetes are three subtypes of diabetes that share the same behavioral risk factors. Efforts in lifestyle modification, such as daily physical activity and healthy diets, can reduce the risk of prediabetes, improve the health levels of people with diabetes, and prevent complications. Lifestyle modification is commonly performed in a face-to-face interaction, which can prove costly. Mobile phone apps provide a more accessible platform for lifestyle modification in diabetes.

Objective

This review aimed to summarize and synthesize the clinical evidence of the efficacy of mobile phone apps for lifestyle modification in different subtypes of diabetes.

Methods

In June 2018, we conducted a literature search in 5 databases (Cochrane Central Register of Controlled Trials, MEDLINE, Embase, CINAHL, and PsycINFO). We evaluated the studies that passed screening using The Cochrane Collaboration’s risk of bias tool. We conducted a meta-analysis for each subtype on the mean difference (between intervention and control groups) at the posttreatment glycated hemoglobin (HbA_1c) level. Where possible, we analyzed subgroups for short-term (3-6 months) and long-term (9-12 months) studies. Heterogeneity was assessed using the I² statistic.

Results

We identified total of 2669 articles through database searching. After the screening, we included 26 articles (23 studies) in the systematic review, of which 18 studies (5 type 1 diabetes, 11 type 2 diabetes, and 2 prediabetes studies) were eligible for meta-analysis. For type 1 diabetes, the overall effect on HbA_1c was statistically insignificant (P=.46) with acceptable heterogeneity (I²=39%) in the short-term subgroup (4 studies) and significant heterogeneity between the short-term and long-term subgroups (I²=64%). Regarding type 2 diabetes, the overall effect on HbA_1c was statistically significant (P<.01) in both subgroups, and when the 2 subgroups were combined, there was virtually no heterogeneity within and between the subgroups (I² range 0%-2%). The effect remained statistically significant (P<.01) after adjusting for publication bias using the trim and fill method. For the prediabetes condition, the overall effect on HbA_1c was statistically insignificant (P=.67) with a large heterogeneity (I²=65%) between the 2 studies.

Conclusions

There is strong evidence for the efficacy of mobile phone apps for lifestyle modification in type 2 diabetes. The evidence is inconclusive for the other diabetes subtypes.

Tailored mobile text messaging interventions targeting type 2 diabetes self-management: A systematic review and a meta-analysis

OBJECTIVES

This study aimed to identify, assess and summarize available scientific evidence on tailored text messaging interventions focused on type 2 diabetes self-management. The systematic review concentrated on message design and delivery features, and tailoring strategies. The meta-analysis assessed the moderators of the effectiveness of tailored text messaging interventions.

METHODS

A comprehensive search strategy included major electronic databases, key journal searches and reference list searching for related studies. PRISMA and Cochrane Collaboration's guidelines and recommended tools for data extraction, quality appraisal and data analysis were followed. Data were extracted on participant characteristics (age, gender, ethnicity), and interventional and methodological characteristics (study design, study setting, study length, choice of modality, comparison group, message type, format, content, use of interactivity, message frequency, message timing, message delivery, tailoring strategies and theory use). Outcome measures included diet, physical activity, medication adherence and glycated hemoglobin data (HbA1C). Where possible, a random effects meta-analysis was performed to pool data on the effectiveness of the tailored text messaging interventions and moderator variables.

RESULTS

The search returned 13 eligible trials for the systematic review and 11 eligible trials for the meta-analysis. The majority of the studies were randomized controlled trials, conducted in high-income settings, used multi-modalities, and mostly delivered informative, educational messages through an automated message delivery system. Tailored text messaging interventions produced a substantial effect (g = 0.54, 95% CI = 0.08-0.99, p < 0.001) on HbA1C values for a total of 949 patients. Subgroup analyses revealed the importance of some moderators such as message delivery (Q B = 18.72, df = 1, p = 0.001), message direction (Q B = 5.26, df = 1, p = 0.022), message frequency (Q B = 18.72, df = 1, p = 0.000) and using multi-modalities (Q B = 6.18, df = 1, p = 0.013).

CONCLUSIONS

Tailored mobile text messaging interventions can improve glycemic control in type 2 diabetes patients. However, more rigorous interventions with larger samples and longer follow-ups are required to confirm these findings and explore the effects of tailored text messaging on other self-management outcomes.

The effectiveness of electronic health interventions on blood pressure control, self-care behavioural outcomes and psychosocial well-being in patients with hypertension: A systematic review and meta-analysis

OBJECTIVES

Hypertension is a global health issue. Electronic health (eHealth) is a potential alternative for managing hypertension and modifying hypertension-related self-care set of behaviour. This review aims to identify the delivery mode and strategies used by current eHealth interventions and examine the effectiveness of eHealth on blood pressure control, self-care behavioural outcomes and psychosocial well-being.

DESIGN

Systematic review and meta-analysis.

DATA SOURCE

Ten English databases (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Embase, Joanna Briggs Institute EBP Database, MEDLINE, CINAHL Plus, PsycINFO, SCOPUS, Web of Science and INSPEC) and two Chinese databases (China Journal Net and WanFang Data) were searched from January 2000 to November 2017.

REVIEW METHODS

This review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement. Two reviewers independently selected potential articles and extracted the details of each eligible article. The Randomized Controlled Trial Checklist of Joanna Briggs Institute was used to assess the methodological quality of the included articles. Meta-analysis was conducted using Review Manager 5.3 for at least two studies reporting the same outcome. Otherwise, narrative synthesis was performed.

RESULTS

Fifteen articles from fourteen studies satisfied the inclusion criteria. The pooled result of 13 studies reported that eHealth intervention significantly affected the reduction of systolic blood pressure (mean difference [MD]: -5.96 mmHg, 95% confidence interval [CI]: -9.21 to -2.70, p < .001) and diastolic blood pressure (MD: -3.35 mmHg, 95% CI: -6.36 to -0.35, p < .05). eHealth interventions significantly decreased the proportion of patients with inadequate blood pressure control (risk ratio: 0.69, 95% CI: 0.57-0.84, p < .001) and their body weight (MD: -1.08 kg, 95% CI: -2.04 to -0.13, p < .05). Regarding self-care behavioural outcomes, the pooled results show that eHealth interventions significantly reduced the sodium intake.

CONCLUSIONS

This study reported that eHealth interventions positively affect blood pressure control and thus could be a promising alternative in the management of hypertension. However, their effectiveness on self-care behavioural change and psychosocial well-being is insufficient. Therefore, additional eHealth interventions with rigorous experimental design on hypertension self-care are needed to provide a robust evidence for a wide population and to address the increasing health care needs of patients with hypertension.

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.

Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature

Objectives

Limited data are available on the correlation of mHealth features and statistically significant outcomes. We sought to identify and analyze: types and categories of features; frequency and number of features; and relationship of statistically significant outcomes by type, frequency, and number of features.

Materials and Methods

This search included primary articles focused on app-based interventions in managing chronic respiratory diseases, diabetes, and hypertension. The initial search yielded 3622 studies with 70 studies meeting the inclusion criteria. We used thematic analysis to identify 9 features within the studies.

Results

Employing existing terminology, we classified the 9 features as passive or interactive. Passive features included: 1) one-way communication; 2) mobile diary; 3) Bluetooth technology; and 4) reminders. Interactive features included: 1) interactive prompts; 2) upload of biometric measurements; 3) action treatment plan/personalized health goals; 4) 2-way communication; and 5) clinical decision support system.

Discussion

Each feature was included in only one-third of the studies with a mean of 2.6 mHealth features per study. Studies with statistically significant outcomes used a higher combination of passive and interactive features (69%). In contrast, studies without statistically significant outcomes exclusively used a higher frequency of passive features (46%). Inclusion of behavior change features (ie, plan/goals and mobile diary) were correlated with a higher incident of statistically significant outcomes (100%, 77%).

Conclusion

This exploration is the first step in identifying how types and categories of features impact outcomes. While the findings are inconclusive due to lack of homogeneity, this provides a foundation for future feature analysis.

Comparative effectiveness of telemonitoring versus usual care for type 2 diabetes: A systematic review and meta-analysis

AIMS

This study evaluated clinical effectiveness of telemonitoring on the management of patients with type 2 diabetes.

METHODS

We searched Ovid-Medline, Ovid-EMBASE, and the Cochrane Library to identify randomized controlled trials that compared telemonitoring and usual care in patients with type 2 diabetes.

RESULTS

Thirty-eight studies (6855 patients) were included. Telemonitoring was associated with a significant decrease in glycated haemoglobin levels compared to usual care (weighted mean difference -0.42%, 95% confidence interval -0.56 to -0.27) but there was evidence of heterogeneity (I²= 96.9%). Telemonitoring was associated with a significant glycated haemoglobin reduction when biological data were transmitted through a web-based device weekly, when voice feedback was performed daily or immediately and when patients were provided with counselling. Telemonitoring also reduced glycated haemoglobin level in studies that monitored patients' medication adherence, provided counselling, education and alarm message. The rate of achieving glycated haemoglobin levels of < 7% was 1.8 times higher in the telemonitoring group compared to the usual care group (risk ratio 1.83, 95% confidence interval 1.35 to 2.47, I²= 0%). There was also significant reduction in systolic blood pressure (weighted mean difference -1.33 mm Hg) and body mass index (weighted mean difference -0.25 kg/m²), but the clinical relevance of these results can be questioned. The data available on patient satisfaction, quality of life, medication adherence, prescription changes, stress and depression were limited.

CONCLUSIONS

Telemonitoring interventions may be a better option than usual care in improving glycated haemoglobin control of patients with type 2 diabetes. Further studies should assess clinical benefit according to specific delivery modes of the intervention and patient-reported outcomes.

An Analysis of Diabetes Mobile Applications Features Compared to AADE7™: Addressing Self-Management Behaviors in People With Diabetes

BACKGROUND

Diabetes self-management (DSM) applications (apps) have been designed to improve knowledge of diabetes and self-management behaviors. However, few studies have systematically examined if diabetes apps followed the American Association of Diabetes Educators (AADE) Self-Care Behaviors^™ guidelines. The purpose of this study was to compare the features of current DSM apps to the AADE7™ guidelines.

METHODS

In two major app stores (iTunes and Google Play), we used three search terms "diabetes," "blood sugar," and "glucose" to capture a wide range of diabetes apps. Apps were excluded based on five exclusion criteria. A multidisciplinary team analyzed and classified the features of each app based on the AADE7^™. We conducted interviews with six diabetes physicians and educators for their opinions on the distribution of the features of DSM apps.

RESULTS

Out of 1050 apps retrieved, 173 apps were identified as eligible during November 2015 and 137 apps during December 2017. We found an unbalanced DSM app development trend based on AADE7^™ guidelines. Many apps were designed to support the behaviors of Healthy Eating (77%), Monitoring (76%), Taking Medication (58%), and Being Active (45%). On the other hand, few apps explored the behaviors of Problem Solving (31%), Healthy Coping (10%), and Reducing Risks (5%). From interviews, we identified the main reasons why only a few apps support the features related to Problem Solving, Healthy Coping, and Reducing Risks.

CONCLUSIONS

Future diabetes apps should attempt to incorporate features under evidence-based guidelines such as AADE7^™ to better support the self-management behavior changes of people with diabetes.

Self-Management of Chronic Diseases Among Older Korean Adults: An mHealth Training, Protocol, and Feasibility Study

Background

Most training programs for self-management of chronic diseases in Korea currently involve face-to-face interactions primarily in a health care setting. Therefore, older Koreans living in the community continue to seek other training opportunities for the management of chronic diseases. This has led to the development of new training methods, such as mobile health (mHealth) care, which are valuable in community centers and homes.

Objective

This feasibility study (1) developed an mHealth training protocol to empower community-dwelling elderly individuals to manage their chronic diseases; (2) examined the feasibility of delivering this mHealth training protocol to elderly individuals through mobile tablets and applications (apps); and (3) discussed the contextual and methodological challenges associated with the development of this protocol.

Methods

The mHealth training protocol was developed based on the eHealth Enhanced Chronic Care Model and comprised of four phases. Phase 1 included standardized technology (mobile tablets) training using guidebooks, demonstrations, and guided practice. Phase 2 included provision of standardized information about disease management that was obtained from governmental and professional health care organizations. Phase 3 included provision of training on the use of high-quality mHealth apps that were selected based on individual diagnoses. Phase 4 included encouraging the patients to practice using self-selected mHealth apps based on their individual needs. Quantitative descriptive statistics and qualitative content analyses of user evaluations were used to assess the feasibility and user acceptance of this protocol.

Results

Of the 27 older adults included in this study, 25 completed all 4 weeks of the mHealth training. The attrition rate was 7% (2/27), and the reasons included time conflicts, emotional distress, and/or family discouragement. The men required little or no training for Phase 1, and in comparison with men, women seemed to depend more on the mHealth trainers in Phase 3. Gender, level of education, and previous experience of using smartphones were associated with the speed of learning, level of confidence, and overall competence.

Conclusions

A tailored and personalized approach is required to develop mHealth training protocols for older adults. Self-management of chronic diseases via mHealth training requires careful consideration of the complex nature of human behavior, emotional responses, and familial influences. Therefore, integration of a theoretical, clinical, and technical approach is necessary for the successful development and implementation of an mHealth training program that targets older adults with chronic diseases in a community setting.

Mobile phone-based interventions for improving adherence to medication prescribed for the primary prevention of cardiovascular disease in adults

BACKGROUND

Cardiovascular disease (CVD) is a major cause of disability and mortality globally. Premature fatal and non-fatal CVD is considered to be largely preventable through the control of risk factors via lifestyle modifications and preventive medication. Lipid-lowering and antihypertensive drug therapies for primary prevention are cost-effective in reducing CVD morbidity and mortality among high-risk people and are recommended by international guidelines. However, adherence to medication prescribed for the prevention of CVD can be poor. Approximately 9% of CVD cases in the EU are attributed to poor adherence to vascular medications. Low-cost, scalable interventions to improve adherence to medications for the primary prevention of CVD have potential to reduce morbidity, mortality and healthcare costs associated with CVD.

OBJECTIVES

To establish the effectiveness of interventions delivered by mobile phone to improve adherence to medication prescribed for the primary prevention of CVD in adults.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and two other databases on 21 June 2017 and two clinical trial registries on 14 July 2017. We searched reference lists of relevant papers. We applied no language or date restrictions.

SELECTION CRITERIA

We included randomised controlled trials investigating interventions delivered wholly or partly by mobile phones to improve adherence to cardiovascular medications prescribed for the primary prevention of CVD. We only included trials with a minimum of one-year follow-up in order that the outcome measures related to longer-term, sustained medication adherence behaviours and outcomes. Eligible comparators were usual care or control groups receiving no mobile phone-delivered component of the intervention.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane. We contacted study authors for disaggregated data when trials included a subset of eligible participants.

MAIN RESULTS

We included four trials with 2429 randomised participants. Participants were recruited from community-based primary care or outpatient clinics in high-income (Canada, Spain) and upper- to middle-income countries (South Africa, China). The interventions received varied widely; one trial evaluated an intervention focused on blood pressure medication adherence delivered solely through short messaging service (SMS), and one intervention involved blood pressure monitoring combined with feedback delivered via smartphone. Two trials involved interventions which targeted a combination of lifestyle modifications, alongside CVD medication adherence, one of which was delivered through text messages, written information pamphlets and self-completion cards for participants, and the other through a multi-component intervention comprising of text messages, a computerised CVD risk evaluation and face-to-face counselling. Due to heterogeneity in the nature and delivery of the interventions, we did not conduct a meta-analysis, and therefore reported results narratively.We judged the body of evidence for the effect of mobile phone-based interventions on objective outcomes (blood pressure and cholesterol) of low quality due to all included trials being at high risk of bias, and inconsistency in outcome effects. Of two trials targeting medication adherence alongside other lifestyle modifications, one reported a small beneficial intervention effect in reducing low-density lipoprotein cholesterol (mean difference (MD) -9.2 mg/dL, 95% confidence interval (CI) -17.70 to -0.70; 304 participants), and the other found no benefit (MD 0.77 mg/dL, 95% CI -4.64 to 6.18; 589 participants). One trial (1372 participants) of a text messaging-based intervention targeting adherence showed a small reduction in systolic blood pressure (SBP) for the intervention arm which delivered information-only text messages (MD -2.2 mmHg, 95% CI -4.4 to -0.04), but uncertain evidence of benefit for the second intervention arm that provided additional interactivity (MD -1.6 mmHg, 95% CI -3.7 to 0.5). One study examined the effect of blood pressure monitoring combined with smartphone messaging, and reported moderate intervention benefits on SBP and diastolic blood pressure (DBP) (SBP: MD -7.10 mmHg, 95% CI -11.61 to -2.59; DBP: -3.90 mmHg, 95% CI -6.45 to -1.35; 105 participants). There was mixed evidence from trials targeting medication adherence alongside lifestyle advice using multi-component interventions. One trial found large benefits for SBP and DBP (SBP: MD -12.45 mmHg, 95% CI -15.02 to -9.88; DBP: MD -12.23 mmHg, 95% CI -14.03 to -10.43; 589 participants), whereas the other trial demonstrated no beneficial effects on SBP or DBP (SBP: MD 0.83 mmHg, 95% CI -2.67 to 4.33; DBP: MD 1.64 mmHg, 95% CI -0.55 to 3.83; 304 participants).Two trials reported on adverse events and provided low-quality evidence that the interventions did not cause harm. One study provided low-quality evidence that there was no intervention effect on reported satisfaction with treatment.Two trials were conducted in high-income countries, and two in upper- to middle-income countries. The interventions evaluated employed between three and 16 behaviour change techniques according to coding using Michie's taxonomic method. Two trials evaluated interventions that involved potential users in their development.

AUTHORS' CONCLUSIONS

There is low-quality evidence relating to the effects of mobile phone-delivered interventions to increase adherence to medication prescribed for the primary prevention of CVD; some trials reported small benefits while others found no effect. There is low-quality evidence that these interventions do not result in harm. On the basis of this review, there is currently uncertainty around the effectiveness of these interventions. We identified six ongoing trials being conducted in a range of contexts including low-income settings with potential to generate more precise estimates of the effect of primary prevention medication adherence interventions delivered by mobile phone.