Protocol for the mWellcare trial: a multicentre, cluster randomised, 12-month, controlled trial to compare the effectiveness of mWellcare, an mHealth system for an integrated management of patients with hypertension and diabetes, versus enhanced usual care in India

Primary-level and community worker interventions for the prevention of mental disorders and the promotion of well-being in low- and middle-income countries

BACKGROUND

There is a significant research gap in the field of universal, selective, and indicated prevention interventions for mental health promotion and the prevention of mental disorders. Barriers to closing the research gap include scarcity of skilled human resources, large inequities in resource distribution and utilization, and stigma.

OBJECTIVES

To assess the effectiveness of delivery by primary workers of interventions for the promotion of mental health and universal prevention, and for the selective and indicated prevention of mental disorders or symptoms of mental illness in low- and middle-income countries (LMICs). To examine the impact of intervention delivery by primary workers on resource use and costs.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, CINAHL, Global Index Medicus, PsycInfo, WHO ICTRP, and ClinicalTrials.gov from inception to 29 November 2021.

SELECTION CRITERIA

Randomized controlled trials (RCTs) of primary-level and/or community health worker interventions for promoting mental health and/or preventing mental disorders versus any control conditions in adults and children in LMICs.

DATA COLLECTION AND ANALYSIS

Standardized mean differences (SMD) or mean differences (MD) were used for continuous outcomes, and risk ratios (RR) for dichotomous data, using a random-effects model. We analyzed data at 0 to 1, 1 to 6, and 7 to 24 months post-intervention. For SMDs, 0.20 to 0.49 represented small, 0.50 to 0.79 moderate, and ≥ 0.80 large clinical effects. We evaluated the risk of bias (RoB) using Cochrane RoB2.

MAIN RESULTS

Description of studies We identified 113 studies with 32,992 participants (97 RCTs, 19,570 participants in meta-analyses) for inclusion. Nineteen RCTs were conducted in low-income countries, 27 in low-middle-income countries, 2 in middle-income countries, 58 in upper-middle-income countries and 7 in mixed settings. Eighty-three RCTs included adults and 30 RCTs included children. Cadres of primary-level workers employed primary care health workers (38 studies), community workers (71 studies), both (2 studies), and not reported (2 studies). Interventions were universal prevention/promotion in 22 studies, selective in 36, and indicated prevention in 55 RCTs. Risk of bias The most common concerns over risk of bias were performance bias, attrition bias, and reporting bias. Intervention effects 'Probably', 'may', or 'uncertain' indicates 'moderate-', 'low-', or 'very low-'certainty evidence. *Certainty of the evidence (using GRADE) was assessed at 0 to 1 month post-intervention as specified in the review protocol. In the abstract, we did not report results for outcomes for which evidence was missing or very uncertain. Adults Promotion/universal prevention, compared to usual care: - probably slightly reduced anxiety symptoms (MD -0.14, 95% confidence interval (CI) -0.27 to -0.01; 1 trial, 158 participants) - may slightly reduce distress/PTSD symptoms (SMD -0.24, 95% CI -0.41 to -0.08; 4 trials, 722 participants) Selective prevention, compared to usual care: - probably slightly reduced depressive symptoms (SMD -0.69, 95% CI -1.08 to -0.30; 4 trials, 223 participants) Indicated prevention, compared to usual care: - may reduce adverse events (1 trial, 547 participants) - probably slightly reduced functional impairment (SMD -0.12, 95% CI -0.39 to -0.15; 4 trials, 663 participants) Children Promotion/universal prevention, compared to usual care: - may improve the quality of life (SMD -0.25, 95% CI -0.39 to -0.11; 2 trials, 803 participants) - may reduce adverse events (1 trial, 694 participants) - may slightly reduce depressive symptoms (MD -3.04, 95% CI -6 to -0.08; 1 trial, 160 participants) - may slightly reduce anxiety symptoms (MD -2.27, 95% CI -3.13 to -1.41; 1 trial, 183 participants) Selective prevention, compared to usual care: - probably slightly reduced depressive symptoms (SMD 0, 95% CI -0.16 to -0.15; 2 trials, 638 participants) - may slightly reduce anxiety symptoms (MD 4.50, 95% CI -12.05 to 21.05; 1 trial, 28 participants) - probably slightly reduced distress/PTSD symptoms (MD -2.14, 95% CI -3.77 to -0.51; 1 trial, 159 participants) Indicated prevention, compared to usual care: - decreased slightly functional impairment (SMD -0.29, 95% CI -0.47 to -0.10; 2 trials, 448 participants) - decreased slightly depressive symptoms (SMD -0.18, 95% CI -0.32 to -0.04; 4 trials, 771 participants) - may slightly reduce distress/PTSD symptoms (SMD 0.24, 95% CI -1.28 to 1.76; 2 trials, 448 participants).

AUTHORS' CONCLUSIONS

The evidence indicated that prevention interventions delivered through primary workers - a form of task-shifting - may improve mental health outcomes. Certainty in the evidence was influenced by the risk of bias and by substantial levels of heterogeneity. A supportive network of infrastructure and research would enhance and reinforce this delivery modality across LMICs.

Improving care for hypertension and diabetes in india by addition of clinical decision support system and task shifting in the national NCD program: I-TREC model of care

Background

The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology “CDSS” and a strategy “Task-shifting” within the Government of India’s (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program’s impact to address the growing burden of hypertension and diabetes in India.

Methods

We developed a model of care “I-TREC” entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system.

Discussion

The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse.

Conclusion

Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level.

Trial registration

CTRI/2020/01/022723.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08025-y.

Scaling up the primary health integrated care project for chronic conditions in Kenya: study protocol for an implementation research project

INTRODUCTION

Amid the rising number of people with non-communicable diseases (NCDs), Kenya has invested in strengthening primary care and in efforts to expand existing service delivery platforms to integrate NCD care. One such approach is the AMPATH (Academic Model Providing Access to Healthcare) model in western Kenya, which provides the platform for the Primary Health Integrated Care Project for Chronic Conditions (PIC4C), launched in 2018 to further strengthen primary care services for the prevention and control of hypertension, diabetes, breast and cervical cancer. This study seeks to understand how well PIC4C delivers on its intended aims and to inform and support scale up of the PIC4C model for integrated care for people with NCDs in Kenya.

METHODS AND ANALYSIS

The study is guided by a conceptual framework on implementing, sustaining and spreading innovation in health service delivery. We use a multimethod design combining qualitative and quantitative approaches, involving: (1) in-depth interviews with health workers and decision-makers to explore experiences of delivering PIC4C; (2) a cross-sectional survey of patients with diabetes or hypertension and in-depth interviews to understand how well PIC4C meets patients' needs; (3) a cohort study with an interrupted time series analysis to evaluate the degree to which PIC4C leads to health benefits such as improved management of hypertension or diabetes; and (4) a cohort study of households to examine the extent to which the national hospital insurance chronic care package provides financial risk protection to people with hypertension or diabetes within PIC4C.

ETHICS AND DISSEMINATION

The study has received approvals from Moi University Institutional Research and Ethics Committee (FAN:0003586) and the London School of Hygiene & Tropical Medicine (17940). Workshops with key stakeholders at local, county, national and international levels will ensure early and wide dissemination of our findings to inform scale up of this model of care. We will also publish findings in peer-reviewed journals.

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.

Self-management of diabetes and associated comorbidities in rural and remote communities: a scoping review

Chronic health conditions are more prevalent in rural and remote areas than in metropolitan areas; living in rural and remote areas may present particular barriers to the self-management of chronic conditions like diabetes and comorbidities. The aims of this review were to: (1) synthesise evidence examining the self-management of diabetes and comorbidities among adults living in rural and remote communities; and (2) describe barriers and enablers underpinning self-management reported in studies that met our inclusion criteria. A systematic search of English language papers was undertaken in PsycINFO, Medline Complete, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete, EMBASE and the Cochrane Database of Systematic Reviews, searching for literature indexed from the beginning of the database until 6 March 2020. Essential key concepts were diabetes, comorbidities, self-management and rural or remote. Twelve studies met the inclusion criteria. Six of these reported interventions to promote self-management for adults with diabetes in rural and remote communities and described comorbidities. These interventions had mixed results; only three demonstrated improvements in clinical outcomes or health behaviours. All three of these interventions specifically targeted adults living with diabetes and comorbidities in rural and remote areas; two used the same telehealth approach. Barriers to self-management included costs, transport problems and limited health service access. Interventions should take account of the specific challenges of managing both diabetes and comorbidities; telehealth may address some of the barriers associated with living in rural and remote areas.

Bibliometric Analysis and Methodological Review of Mobile Health Services and Applications in India

PURPOSE

The purpose of this research is to analyze the literature published on mobile health (mHealth) in the Indian context. It also reviews the most important research works and presents various methodologies adopted by the researchers in this domain.

DESIGN/METHODOLOGY/APPROACH

The SciVerse SCOPUS database was used for extracting the literature on mobile health. The study used articles published between January 2008 to 28^th June 2019. The keyword used is 'mHealth' and journal articles with studies or interventions carried out in India were selected for bibliometric analysis and methodological review.

FINDINGS

For the keyword search, a total of 7,874 documents have been extracted, of which only 158 have been considered for the analysis. There is an exponential increase in the number of publications from the year 2015 to 2019. The keywords used for representing their articles have been grouped as mobile health devices, gender and age groups, system and software, health and disease condition, management, evidence-based practices (outcome), methods, and importance of the study. The journal PLOS One (87) has the highest number of citations, followed by The Lancet (63). The bibliometric analysis of the literature revealed seven clusters classified as individual's individual's mobile health applications adoption characteristics, need for mobile health and its governance, mobile phone application with the internet of things based framework for healthcare monitoring, mobile health for primary healthcare systems, authentication and security protocol for mobile healthcare, development and experimentation of mobile health application, and development and mobile health for adherence support intervention.

ORIGINALITY/VALUE

The study contributes in analyzing the bibliometrics and provides a methodological review for the journal articles published on mobile health. Previous articles considered systematic analysis of the bibliometric for mHealth, and mobile technology but less adequately discussed specifically towards Indian context which this study has embraced.

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSION

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

Clinical Decision Support for the Diagnosis and Management of Adult and Pediatric Hypertension

PURPOSE OF REVIEW

To review literature from 2016 to 2019 on clinical decision support (CDS) for diagnosis and management of hypertension in children and adults.

RECENT FINDINGS

Ten studies described hypertension CDS systems. Novel advances included the integration of patient-collected blood pressure data, automated information retrieval and management support, and use of CDS in low-resource/developing-world settings and in pediatrics. Findings suggest that CDS increases hypertension detection/control, yet many children and adults with hypertension remain undetected or undercontrolled. CDS challenges included poor usability (from lack of health record integration, excessive data entry requests, and wireless connectivity challenges) and lack of clinician trust in blood pressure measures. Hypertension CDS has improved but not closed gaps in the detection and control of hypertension in children and adults. The studies reviewed indicate that the usability of CDS and the system where CDS is deployed (e.g., commitment to high-quality blood pressure measurement/infrastructure) may impact CDS's ability to increase hypertension detection and control.

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.

Mobile health applications for the management of primary hypertension: A multicenter, randomized, controlled trial

BACKGROUND

Hypertension is 1 of the major global public health challenges, which means that patients with hypertension need more measures to control their blood pressure. Currently, smart phones and applications are developing rapidly, and mobile health applications are used to manage hypertension, but evidences related to effectiveness are limited.

OBJECTIVE

The purpose was to assess the impact of m-Health apps on blood pressure control, medication adherence.

METHODS

480 participants were randomly assigned to the intervention and control groups. The intervention group used the "Yan Fu" app to manage their blood pressure, and the control group did not use any m-Health apps. The outcomes were changes in blood pressure, the percentage of participants with their blood pressure under control and medication adherence.

RESULTS

At the end of the study, the baseline characteristics between the 2 groups had no statistically differences (P > .05). Participants in the 2 groups all had lower systolic blood pressure and diastolic blood pressure than they did at baseline, and the intervention group demonstrated a significantly greater systolic blood pressure and diastolic blood pressure reduction than the control group (P < .05). Additionally, the percentage of participants with controlled blood pressure was higher in the intervention group (P < .05). The medication adherence of the intervention group was much higher than that of the control group (P < .05).

CONCLUSION

M-Health apps are effective for hypertension management, it can favor the medication adherence and blood pressure control. Perhaps m-Health apps can be promoted in the blood pressure control.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry under the number ChiCTR-IOR-17012069.

The Potential of mHealth Applications in Improving Resistant Hypertension Self-Assessment, Treatment and Control

PURPOSE OF REVIEW

To review the evidence supporting the use of mobile health (mHealth) apps to improve resistant hypertension self-assessment, treatment and control.

RECENT FINDINGS

mHealth apps have been used to directly measure blood pressure (BP) levels, either using the oscillometric method with automated inflatable cuffs or using pulse wave signals detected by smartphone technology without the need for cuffs. These app-based BP monitors tend to over or underestimate BP levels when compared to a gold standard aneroid sphygmomanometer. However, the differences in BP measurements are within the acceptable range of 5 mmHg pre-defined by the European Society of Hypertension International Protocol Revision 2010. mHealth apps are also used as tools to support physicians in improving hypertension treatment. App-based clinical decision support systems are innovative solutions, in which patient information is entered in the app and management algorithms provide recommendations for hypertension treatment. The use of these apps has been shown to be feasible and easily integrated into the workflow of healthcare professionals, and, therefore particularly useful in resource-limited settings. In addition, apps can be used to improve hypertension control by facilitating regular BP monitoring, communication between patients and health professionals, and patient education; as well as by reinforcing behaviours through reminders, including medication-taking and appointment reminders. Several studies provided evidence supporting the use of apps for hypertension control. Although some of the results are promising, there is still limited evidence on the benefits of using such mHealth tools, as these studies are relatively small and with a short-term duration. Recent research has shown that mHealth apps can be beneficial in terms of improving hypertension self-assessment, treatment and control, being especially useful to help differentiate and manage true and pseudo-resistant hypertension. However, future research, including large-scale randomised clinical trials with user-centred design, is crucial to further evaluate the potential scalability and effectiveness of such mHealth apps in the resistant hypertension context.

The role of medical smartphone apps in clinical decision-support: A literature review

INTRODUCTION

The now ubiquitous smartphone has huge potential to assist clinical decision-making across the globe. However, the rapid pace of digitalisation contrasts starkly with the slower rate of medical research and publication. This review explores the evidence base that exists to validate and evaluate the use of medical decision-support apps. The resultant findings will inform appropriate and pragmatic evaluation strategies for future clinical app developers and provide a scientific and cultural context for research priorities in this field.

METHOD

Medline, Embase and Cochrane databases were searched for clinical trials concerning decision support and smart phones from 2007 (introduction of first smartphone iPhone) until January 2019.

RESULTS

Following exclusions, 48 trials and one Cochrane review were included for final analysis. Whilst diagnostic accuracy studies are plentiful, clinical trials are scarce. App research methodology was further interrogated according to setting and decision-support modality: e.g. camera-based, guideline-based, predictive models. Description of app development pathways and regulation were highly varied. Global health emerged as an early adopter of decision-support apps and this field is leading implementation and evaluation.

CONCLUSION

Clinical decision-support apps have considerable potential to enhance access to care and quality of care, but the medical community must rise to the challenge of modernising its approach if it is truly committed to capitalising on the opportunities of digitalisation.

Cardiovascular Diseases in India Compared With the United States

This review describes trends in the burden of cardiovascular diseases (CVDs) and risk factors in India compared with the United States; provides potential explanations for these differences; and describes strategies to improve cardiovascular health behaviors, systems, and policies in India. The prevalence of CVD in India has risen over the past 2 decades due to population growth, aging, and a stable age-adjusted CVD mortality rate. Over the same time period, the United States has experienced an overall decline in age-adjusted CVD mortality, although the trend has begun to plateau. These improvements in CVD mortality in the United States are largely due to favorable population-level risk factor trends, specifically with regard to tobacco use, cholesterol, and blood pressure, although improvements in secondary prevention and acute care have also contributed. To realize similar gains in reducing premature death and disability from CVD, India needs to implement population-level policies while strengthening and integrating its local, regional, and national health systems. Achieving universal health coverage that includes financial risk protection should remain a goal to help all Indians realize their right to health.

India and the United Kingdom-What big data health research can do for a country

INTRODUCTION

Big data and growth in telecommunications have increased the enormous promise of an informatics approach to health care. India and the United Kingdom are two countries facing these challenges of implementing learning health systems and big data health research.

ANALYSIS

At present, these opportunities are more likely to be exploited in the private sector or in public-private partnerships (eg, Public Health Foundation of India [PHFI]) than public sector ventures alone. In both India and the United Kingdom, the importance of health informatics (HIs), a relatively new discipline, is being recognised and there are national initiatives in academic and health sectors to fill gaps in big data health research. The challenges are in many ways greater in India but outweighed by three potential benefits in health-related scientific research: (a) increased productivity; (b) a learning health system with better use of data and better health outcomes; and (c) to fill workforce gaps in both research and practice.

CONCLUSIONS

Despite several system-level obstacles, in India, big data research in health care can improve the status quo, whether in terms of patient outcomes or scientific discovery. Collaboration between India and the United Kingdom in HI can result in mutual benefits to academic and health care delivery organisations in both countries and can serve as examples to other countries embracing the promises and the pitfalls of health care research in the digital era.

Integrated health care systems in Asia: an urgent necessity

A rapidly aging population along with the increasing burden of patients with chronic conditions in Asia requires efficient health systems with integrated care. Although some efforts to integrate primary care and hospital care in Asia are underway, overall care delivery remains fragmented and diverse, eg, in terms of medical electronic record sharing and availability, patient registries, and empowerment of primary health care providers to handle chronic illnesses. The primary care sector requires more robust and effective initiatives targeted at specific diseases, particularly chronic conditions such as diabetes, hypertension, depression, and dementia. This can be achieved through integrated care - a health care model of collaborative care provision. For successful implementation of integrated care policy, key stakeholders need a thorough understanding of the high-risk patient population and relevant resources to tackle the imminent population demographic shift due to the extremely rapid rate of increase in the aging population in Asia.

Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial

BACKGROUND

The burden of noncommunicable diseases and their risk factors has rapidly increased worldwide, including in India. Innovative management strategies with electronic decision support and task sharing have been assessed for hypertension, diabetes mellitus, and depression individually, but an integrated package for multiple chronic condition management in primary care has not been evaluated.

METHODS

In a prospective, multicenter, open-label, cluster-randomized controlled trial involving 40 community health centers, using hypertension and diabetes mellitus as entry points, we evaluated the effectiveness of mWellcare, an mHealth system consisting of electronic health record storage and an electronic decision support for the integrated management of 5 chronic conditions (hypertension, diabetes mellitus, current tobacco and alcohol use, and depression) versus enhanced usual care among patients with hypertension and diabetes mellitus in India. At trial end (12-month follow-up), using intention-to-treat analysis, we examined the mean difference between arms in change in systolic blood pressure and glycated hemoglobin as primary outcomes and fasting blood glucose, total cholesterol, predicted 10-year risk of cardiovascular disease, depression score, and proportions reporting tobacco and alcohol use as secondary outcomes. Mixed-effects regression models were used to account for clustering and other confounding variables.

RESULTS

Among 3698 enrolled participants across 40 clusters (mean age, 55.1 years; SD, 11 years; 55.2% men), 3324 completed the trial. There was no evidence of difference between the 2 arms for systolic blood pressure (∆=-0.98; 95% CI, -4.64 to 2.67) and glycated hemoglobin (∆=0.11; 95% CI, -0.24 to 0.45) even after adjustment of several key variables (adjusted differences for systolic blood pressure: - 0.31 [95% CI, -3.91 to 3.29]; for glycated hemoglobin: 0.08 [95% CI, -0.27 to 0.44]). The mean withingroup changes in systolic blood pressure in mWellcare and enhanced usual care were -13.65 mmHg versus -12.66 mmHg, respectively, and for glycated hemoglobin were -0.48% and -0.58%, respectively. Similarly, there were no differences in the changes between the 2 groups for tobacco and alcohol use or other secondary outcomes.

CONCLUSIONS

We did not find an incremental benefit of mWellcare over enhanced usual care in the management of the chronic conditions studied.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT02480062.

The Emerging Role of Mobile-Health Applications in the Management of Hypertension

PURPOSE OF REVIEW

Mobile-health technology, frequently referred to as m-health, encompasses smartphone, tablet, or personal computer use in the management of chronic disease. There has been a rise in the number of commercially available smartphone applications and website-based platforms which claim to help patients manage hypertension. Very little research has been performed confirming whether or not use of these applications results in improved blood pressure (BP) outcomes. In this paper, we review existing literature on m-health systems and how m-health can affect hypertension management.

RECENT FINDINGS

M-health systems help patients manage hypertension in the following ways: (1) setting alarms and reminders for patients to take their medications, (2) linking patients' BP reports to their electronic medical record for their physicians to review, (3) providing feedback to patients about their BP trends, and (4) functioning as point-of-care BP sensors. M-health applications with alarms and reminders can increase medication compliance while applications that share ambulatory BP data with patients' physicians can foster improved patient-physician dialog. However, the most influential tool for achieving positive BP outcomes appears to be patient-directed feedback about BP trends. A large number of commercially available m-health applications may facilitate self-management of hypertension by enhancing medication adherence, maintaining a log of blood pressure measurements, and facilitating physician-patient communication. A small number of applications function as BP sensors, thereby transforming the smartphone into a medical device. Such BP sensors often generate unreliable recordings. Patients must be cautioned regarding the use of smartphones for BP measurement at least until these applications have been more extensively validated.

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.