Development of mWellcare: an mHealth intervention for integrated management of hypertension and diabetes in low-resource settings

How Is Telehealth Currently Being Utilized to Help in Hypertension Management within Primary Healthcare Settings? A Scoping Review

Telehealth has improved patient access to healthcare services and has been shown to have a positive impact in various healthcare settings. In any case, little is understood regarding the utilization of telehealth in hypertension management in primary healthcare (PHC) settings. This study aimed to identify and classify information about the types of interventions and types of telehealth technology in hypertension management in primary healthcare. A scoping review based on PRISMA-ScR was used in this study. We searched for articles in four databases: Pubmed, Scopus, Science Direct, and Embase in English. The selected articles were published in 2013-2023. The data were extracted, categorized, and analyzed using thematic analysis. There were 1142 articles identified and 42 articles included in this study. Regarding the proportions of studies showing varying trends in the last ten years, most studies came from the United States (US) (23.8%), were conducted in urban locations (33.3%), and had a quantitative study approach (69%). Telehealth interventions in hypertension management are dominated by telemonitoring followed by teleconsultation. Asynchronous telehealth is becoming the most widely used technology in managing hypertension in primary care settings. Telehealth in primary care hypertension management involves the use of telecommunications technology to monitor and manage blood pressure and provide medical advice and counselling remotely.

Adherence to Lifestyle Modification Practices and Its Associated Factors Among Hypertensive Patients in Bahir Dar City Hospitals, North West Ethiopia

Background

Globally, hypertension affects 1.4 billion adults, accounting for 31% of the world population. The prevention and control of hypertension is not addressed only by pharmacological management. Even though the prevalence of uncontrolled hypertension and its complications is increasing every day, Adherence to lifestyle modification practice among diagnosed hypertensive individuals is low for a number of reasons. The study aims to assess adherence to lifestyle modification practices and associated factors among hypertensive patients at Bahir Dar city hospitals, in North West Ethiopia.

Methods

An institutional-based cross-sectional study design was conducted at Bahir Dar city from October 30 to November 30, 2022. A stratified sampling technique was used. For the data quality pre-test was done, the questionnaire was checked for completion, the assumption of binary logistic regression (VIF 1.8 and no outlier), and model fit using the Hosmer and Lemeshow's test was checked. Binary logistic and multivariate logistic regression were used to find significant variables after the data were entered into EpiInfo and analyzed using SPSS version 23.

Results

The overall adherence to lifestyle modification practices was about 32.4%. From the independent factors, above secondary educational status (AOR = 0.201 95% CI (0.081-0.499)), good knowledge (AOR = 3.323 95% CI (1.79-6.168)), good self-efficacy (AOR = 3.553 95% CI (1.91-6.613)), good social support (AOR = 8.339 95% CI (4.251-16.357)), and good patient-physician relationship (AOR = 2.424 95% CI (1.309-4.490)) were statistically significant predictors of adherence to lifestyle modification practices.

Conclusion

Only one-third of the participants had adhered to the recommended lifestyle modifications. Educational status, knowledge, self-efficacy, social support, and patient-physician relationships were significant factors. Healthcare organizations should develop programs to raise hypertension patients' awareness and degree of self-efficacy that aid in adherence to advised lifestyle changes.

A Situational Analysis of the Impact of the COVID-19 Pandemic on Digital Health Research Initiatives in South Asia

The objective of this paper was to evaluate and compare the quantity and sustainability of digital health initiatives in the South Asia region before and during the COVID-19 pandemic. The study used a two-step methodology of (a) descriptive analysis of digital health research articles published from 2016 to 2021 from South Asia in terms of stratification of research articles based on diseases and conditions they were developed, geography, and tasks wherein the initiative was applied and (b) a simple and replicable tool developed by authors to assess the sustainability of digital health initiatives using experimental or observational study designs. The results of the descriptive analysis highlight the following: (a) there was a 40% increase in the number of studies reported in 2020 when compared to 2019; (b) the three most common areas wherein substantive digital health research has been focused are health systems strengthening, ophthalmic disorders, and COVID-19; and (c) remote consultation, health information delivery, and clinical decision support systems are the top three commonly developed tools. We developed and estimated the inter-rater operability of the sustainability assessment tool ascertained with a Kappa value of 0.806 (±0.088). We conclude that the COVID-19 pandemic has had a positive impact on digital health research with an improvement in the number of digital health initiatives and an improvement in the sustainability score of studies published during the COVID-19 pandemic.

GDM care re-imagined: Maternal and neonatal outcomes following a major model of care change for gestational diabetes mellitus at a large metropolitan hospital

BACKGROUND

The rapidly rising prevalence of gestational diabetes mellitus (GDM) poses major challenges to the efficient, timely and sustainable provision of diabetes care.

AIM

To assess whether the implementation of a novel, digital model of care would provide improved efficiency without compromising clinical outcomes in a cohort of women with GDM.

METHODS

A digital model of care was developed, implemented and evaluated using a prospective pre-post study design in 2020-21 at a quaternary centre. We introduced six culturally and linguistically tailored educational videos, home delivery of equipment and prescriptions, and a smartphone app-to-clinician portal for glycaemic review and management. Outcomes were prospectively recorded by an electronic medical record. Associations between model of care and maternal and neonatal characteristics and birth outcomes were examined for all women and separately by treatment received (diet, metformin, insulin).

RESULTS

Comparing pre-implementation (n = 598) and post-implementation (n = 337) groups, maternal (onset, mode of birth) and neonatal (birthweight, large for gestational age (LGA), nursery admission) clinical outcomes confirmed that the novel model of care was similar to standard, traditional care. Minor birthweight variation was noted when separated by treatment type (diet, metformin, insulin).

CONCLUSION

This pragmatic service redesign demonstrates reassuring clinical outcomes in a culturally diverse GDM cohort. Despite the lack of randomisation, this intervention has potential generalisability for GDM care and important key learnings for service redesign in the digital era.

DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes

Type 2 diabetes (T2D) is a large disease burden worldwide and represents an increasing and complex challenge for all societies. For the individual, T2D is a complex, multi-dimensional, and long-term challenge to manage, and it is challenging to establish and maintain good communication between the patient and healthcare professionals. This article presents DiaFocus, which is a mobile health sensing application for long-term ambulatory management of T2D. DiaFocus supports an adaptive collection of physiological, behavioral, and contextual data in combination with ecological assessments of psycho-social factors. This data is used for improving patient-clinician communication during consultations. DiaFocus is built using a generic data collection framework for mobile and wearable sensing and is highly extensible and customizable. We deployed DiaFocus in a 6-week feasibility study involving 12 patients with T2D. The patients found the DiaFocus approach and system useful and usable for diabetes management. Most patients would use such a system, if available as part of their treatment. Analysis of the collected data shows that mobile sensing is feasible for longitudinal ambulatory assessment of T2D, and helped identify the most appropriate target users being early diagnosed and technically literate T2D patients.

Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation

Background

Clinical decision support (CDS) is increasingly used to facilitate chronic disease care. Despite increased availability of electronic health records and the ongoing development of new CDS technologies, uptake of CDS into routine clinical settings is inconsistent. This qualitative systematic review seeks to synthesise healthcare provider experiences of CDS—exploring the barriers and enablers to implementing, using, evaluating, and sustaining chronic disease CDS systems.

Methods

A search was conducted in Medline, CINAHL, APA PsychInfo, EconLit, and Web of Science from 2011 to 2021. Primary research studies incorporating qualitative findings were included if they targeted healthcare providers and studied a relevant chronic disease CDS intervention. Relevant CDS interventions were electronic health record-based and addressed one or more of the following chronic diseases: cardiovascular disease, diabetes, chronic kidney disease, hypertension, and hypercholesterolaemia. Qualitative findings were synthesised using a meta-aggregative approach.

Results

Thirty-three primary research articles were included in this qualitative systematic review. Meta-aggregation of qualitative data revealed 177 findings and 29 categories, which were aggregated into 8 synthesised findings. The synthesised findings related to clinical context, user, external context, and technical factors affecting CDS uptake. Key barriers to uptake included CDS systems that were simplistic, had limited clinical applicability in multimorbidity, and integrated poorly into existing workflows. Enablers to successful CDS interventions included perceived usefulness in providing relevant clinical knowledge and structured chronic disease care; user confidence gained through training and post training follow-up; external contexts comprised of strong clinical champions, allocated personnel, and technical support; and CDS technical features that are both highly functional, and attractive.

Conclusion

This systematic review explored healthcare provider experiences, focussing on barriers and enablers to CDS use for chronic diseases. The results provide an evidence-base for designing, implementing, and sustaining future CDS systems. Based on the findings from this review, we highlight actionable steps for practice and future research.

Trial registration

PROSPERO CRD42020203716

Supplementary Information

The online version contains supplementary material available at 10.1186/s43058-022-00326-x.

Adopting mobile health applications by nurses: a scoping review

Background

The concept of mobile health has attracted considerable attention across the globe, as it provides both healthcare professionals and patients with a distinct means of information and resources.

Aim

This study was conducted with the aim of utilising mobile health (mHealth) applications by nurses and presenting a scenario of how and why they are utilised.

Methods

This study was a scoping review. Data collection was carried out by searching the related keywords in Google Scholar, Scopus, Cochrane, EMBASE, Ovid, and PubMed databases from January 2000 to March 2019.

Results

Regarding the reasons for using mobile applications by nurses, five objectives were identified, including learning and knowledge enhancement, treatment and improvement of the patient care process, diagnostic process, data and patient management, and health promotion. Effective factors in the nurses' use of mobile applications were categorised into eight themes: ease of use, usefulness, security and confidentiality, feasibility and functionality, design and use-interface, effectiveness, infrastructure, versatility, and social norms.

Conclusions

Mobile health applications have considerable potential in enhancing nurses' professional activities. This study contributes to both nursing and health policy by providing a scenario of how and why nurses use mobile health applications.

Innovative mobile-health led participatory approach to comprehensive screening and treatment of diabetes (IMPACT diabetes): rationale, design, and baseline characteristics

Background

India has 66 million people with diabetes, of which a large proportion do not receive adequate care. The primary health centres can serve as platforms for early detection of diabetes and continuum of care.

Objectives

This project evaluates a community-level technology-enabled system-level intervention based around the community health workers and primary-care physicians. We hypothesize that incorporation of a mobile clinical decision support system, with other process-level changes will improve identification and management of individuals with diabetes in primary care settings.

Methods

A cluster-randomized trial in sixteen villages/peri-urban areas in Andhra Pradesh and Haryana will test the feasibility and preliminary effectiveness of this intervention. The effectiveness of the extended care intervention will be evaluated by the difference in HbA1c (glycosylated hemoglobin) measured at baseline and end-line between the two study arms. Qualitative interviews of physicians, ASHA, and community members will ascertain the intervention acceptability and feasibility.

Results

A total of 1785 adults (females: 53.2%; median age: 50 years) were screened. ASHAs achieved 100% completeness of data for anthropometric, blood-pressure, and blood-glucose measures. At baseline, 63% of the participants were overweight/obese, 27.8% had elevated blood pressure, 20.3% were at high-risk for cardiovascular disease (CVD), and 21.3% had elevated blood glucose. Half of the individuals with diabetes were newly diagnosed.

Conclusion

Technology enabled transfer of simple clinical procedures from physicians to nonphysician health workers can support the provision of healthcare in under-served communities. Community health workers can successfully screen and refer patients with diabetes and/or CVD to physicians in primary healthcare system.

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.

Digital Health Interventions for Depression and Anxiety Among People with Chronic Conditions: Scoping Review (Preprint)

Background

Chronic conditions are characterized by their long duration (≥1 year), need for ongoing medical attention, and limitations in activities of daily living. These can often co-occur with depression and anxiety as common and detrimental comorbidities among the growing population living with chronic conditions. Digital health interventions (DHIs) hold promise in overcoming barriers to accessing mental health support for these individuals; however, the design and implementation of DHIs for depression and anxiety in people with chronic conditions are yet to be explored.

Objective

This study aimed to explore what is known in the literature regarding DHIs for the prevention, detection, or treatment of depression and anxiety among people with chronic conditions.

Methods

A scoping review of the literature was conducted using the Arksey and O’Malley framework. Searches of the literature published in 5 databases between 1990 and 2019 were conducted in April 2019 and updated in March 2021. To be included, studies must have described a DHI tested with, or designed for, the prevention, detection, or treatment of depression or anxiety in people with common chronic conditions (arthritis, asthma, diabetes mellitus, heart disease, chronic obstructive pulmonary disease, cancer, stroke, and Alzheimer disease or dementia). Studies were independently screened by 2 reviewers against the inclusion and exclusion criteria. Both quantitative and qualitative data were extracted, charted, and synthesized to provide a descriptive summary of the trends and considerations for future research.

Results

Database searches yielded 11,422 articles across the initial and updated searches, 53 (0.46%) of which were included in this review. DHIs predominantly sought to provide treatment (44/53, 83%), followed by detection (5/53, 9%) and prevention (4/53, 8%). Most DHIs were focused on depression (36/53, 68%), guided (32/53, 60%), tailored to chronic physical conditions (19/53, 36%), and delivered through web-based platforms (20/53, 38%). Only 2 studies described the implementation of a DHI.

Conclusions

As a growing research area, DHIs offer the potential to address the gap in care for depression and anxiety among people with chronic conditions; however, their implementation in standard care is scarce. Although stepped care has been identified as a promising model to implement efficacious DHIs, few studies have investigated the use of DHIs for depression and anxiety among chronic conditions using such models. In developing stepped care, we outlined DHI tailoring, guidance, and intensity as key considerations that require further research.

Achieving the potential of mHealth in medicine requires challenging the ethos of care delivery

Mobile Health (mHealth) interventions have received a mix of praise and excitement, as well as caution and even opposition over recent decades. While the rapid adoption of mHealth solutions due to the COVID-19 pandemic has weakened resistance to integrating these digital approaches into practice and generated renewed interest, the increased reliance on mHealth signals a need for optimizing development and implementation. Despite an historically innovation-resistant medical ethos, mHealth is becoming a normalized supplement to clinical practice, highlighting increased demand. Reaching the full potential of mHealth requires new thinking and investment. The current challenge to broaden mHealth adoption and to ensure equity in access may be overcoming a “design purgatory,” where innovation fails to connect to practice. We recommend leveraging the opportunity presented by the COVID-19 pandemic to disrupt routine practice and with a new focus on theory-driven replicability of mHealth tools and strategies aimed at medical education and professional organizations.

Determinant factors in adopting mobile health application in healthcare by nurses

Background

Mobile applications are among effective learning tools and have a significant role in transferring information and knowledge to nurses. The current study was carried to identify the factors affecting nurses’ use of practical health related mobile applications in education and patient interaction based on the combined Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI).

Method

The study is a descriptive-analytical study with a cross-sectional method. The research population includes nurses working at Tabriz University of Medical Sciences hospitals, 150 of which were selected as the research sample using simple and available sampling. The data collection instrument was a questionnaire, the validity and reliability of which were confirmed (α = 0.9). Data analysis was carried out using a correlation test and regression analysis by applying SPSS _v16 software.

Results

The findings show that perceived usefulness and perceived ease of use have a direct and significant effect on the rate of using mobile applications by nurses (P value ≤ 0.01), [(β = 0.52), (β = 0.40)]. Other findings indicate that relative advantage, compatibility, trialability and observability, have a direct and significant effect on nurses’ use of mobile applications, while complicatedness does not have a significant effect.

Conclusion

The current study identifies the effective factors in nurses’ use of health-related mobile applications based on an integrated model of TAM and DOI. Designers of mobile applications should consider these factors in designing and developing programs so that mobile applications can successfully fulfill their purpose in healthcare.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01784-y.

Remote Monitoring Systems for Patients With Chronic Diseases in Primary Health Care: Systematic Review

Background

The digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID-19 pandemic. Health remote monitoring systems (HRMS) present various advantages such as the reduction in patient load at hospitals and health centers. Patients that would most benefit from HRMS are those with chronic diseases, older adults, and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection.

Objective

This paper aimed to perform a systematic review of the literature of HRMS in primary health care (PHC) settings, identifying the current status of the digitalization of health processes, remote data acquisition, and interactions between health care personnel and patients.

Methods

A systematic literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify articles that explored interventions with HRMS in patients with chronic diseases in the PHC setting.

Results

The literature review yielded 123 publications, 18 of which met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (9/26, 35%) and cardiovascular diseases (7/26, 27%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integration of information into already existing systems in the PHC infrastructure and in changing working processes of PHC professionals (83%).

Conclusions

The PHC context integrates multidisciplinary teams and patients with often complex, chronic pathologies. Despite the theoretical framework, objective identification of problems, and involvement of stakeholders in the design and implementation processes, these interventions mostly fail to scale up. Despite the inherent limitations of conducting a systematic literature review, the small number of studies in the PHC context is a relevant limitation. This study aimed to demonstrate the importance of matching technological development to the working PHC processes in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management, so that information with clinical value is not lost along the way.

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review

BACKGROUND

A medication-related Clinical Decision Support System (CDSS) is an application that analyzes patient data to provide assistance in medication-related care processes. Despite its potential to improve the clinical decision-making process, evidence shows that clinicians do not always use CDSSs in such a way that their potential can be fully realized. This systematic literature review provides an overview of frequently-reported barriers and facilitators for acceptance of medication-related CDSS.

MATERIALS AND METHODS

Search terms and MeSH headings were developed in collaboration with a librarian, and database searches were conducted in Medline, Scopus, Embase and Web of Science Conference Proceedings. After screening 5404 records and 140 full papers, 63 articles were included in this review. Quality assessment was performed for all 63 included articles. The identified barriers and facilitators are categorized within the Human, Organization, Technology fit (HOT-fit) model.

RESULTS

A total of 327 barriers and 291 facilitators were identified. Results show that factors most often reported were related to (a lack of) usefulness and relevance of information, and ease of use and efficiency of the system.

DISCUSSION

This review provides a valuable insight into a broad range of barriers and facilitators for using a medication-related CDSS as perceived by clinicians. The results can be used as a stepping stone in future studies developing medication-related CDSSs.

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.

The Integrated Tracking, Referral, and Electronic Decision Support, and Care Coordination (I-TREC) program: scalable strategies for the management of hypertension and diabetes within the government healthcare system of India

Background

Hypertension and diabetes are among the most common and deadly chronic conditions globally. In India, most adults with these conditions remain undiagnosed, untreated, or poorly treated and uncontrolled. Innovative and scalable approaches to deliver proven-effective strategies for medical and lifestyle management of these conditions are needed.

Methods

The overall goal of this implementation science study is to evaluate the Integrated Tracking, Referral, Electronic decision support, and Care coordination (I-TREC) program. I-TREC leverages information technology (IT) to manage hypertension and diabetes in adults aged ≥30 years across the hierarchy of Indian public healthcare facilities. The I-TREC program combines multiple evidence-based interventions: an electronic case record form (eCRF) to consolidate and track patient information and referrals across the publicly-funded healthcare system; an electronic clinical decision support system (CDSS) to assist clinicians to provide tailored guideline-based care to patients; a revised workflow to ensure coordinated care within and across facilities; and enhanced training for physicians and nurses regarding non-communicable disease (NCD) medical content and lifestyle management. The program will be implemented and evaluated in a predominantly rural district of Punjab, India. The evaluation will employ a quasi-experimental design with mixed methods data collection. Evaluation indicators assess changes in the continuum of care for hypertension and diabetes and are grounded in the Reach, Effectiveness, Adoption Implementation, and Maintenance (RE-AIM) framework. Data will be triangulated from multiple sources, including community surveys, health facility assessments, stakeholder interviews, and patient-level data from the I-TREC program’s electronic database.

Discussion

I-TREC consolidates previously proven strategies for improved management of hypertension and diabetes at single-levels of the healthcare system into a scalable model for coordinated care delivery across all levels of the healthcare system hierarchy. Findings have the potential to inform best practices to ultimately deliver quality public-sector hypertension and diabetes care across India.

Trial registration

The study is registered with Clinical Trials Registry of India (registration number CTRI/2020/01/022723). The study was registered prior to the launch of the intervention on 13 January 2020. The current version of protocol is version 2 dated 6 June 2018.

Role of self-care in COVID-19 pandemic for people living with comorbidities of diabetes and hypertension

People living with comorbidities especially chronic non-communicable disease (NCDs) like diabetes and hypertension are at greater risk of acquiring severe form of Corona Virus Disease (COVID-19) infection known to be caused by Severe Acute Respiratory Syndrome-CoV -2 (SARS-CoV-2) due to underlying immunodeficiency. The government has taken various public health measures to reduce the risk of infection, such as physical distancing, Information Education and Communication (IEC) messages regarding hand-washing, usage of masks, and avoidance of unnecessary travel including lockdown to combat the spread of disease. However, nationwide lockdown due to COVID-19 pandemic has also confronted the existing health care system (clinician centric approach) for the management of diabetes and hypertension in India. Using secondary source of data from specific website and search engine a review was done for existing guidelines and literature focusing on the various components of self-care management (patient-centered care) and highlights the importance of self-care management education to cope up with twin pandemic of COVID-19 and NCDs. An attempt was also made to highlight the use of eHealth to manage diabetes and hypertension which may act as a bridge to fill the gap between primary care physician and patient's amid lockdown and help physician to deliver comprehensive care for people suffering from comorbidities.

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.

The Promise of Clinical Decision Support Systems Targetting Low-Resource Settings

Low-resource clinical settings are plagued by low physician-to-patient ratios and a shortage of high-quality medical expertise and infrastructure. Together, these phenomena lead to over-burdened healthcare systems that under-serve the needs of the community. Alleviating this burden can be undertaken by the introduction of clinical decision support systems (CDSSs); systems that support stakeholders (ranging from physicians to patients) within the clinical setting in their day-to-day activities. Such systems, which have proven to be effective in the developed world, remain to be under-explored in low-resource settings. This review attempts to summarize the research focused on clinical decision support systems that either target stakeholders within low-resource clinical settings or diseases commonly found in such environments. When categorizing our findings according to disease applications, we find that CDSSs are predominantly focused on dealing with bacterial infections and maternal care, do not leverage deep learning, and have not been evaluated prospectively. Together, these highlight the need for increased research in this domain in order to impact a diverse set of medical conditions and ultimately improve patient outcomes.

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.

Investigating the attitude of patients with chronic diseases about using mobile health

BACKGROUND

Mobile health (mHealth) due to its popularity and accessibility can be widely applied in different health areas such as the management of chronic diseases. However, its success depends on the acceptance of their users. Therefore, the aim of this study was to survey the attitudes of patients with chronic disease toward mHealth technology and their willingness to use it.

METHODS

This study was conducted within a 2-year period (2016-2018) to determine and compare the attitude and willingness of patients with asthma, diabetes, and multiple sclerosis (MS) toward using mHealth technology in a province in Iran.

RESULTS

In total, 222 patients participated in this study. More than 93 percent of the patients with diabetes and MS, and 65 percent of the asthmatic patients preferred using mHealth services rather than consulting a physician (p < .0001). About 98, 94, and 49 percent of the MS, diabetic, and asthmatic patients, respectively felt comfortable if their health conditions checked by physicians through mHealth technology (p < .0001).

CONCLUSIONS

Our results showed that the majority of the patients felt comfortable and preferred using mHealth technology rather than consulting the physicians. The attitudes of diabetic and MS patients toward mHealth technology were rather more positive compared to asthmatic patient attitude. These results may be helpful for the developers of mHealth technology, and researchers who design mHelath interventions for patients with chronic disease.

Artificial Intelligence/Machine Learning in Diabetes Care

Artificial intelligence/Machine learning (AI/ML) is transforming all spheres of our life, including the healthcare system. Application of AI/ML has a potential to vastly enhance the reach of diabetes care thereby making it more efficient. The huge burden of diabetes cases in India represents a unique set of problems, and provides us with a unique opportunity in terms of potential availability of data. Harnessing this data using electronic medical records, by all physicians, can put India at the forefront of research in this area. Application of AI/ML would provide insights to our problems as well as may help us to devise tailor-made solutions for the same.

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.