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Digital Health Intervention Does Not Lower Heart Attack Risk

Digital Health Intervention Does Not Lower Heart Attack Risk

Digital health interventions offer effective means of improving NCD management in primary healthcare settings in LMICs. Such technologies can address gaps in access, efficiency and equity.

Yet findings across trials and reviews remain highly contradictory, especially regarding behavioral outcomes; for instance, interventions aiming at increasing medication adherence have produced mixed results on medication management as well as lifestyle change.

Background

As digital health interventions become an integral part of daily life, it is increasingly essential that they be designed with inclusion at their core. This is particularly important for population subgroups disproportionately impacted by preexisting and/or emerging systemic healthcare inequalities – including ethnic minorities, those from lower socioeconomic status backgrounds and older people (aged 65 and above).

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At present, digital health interventions being tested in RCTs tend to be complex and require considerable time and energy to master. This could explain the low engagement levels seen in trials, which is an indication of effectiveness. Moreover, some populations may lack digital literacy and find it difficult to engage with these tools due to the financial or accessibility limitations of the technology.

This scoping review seeks to identify strategies for optimizing the design and deployment of digital health interventions to bridge the digital divide and increase digital health literacy. Interventions targeted include those that use text messaging (e.g. ToQuit) as their communication platform as this is the most widely-used communication tool with real-time feedback capabilities that have strong effectiveness evidence for changing health behavior in various contexts including diabetes management.

Health and public health policymakers’ involvement in scoping reviews will enable the identification of opportunities to enhance current and future digital health interventions, including setting clear national guidelines and an eHealth strategy, standardizing policies across institutions, harmonization of policies across institutions, cost effectiveness analysis of new digital health technologies in clinical practice settings as well as wider healthcare systems, cost effectiveness evaluation, adoption promotion strategies etc.

The Digital Health Readiness Scale is a great way to assess an individual’s readiness to use digital tools. It can help bridge the digital divide and reduce disparities in healthcare.

Methods

Digital health interventions can assist people in making healthier lifestyle choices and managing their health more effectively by providing personalized guidance and feedback, self-management tools and encouraging interaction between patients and healthcare providers. 

They may also increase patient-provider communication efficiency as well as efficiency and effectiveness of healthcare delivery; however, studies that examined digital health interventions demonstrated mixed or neutral effects across various outcomes.

These interventions are typically delivered using smartphones or tablet computers with Internet connectivity, and outcomes studied during trials include both clinical (such as blood pressure reduction) and behavioral outcomes such as medication adherence. 

Digital health modalities used include case management, healthcare worker communication and collaboration tools and data services which include electronic health records (EHRs) as well as mobile phone applications that give patients access to their medical records.

Most trials measured outcomes like adherence, compliance or symptom reduction as outcomes; fewer included cost-effectiveness analyses as well as accessibility, acceptability and equity evaluations. 

Most trials took place in high-income countries which limited availability of relevant and comparable data from lower income populations; furthermore due to a lack of national eHealth guidelines and strategies they failed to effectively monitor the impacts and benefits of digital health interventions on local environments.

Recruitment of participants for digital health intervention studies can have significant ramifications on results that are achieved. In the trials reviewed here, poor recruitment and engagement was often one of the primary contributors to failure to reach desired clinical outcomes. 

Furthermore, disparities have been documented at multiple stages during research and recruitment process for these interventions.

Though inequalities cannot always be avoided, efforts could be made to streamline the identification and recruitment processes for patients. Furthermore, including sensitivity analyses evaluating digital health interventions on groups less likely to benefit could help understand why certain interventions were found effective or ineffective.

Results

Over the last decade, advances in digital technology have created new opportunities to deliver healthcare services via smartphone apps (apps) and internet portals, including telehealth services, data-driven precision medicine and personalized risk score apps. Unfortunately, evidence regarding their effectiveness in lowering heart attack risks remains limited. 

To advance this field further, large-scale clinical trials featuring adequately powered randomized control trials must be conducted to assess whether these digital health interventions actually reduce cardiovascular disease risk factors.

Scoping review identified 52 studies, comprising 31 reviews and 21 trials. This research covered 14 out of 28 digital health intervention categories as defined by the World Health Organization classification system. Most interventions examined by this research were used by healthcare providers such as electronic health records (EHR), decision support systems and telemonitoring devices; five others were designed specifically to be utilized by clients such as text messaging apps for medication adherence or phone coaching calls.

Findings showed that results of digital health interventions varied greatly for clinical outcomes (such as blood pressure and glucose control of individual patients) as well as behavioral outcomes such as disease self-management and healthy behaviors, with highly mixed results due to study design limitations like small sample sizes and short follow up durations. Implementation outcomes such as increased efficiency and accessibility were generally more consistent across studies.

Digital health research should prioritize equitable and sustainable implementation to ensure digital technologies benefit disadvantaged populations. 

To meet this objective, researchers are advised to include various sociodemographic indicators when designing samples for digital intervention trials – beyond age and gender – including education level, income status and level of deprivation as indicators in their selection process for trial samples. During design phase sensitivity analyses could examine whether digital interventions have differential effects among populations.

Researchers should conduct process evaluations of digital health interventions in order to identify any challenges or barriers related to their implementation, including impact assessments on key stakeholders like healthcare providers and patients as well as what needs to change to increase adoption of these technologies in practice.

Conclusions

Although evidence for digital health interventions is expanding quickly, significant barriers remain that limit their application in CVD prevention. One such obstacle is an increasing digital divide between those who possess access to technology and literacy skills to utilize these platforms and those who do not; this digital gap may account for mixed findings of intervention efficacy and effectiveness found throughout this literature.

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Studies on digital health interventions often vary widely in their objectives and outcomes, making rigorous quantitative synthesis such as meta-analysis difficult. However, literature addressing their effect on individual-level outcomes has been more robust; for instance, an EHRs integrated consumer-focused digital health intervention was linked with borderline improvements in medication adherence, risk factor control and lifestyle behaviors among those at moderate to high risk for CVD.

Other studies have investigated the potential advantages of digital interventions in improving patient-centric outcome such as quality-of-life and satisfaction with healthcare, including strategies for self-management and engagement. Although results from these types of trials have been positive in general, no evidence has emerged that changes have occurred for disease-specific outcome like blood pressure.

Digital health interventions are implemented in many ways, including smartphone apps and telemedicine to physical activity monitors. It’s important to consider both the context and the target audience of the technology in order to increase the chances of success. For example, an app that encourages physical activity may be more effective at encouraging healthy lifestyles among active individuals.

Assessing whether the target population possesses both the capability and motivation for engaging with digital health interventions is also of vital importance. Low education levels and limited e-health literacy have been identified as barriers to engaging with these initiatives; researchers should therefore focus on optimizing digital health interventions so as to overcome them.

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