Abstract
Public health informatics is one of the diverse fields that has greatly leveraged technology in building superior information systems and applications. The integration of public health informatics into research in public health has fuelled the development of better healthcare systems that facilitate, improved medical practices, innovation, and quality human health. The insufficiency of up-to-date statistics from healthcare research portals and healthcare providers on the various social factors in health aiming towards the prevention of cardiovascular diseases (CVD) through public health informatics has formulated the objective of this study. The objective of this scoping review is to determine the various obstacles and the possibility of using informatics to handle social determinants and further encourage cardiovascular disease prevention. The execution of this scoping review paper involves the analysis of literature materials published not earlier than 2015. These approved and published literature materials are freely available on internet databases such as Google Scholar. Flow diagrams have been strategically selected to represent the process of execution of this review.
Introduction
Cardiovascular disease is a collective term used to describe the disorders of the heart and the blood vessels. Some of these cardiovascular diseases include coronary heart disease, congenital heart disease, cerebrovascular disease, rheumatic heart disease, and deep vein thrombosis. According to the statistics by the World Health Organization updated in 2021, Cardiovascular diseases are the leading killer diseases in the world with data estimations indicating that 17.2 million individuals succumbed to CVD in 2019 with 85% of these deaths resulting from heart attack and stroke. The WHO further indicated some social determinants of health in CVD prevention and treatment. As defined by (Mannoh, et al.,2021) social determinants of health in cardiovascular diseases describe the various social factors that influence the disease risk factors, testing, and prevention strategies as determined by an individual’s environment. These factors include ethnicity, race, social support, level of income, level of education, employment, ease of access to healthcare, and social support.WHO stated that more than 75% of CVD deaths occurred in low to middle-income countries due to limited accessibility to quality healthcare facilities for CVD diagnosis and treatment.
The purpose of this scoping review is to exhaustively review and analyse the various published literature on the effects of social determinants of health in cardiovascular disease prevention using the various elements of public health informatics.
Changes in human lifestyle behaviors have been changing over the recent couple of decades and have been attributed to be one of the drivers of the increasing rates of cardiovascular diseases in the world. Other factors include environmental-related risk factors as quoted by (Cosselman, et al.,2015) who stated that the effect of environmental risks has been underlooked as one of the major causative agents of cardiovascular diseases. Cardiovascular diseases are a main contributor to increased mortality rates in countries such as the United Kingdom as indicated by (Bhatnagar, et al.,2015) who reviewed statistics on CVD, development, cost of diagnosis, treatment, and mortality rates across the UK population. The findings from the research on the population demographics illustrated that females led in high mortality rates due to CVD and illustrated the government’s efforts in secondary treatment strategies. The author further emphasized the importance of implementing primary and secondary preventive strategies for CVD.
With technologies such as Artificial Intelligence (AI) rapidly changing the dynamics of prognosis, diagnosis, treatment, and decision-making in public health, public health informatics remains a promising field that needs to be regularly explored and updated. Some of the applications of AI in CVD as illustrated by (Siontis, et al.,2021) is AI-enhanced electrocardiography in cardiovascular disease management. As stated by (Widmer, et al.,2015) digital health interventions are more effective compared to traditional interventions paving way for the implementation of digital health interventions composed of elements such as telemedicine, mobile applications, and web-based approaches. (Neubeck, et al.,2015) explored the effectiveness of mobile applications in the mobilization and prevention of cardiovascular diseases and further reviewed the various published literature on the applications of technologies in the management and prevention of cardiovascular diseases.
Methodology
In this scoping review paper, several literature sources comprising published and unpublished materials will be evaluated to form the basis for this review. This will involve the selection of literature materials published not earlier than 2015. the selected materials should address and answer some of the questions arising from the formulated objectives of this paper. Google Scholar is one of the popularly recognized databases that consists of millions of journals and books spanning numerous fields of study. It is one of the most efficient sources of data during the execution of reviews and literature reviews. Google Scholar is one of the sites that offers ease of accessibility to literature materials published over the years facilitated by the ease of accessibility to informational databases as facilitated by internet connectivity. In addition to Google Scholar, PubMed database will be used in this scoping review. Pubmed is a free health database that provides data from published journals and articles on public health.
Figure 1 below has been used to illustrate the full electronic search strategy processes involved undertaken when searching for relevant data and information from the Google Scholar databases and PubMed health database.
Figure 1: flow diagram of search strategy results in Google Scholar and PubMed electronic database.
Results
Numerous records of data on the effects of social determinants of health on cardiovascular disease prevention using public health informatics were found on Pubmed and Google Scholar databases. One such record was found on PubMed published by (Mannoh, et al.,2021) who described the various social determinants of health and linked the various way through which they influence Cardiovascular disease prevention in various regions across the world. The findings by the author indicated that social determinants of health affect efforts towards the prevention of cardiovascular diseases adversely and described them as complex. The author further stated that solving these challenges can be an uphill task that will require an integrated approach that includes public health measures, modifications in the healthcare systems, the emphasis on collaboration in providing care, and mobilization of the negative impacts of structural racism.
The above findings have been backed by the data obtained by (Jilani et al.,2021) in similar research on the effects of social determinants of health in cardiovascular disease prevention strategies. The author examined the various social demographic disparities in Cardiovascular diseases with data indicating disproportionalities among marginalized populations and further described suitable recommendations geared towards ensuring these disparities are minimized. However, from the data gathered by (DeVoe, et al.,2016) reducing these disparities is a difficult and complex process that can be improved by embedding innovation. (Brewer, et al.,2020) described the role of innovation in enhancing public health informatics and digital technologies in minimizing the disparities in health care by facilitating public health research. the author further described the vital role of public health informatics and digital technologies in enhancing the quality of healthcare among populations.
Additionally, (Brewer, et al.,2020) highlighted some concerns about technology and how these technologies can lead to disparities, especially for underresourced populations. Thus the author emphasized that to counter this challenge, health informatics and health organizations need to examine the various challenges that these disadvantaged communities face in towards the achievement of ideal health. The author further emphasized the importance of public health researchers and scientists engaging in community interactions in all stages of public health research. Additionally, (Adler, et al.,2016) comparatively analyzed the relationship between the poor health status of a population concerning health inequalities and the implementation of policies that affect social determinants. Policies aimed at reducing social disadvantages also reduce socioeconomic disparities.
With organizations such as the America Heart Association highlighting the linkage between health illiteracy in populations and the associated morbidity, mortality, cost of healthcare, and healthcare use, there’s a need to mobilize populations on cardiovascular disease prevention to counter disparities in healthcare (Magnani, et al.,2018). However, as highlighted by (Bazemore, et al.,2016) some healthcare providers also face the limitation of insufficient tools and technologies to facilitate decision-making and in the determination of the patient’s social determinants of health.
Moreover, according to (Richards, et al.,2017) several regions in the world still rely on traditional and out-of-date technologies with inefficient data management and analysis strategies and do not meet user needs in public health surveillance and information dissemination for disease control and prevention. Additionally, the author illustrated how technologies such as data science, advances in information technology, analytic methods, and enhanced information sharing have facilitated public health surveillance in disease prevention and control.
Since the early 2010s, numerous research studies aimed at reducing the rates of Cardiovascular Diseases in countries such as the United States of America have been successful in implementing effective Cardiovascular Diseases prevention strategies. According to (Lloyd-Jones, et al.,2022), organizations such as the American Heart Association have been actively involved in the implementation of suitable healthcare practices shifting the focus from the original Life Simple 7 which was focused on cardiovascular disease treatment. Life’s Essential 8 was a modification of Life Simple 7 and focussed on the social determinants of health in cardiovascular disease prevention and overall disease prevention. This new modification was formulated based on the existing data and various emerging concepts of cardiovascular preventive approaches with the intent to be accessible to all populations, recommendations for researchers, medical practitioners, policy makers, readers, and individuals on the various ways to implement effective policies and strategies in ensuring cardiovascular health.
In the report formulated by the American Heart Association in 2022, (Tsao, et al.,2023) demonstrated the association’s efforts in reducing structural racism a major crisis that poses danger the access to quality healthcare by increasing disparities and significantly paralyzes physical and mental health of populations. Additionally, the American Heart Association has established committees such as the Epidemiology and Prevention Statistics Committee that collect and evaluate data on heart diseases and stroke from various sources and seek to understand the associated costs of care, procedures, and economic costs.
Discussions
Summary of Evidence
From the finding discussed in the above sections, it is evident that the effects of social determinants of health have negative impacts on the implementation of preventive measures for cardiovascular diseases using technology. Technology has facilitated the development of numerous tools in data analysis through areas such as data analytics and data science. The integration of these technologies in health information systems is not only effective in the decision-making approaches among healthcare providers but improves the critical field of research. Research facilitates the development of better and improved healthcare tools and practices and further mobilizes the patients on health literacy by effectively facilitating the determination of the various social determinants respective to a particular patient.
Limitations
Some underlying challenges encountered in the execution of this scoping review will be highlighted in this section. Since this review involved extensive research on the effects of social determinants on the prevention of cardiovascular diseases using information and technology, the complex nature of the review was present making the entire process of data analysis based on numerous data and statistics from the numerous records of the databases used intensely. Additionally, the process of information search was time-consuming due to the complexity of the data search and thorough evaluation of the data records in line with the objectives of the scoping review.
Conclusion
Cardiovascular diseases are some of the leading causes of death in the world. The rate of morbidity and mortality varies across different regions in the world due to variations in social determinants. Health literacy among populations and healthcare practitioners is suitable for ensuring preventive strategies for cardiovascular diseases are successful. This is influenced by the accessibility to technology by populations, tools, and technologies for decision-making in cardiovascular disease prevention. The rapid advancements in technology have, however, influenced numerous research works and the process of information dissemination and communication facilitation. Numerous research works have successfully reduced the mortality rates from cardiovascular diseases leading to a more disease-preventive approach.
Funding
The various sources of information included in this scoping review provides little to no information on the funding of the projects. However, some authors such as (Richards, et al.,2017) indicated that they received no funding for the research, authorship, and publication of the research article. (Bazemore,et al.,2016) indicated that they received the funding from the Patient- Centred Outcome Research Institute Grant number CDRN -1306-04716.
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