digital health thesis

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• Published: 18 August 2022

A framework for digital health equity

• Safiya Richardson 1 ,
• Katharine Lawrence   ORCID: orcid.org/0000-0001-5640-2138 1 ,
• Antoinette M. Schoenthaler 1 &
• Devin Mann   ORCID: orcid.org/0000-0002-2099-0852 1  

npj Digital Medicine volume  5 , Article number:  119 ( 2022 ) Cite this article

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• Health policy
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We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of healthcare may widen health disparities if solutions are not developed with these determinants in mind. Our framework builds on the leading health disparities framework, incorporating a digital environment domain. We examine DDoHs at the individual, interpersonal, community, and societal levels, discuss the importance of a root cause, multi-level approach, and offer a pragmatic case study that applies our framework.

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Introduction.

Decades of research have identified health differences, based on one or more health outcomes, that adversely affect several defined populations, including rural populations, persons with low incomes, racial and ethnic, and sexual and gender minorities 1 . Early work in the field of health disparities focused on identifying and describing these differences and their potential causes. In the last two decades, there has been a growing understanding of the role of systemic oppression as a root cause of disparities, as well as a commitment to discovering effective interventions 2 , 3 . The field’s focus on health equity reflects this shift. Health equity refers to the absence of health inequities, differences in health that are unnecessary, avoidable, unfair, and unjust 4 .

As the field of health disparities has matured, we’ve simultaneously witnessed the digital transformation of healthcare. The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 sparked the long-awaited adoption of electronic health records (EHRs) by healthcare systems across the country and eventually the development of patient portals, allowing patients online access to key elements of their medical charts. Today, over 95% of hospitals use a government-certified EHR and allow their patients to view health information online 5 . HITECH additionally spurred private industry investment in digital health, including mobile health, wearable devices, remote patient monitoring (RPM), and telehealth, which now is noted in billions per year.

The coronavirus disease 2019 (COVID-19) pandemic highlighted both the continued impact of long-standing systemic oppression on disparate health outcomes as well as the growing importance of digital healthcare. Several studies found significant differences in successful telehealth use in disparity populations 6 , 7 , 8 . Access to digital health is becoming an increasingly important determinant of health. There has been a growing recognition of access as just one of several determinants in the digital environment that impact outcomes 9 , 10 . These digital determinants of health (DDoH), including access to technological tools, digital literacy, and community infrastructure like broadband internet, likely function independently as barriers to and facilitators of health as well as interact with the social determinants of health (SDoH) to impact outcomes 11 , 12 .

As digital health becomes increasingly essential, a framework for digital health equity detailing key DDoHs, is needed to support the work of leaders and developers in the industry, health systems operations, and academia. Digital health solution developers include computer scientists, software architects, product managers, and user experience designers. The digital transformation of health requires leaders and developers to understand how digital determinants impact health equity. In this article, we present the Framework for Digital Health Equity, an expansion of the leading health disparities framework. We examine key DDoHs at the individual, interpersonal, community, and societal levels, discuss the importance of a root cause, multi-level approach, and offer a pragmatic case study as an example application of our framework.

Definitions

Health disparity populations.

The framework applies to all health disparity populations. As defined by the US Office of Management and Budget, these include racial/ethnic minorities, socioeconomically disadvantaged populations, underserved rural populations, and sexual and gender minorities (which include lesbian, gay, bisexual, transgender, and gender-nonbinary or gender-nonconforming individuals). We acknowledge and support the special emphasis placed by the NIMHD on the historical trauma experienced by American Indian groups that were displaced from their traditional lands and African-American populations that continue to endure the legacy of slavery. We additionally include a focus on individuals with disabilities, including those with limitations in their ability to see, see color, hear, etc., that might impact digital accessibility.

Digital environment

The digital environment is enabled by technology and digital devices, often transmitted over the internet, or other digital means, e.g., mobile phone networks. This includes digital communication, RPM, digital health sensors, telehealth, and the EHR. The digital environment includes elements of the physical/built environment, sociocultural practices, and understanding, as well as the habits and behaviors that dictate how we use these tools. The digital environment exists within and outside of the formal healthcare system.

Social determinants of health

SDoH are defined by the Centers for Disease Control and Prevention as “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks” 13 . These social circumstances are responsible for health inequities as they are heavily shaped by the distribution of money, power, and resources. The SDoH falls into five key categories: healthcare access and quality, education access and quality, social and community context, economic stability and the neighborhood, and the built environment. Determinants in the digital environment, including access, can significantly impact the SDoHs. For example, applications for employment, which influence an individual’s economic stability, are now almost exclusively accessible online.

Digital determinants of health

The DDoH are conditions in the digital environment that affect a wide range of health, functioning, and quality of life outcomes and risks. The DDoH includes access to technological tools, digital literacy, and community infrastructure like broadband internet and operates at the individual, interpersonal, community, and societal levels. They impact digital health equity, which is equitable access to digital healthcare, equitable outcomes from and experience with digital healthcare, and equity in the design of digital health solutions 10 , 12 .

Framework for digital health equity

National institute on minority health and health disparities (nimhd) research framework.

The framework for digital health equity is an expansion of the NIMHD Research Framework. This framework, published in 2019, is the culmination of decades of work in the field of health disparities 14 . The framework is organized into several domains, including biological, behavioral, physical/built environment, sociocultural environment, and the healthcare system. It categorizes domains of determinants according to levels of the socioecological model. The SDoH are included primarily in the physical/built environment, sociocultural environment, and the healthcare system domains. The NIMHD Research Framework was an adaptation of the National Institute on Aging (NIA) disparities model, where the healthcare system domain was added because of its particular importance to health. Similarly, because of its critical role in health and healthcare - we incorporate a digital environment domain.

The DDoH are incorporated into the NIMHD Research Framework within the digital environment domain (Fig. 1 ). Determinants are not intended to be exhaustive and often function in ways that are cumulative or interactive.

National Institute on Minority Health and Health Disparities Research Framework Expanded for Digital Health Equity.

Individual-level determinants

Determinants at the individual level include digital literacy, digital self-efficacy, technology access, and attitudes towards use. Digital literacy refers to the skills and abilities necessary for digital access, including an understanding of the language, hardware, and software required to successfully navigate the technology 15 . Self-efficacy is the belief that one can surmount any problem through one’s own effort and is connected to a wide variety of desirable outcomes, including higher performance and achievement striving 16 , 17 . Digital self-efficacy is an individual’s self-efficacy with regard to the effective and effortless utilization of information technology and predicts proficiency 18 . Digital literacy contributes positively to but does not entirely account for an individual’s sense of digital self-efficacy 19 , 20 . Others have highlighted similar terms, such as digital confidence, as distinct from digital literacy and instrumental in establishing the digital agency, an individual’s ability to control and adapt to a digital world 20 .

Technology access describes the necessary technological equipment availability to an individual. Attitudes towards use include an individual’s desire and willingness to use, trust in, and beliefs about their ability to use digital tools. Attitudes towards use are adapted from theories of technology adoption such as the technology acceptance model (TAM) and include perceived usefulness and perceived ease of use which predict technology adoption 21 . Trust is also a key construct, as disparity populations can have unique concerns about privacy, security, and surveillance. These concerns can be exacerbated by factors that might be comforting to other groups, for example, affiliation with state or government institutions or the healthcare system. For example, African Americans are more likely than whites to distrust the medical system, report experiencing racism in it, and to express concern about threats to privacy from EHRs 22 , 23 , 24 .

Interpersonal level determinants

Determinants at the interpersonal level include implicit tech bias, interdependence, and the patient-tech-clinician relationship. These determinants describe relational factors that connect individuals to both digital health technologies and one another. Implicit bias is a term with growing use in the healthcare field, defined as associations outside conscious awareness that lead to a negative evaluation of a person. Implicit Tech Bias is used to describe the impact that unconscious perceptions of an individual’s digital literacy, technology access, and attitudes towards use have on clinician (and affiliated healthcare team members) willingness to enroll and engage individuals with digital healthcare tools. For example, disparity populations have been documented to be less likely to receive invitations to set up patient portal accounts by their clinicians 25 . These clinicians may have been attempting to select patients more likely to successfully use the portal, however implicit bias would have played a role in this assessment and may have contributed to unequal access. Interdependence is used to describe the dependence of two or more people (e.g., family members, caregivers, or friends) on each other for the digital skills, access, and equipment necessary to use digital health tools. For example, low-income households are more likely to share devices and to operate in connection with others 11 . Interdependence can be considered as a positive adaptive mechanism in many contexts, with these bonds serving as positive social capital and facilitating healthy behaviors for both individuals and larger group networks.

The Patient-Tech-Clinician relationship describes the complex interpersonal transformations encouraged by digital technologies, which impact power dynamics between individuals and can help address or exacerbate power imbalances in relationships. For example, the digitization of healthcare may democratize the relationship between the individual and clinician, transforming the paternalistic paradigm of medicine into an equal partnership through data access and transparency 26 . For disparity populations, this has the potential to impact well-documented dimensions of the patient-clinician relationship, including medical mistrust and poor quality communication.

Community level determinants

Determinants at the community level include community infrastructure, healthcare infrastructure, community tech norms, and community partners. Community infrastructure includes cellular wireless and broadband access, quality, and affordability. Broadband access is considered an important health determinant, access to which should be ensured by the Federal Communications Commission 9 . Digital redlining impacts access to patient portals, RPM, and telehealth 27 , 28 . Without broadband internet access, patients cannot fully use telehealth in all its forms: asynchronous messaging via patient portals, remote monitoring devices such as blood pressure monitors, or synchronous video connections to consult with a physician.

Healthcare infrastructure includes community access to health systems with advanced digital capabilities, including sophisticated EHR systems, patient portals, and telehealth tools like RPM and simultaneous audio-visual visits. Community tech norms include community preferences for particular tools (i.e., WeChat), high- vs. low-tech solutions, etc. These norms impact health outcomes based on how they compare or contrast with those of the dominant culture and are influenced by a variety of factors, including perceived utility and availability of certain features (e.g., language) which improve acceptability for specific communities. Community partners are an important contribution to the local digital equity ecosystem, the socio-technical systems that work to increase access, and include tech advocacy groups, community health workers, libraries, and digital literacy training programs.

Societal-level determinants

Determinants at the societal level include tech policy, data and design standards, social norms and ideologies, and algorithmic bias. Tech policy includes the federal, state, and local policies supporting healthcare technology adoption (i.e., HITECH), development and innovation (i.e., 21st Century Cures Act), and security (i.e., HIPAA, Health Insurance Portability and Accountability Act). Data standards are created and maintained by professional organizations, for example, Health Level Seven International produced Health Level Seven (HL7), Fast Healthcare Interoperability Resources (FHIR), and others. The inclusion or exclusion of data relevant to certain populations in these standards impacts the ability of organizations to measure and monitor progress towards equity.

Design standards impact accessibility for those with disabilities and low digital health literacy. For example, Web Content Accessibility Guidelines (WCAG) cover a wide range of recommendations for making Web content more accessible 29 . Recommendations include ensuring a high contrast ratio for colors, that text size can be increased by at least 200%, and not using color alone to convey information. Following these guidelines makes content accessible to a wider range of people with disabilities, including blindness and low vision, deafness and hearing loss, learning disabilities, cognitive limitations, limited movement, speech disabilities, photosensitivity, and combinations of these. Social norms and ideologies are the set of beliefs and philosophies that impact who develops digital tools, what is developed, how it is used, and who it is used by. For example, diffusion of innovation theory is widely adopted in the field and includes the assumption that technology should be developed for early adopters, typically those with excess time and resources, and these tools will eventually trickle down to the general population 30 , 31 . Other examples include the masculine coding of technology and our assumptions that these tools provide objectivity 32 .

Algorithmic bias includes bias in the use of machine learning and artificial intelligence as well as racial bias in health algorithms that do not use these advanced statistical and computational methodologies. The use of race correction in health algorithms has recently come under scrutiny for potentially contributing to health disparities 33 . For example, the Vaginal Birth After Cesarean Risk Calculator provides a lower estimate of the probability of vaginal birth after prior cesarean for individuals of African-American race or Hispanic ethnicity 34 . The health impact of this may be significant considering that women of color continue to have higher rates of cesarean section, the health benefits of vaginal deliveries are well known, including lower rates of surgical complications, and black women, in particular, have higher rates of maternal mortality 35 . The use of a calculator that lowers the estimate of the success of vaginal birth after cesarean for people of color could exacerbate these disparities.

An “upstream”, multi-level approach

We hope that the Framework for Digital Health Equity will encourage users and support them in developing an “upstream”, multi-level approach. Health disparities are the result of complex social, environmental, and structural forces. However, interventions in the field have suffered from the Fundamental Attribution Error—overweighting the impact of individual or personal factors and underweighting contextual or situational factors. Health disparities interventions almost always target individual determinants, less often targeting the interpersonal, community, or societal-level determinants 14 . Disparity populations are less likely to benefit from interventions focused on individual-level determinants, as barriers, including limited resources and competing priorities, are greater in these populations 36 , 37 . Interventions targeting “upstream” determinants at the community and societal levels (i.e., digital infrastructure) are more likely to be effective for these populations 38 , 39 .

In addition to targeting “upstream” DDoH, a multi-level approach that simultaneously targets the interdependence between the levels of influence can be effective as well. Disparity populations often face structural disadvantages at multiple mutually reinforcing levels 40 . For those studying the effects of such approaches, contemporary methods can provide information about causality at multiple levels as well as interaction effects. These contemporary methods include the sequential, multiple assignments, randomized trial (SMART), multi-level analysis, and the multiphase optimization strategy (MOST) research framework. A multi-level approach allows us to discover the impact of targeting determinants that may be necessary to address to close disparities in outcomes but that are by themselves not sufficient for eliminating disparities.

Applying the framework for digital health equity: remote patient monitoring use case

The use of RPM, e.g., ambulatory, noninvasive digital technology to capture, and transmit patient data in real-time for care delivery and disease management, is an innovative digital health capability that is rapidly being embedded into our healthcare delivery system. It is increasingly being leveraged for the management of hypertension 41 , diabetes 42 , congestive heart failure 43 , chronic obstructive pulmonary disease 44 , and a range of other chronic conditions 45 . Established non-digital SDOH for RPM uptake include issues such as limited English proficiency (individual level, sociocultural environment domain), disparities in insurance coverage (individual level and healthcare system domain), preferences for social/community-oriented vs. individually driven care (interpersonal level and sociocultural environment domain), device safety and security issues (community level and behavioral domain) and staffing models of medical practices in underserved communities (societal level and healthcare system domain).

Digital health giants and startups now offer an expanding ecosystem of devices, platforms, and products supporting the scale-up of this new technology 46 . Following the usual diffusion of innovation paradigm, many of these offerings are targeting well-resourced settings and populations. However, the dissemination of RPM is early enough that there is an opportunity to use our emerging understanding of the DDoH to alter the usual diffusion curve and build RPM tools that can meaningfully engage health disparity populations. To facilitate this disruption, we highlight RPM digital health equity considerations for the digital health industry, clinical, community, and policy leaders to consider as they grow their RPM products and programs (Table 1 ).

We use RPM as a use case to demonstrate how this framework can be used to highlight opportunities to reshape how digital health is developed, deployed, and disseminated so that diverse communities have an equal opportunity to take advantage of the potential of new digital health technologies.

The rapid digital transformation of healthcare may contribute to increased inequality. Health interventions often lead to intervention-generated inequalities as they are typically adopted unevenly with disparity populations lagging behind 47 . Digital health is particularly vulnerable to this as interventions are likely to disproportionately benefit more advantaged people with greater access to money, power, and knowledge. Digital health leaders and developers in industry, academia, and healthcare operations must be aware of the DDoH and the roles they play to ensure that the use of technology does not widen disparities.

We expand the NIMHD Research Framework to incorporate a digital environment domain detailing key DDoH. Currently, there is no comprehensive framework for digital health equity that addresses determinants at all levels and provides context with the SDoHs. Without an understanding of the DDoHs in context, digital health solution development and research may result in tools and knowledge that are incomplete as they do not address the cumulative or interactive effects of multiple domains. Notably, the framework includes both risk and resilience factors which is key as we support a strengths-based approach to development.

Digital health stakeholders concerned with equity and impact should consider the DDoHs in product development and intervention design and dissemination, incorporating community and societal-level determinants as well as developing multi-level approaches. By expanding the leading health disparities research framework for digital health equity, we hope digital health leaders in the industry, academia, policy, and the community will benefit from decades of progress in the field of health disparities as well as see their work in the larger context of SDoHs so that we might work together towards meaningful progress in using digital means to achieve health equity for all.

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Acknowledgements

This work was supported by grant K23HL145114 from the National Heart, Lung, and Blood Institute. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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Richardson, S., Lawrence, K., Schoenthaler, A.M. et al. A framework for digital health equity. npj Digit. Med. 5 , 119 (2022). https://doi.org/10.1038/s41746-022-00663-0

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Strengthening health systems using innovative digital health technologies in africa.

• 1 Harvard T.H. Chan School of Public Health, Boston, MA, United States
• 2 World Health Organization – Africa Regional Office, Brazzaville, Congo
• 3 World Health Organization, Geneva, Switzerland
• 4 World Bank Group, New York, NY, United States
• 5 World Bank Group, Maseru, Lesotho

While effective health systems are needed to advance Universal Health Coverage and actualize the health Sustainable Development Goals, information system verticalization remains a challenge among African health systems. Most investments are vertical, partner-driven and program-specific with limited system-wide impacts. Poor linkages exist amongst different solutions as they are not designed to capture robust data across multiple programmatic areas. To address these challenges, the World Health Organization Africa Regional Office has proposed the adoption of a Digital Health Platform (DHP) to streamline different solutions to a cohesive whole. The DHP presents a pragmatic approach of bringing multiple platforms together using recognized standards to create a national infostructure, which bridges information solutions toward healthy and sustainable outcomes. It has capacities to curate accurate, high fidelity and timely data feedback loops needed to strengthen and continuously improve program delivery, monitoring, management, and informed decision-making at every level of the health system regardless of location. This paper contributes to the ongoing regional conversations on the need to harness innovative digital solutions to improve healthcare delivery in Africa.

Introduction

Discussions on harnessing innovative ways of bridging the digital divide among African health systems have continued to gain traction over the past decade. Current challenges with digital solutions in Africa limit their overall impact as most solutions are institution-specific with limited system-wide impacts ( 1 ). There is limited emphasis on system strengthening to drive sustainable developments in countries. Most health investments are vertical, partner-driven and program-specific. Partners too often adopt the reductionist perspective that places more focus on disease priorities, with the belief that the system will be strengthened when interventions are prioritized for specific diseases ( 2 ). There is limited policy buy-in by stakeholders, as partners often seek to produce quick results for the Sustainable Development Goals (SDGs) through fragmented siloed programs. There are also poor linkages amongst different solutions as they are not designed to capture robust data across multiple sectors and programmatic areas. While most solutions lack mechanisms to capture high fidelity real-time data to respond to current needs; others are not designed to support interoperability and data sharing across the continuum of care ( 1 ).

These are fragmented, inefficient vertical silos systems built with minimal involvement of end-users. In addition, there is low management and governance capacity to coordinate digital health solutions that are responsive to regional needs ( 3 ). These peculiar challenges result in major gaps in the ability of digital health solutions to respond to the needs of Member States ( 4 , 5 ). According to the WHO Regional Committee report, different Member States are at different digital health maturity level, which could impact the provisions of integrated care and systemic healthcare digitization ( 6 , 7 ). The Global Observatory report of 2015 on eHealth documented varied level of use of different digital solutions among African health systems, with mHealth technologies reported as the most used innovation, and big data documented as the least used innovation ( 6 ).

This article aims to contribute to the ongoing regional conversations on the need to harness innovative digital solutions to improve healthcare delivery in Africa. The paper highlights key challenges, ongoing progress and future directions in-view of the use of the World Health Organization African Regional Office (WHOAFRO) Digital Health Platform (DHP) to strengthen African health systems for the SDGs. It explores approaches for operationalizing the WHOAFRO DHP, and proposes policy recommendations for addressing persistent digital divide among most African economies. The adoption and institutionalization of the DHP among African health systems has opportunities to bridge information solutions toward healthy and sustainable outcomes in countries.

As a key enabler of health information across the spectrum of data, analytics, and knowledge; digital health solutions contribute to the strengthening of health systems as countries move toward the achievement of the Universal Health Coverage (UHC) and the health Sustainable Development Goals (SDGs). Given the appropriate infrastructure, skills, and education, digital technologies have opportunities to improve access to essential healthcare services, while reducing paper-based reporting systems. When fully optimized and functional, integrated digital solutions have opportunities to positively impact sustainable health outcomes including agreed sustainable development goals and targets ( 3 , 4 ).

The WHOAFRO DHP is a facility-wide end-to-end digital solution that enables users to collect, analyze and interpret clinical information. The platform can be manipulated to fit the hospital workflows and can be customized to fit Member States' health systems across different service delivery levels. The platform has several modules that enable users to easily enter, retrieve and analyze data within the facility, based on their needs, roles and responsibilities. Thereby, enabling the users to: Track data over time; Identify patients who are due for preventive visits and screenings; Monitor how patients measure up to certain parameters (e.g., vaccinations); and improve overall quality of care among others ( 1 , 7 ).

Digital System Fragmentation Creates System Inefficiencies

Advancements in digital technology witnessed among global communities brought opportunities and threats to health systems. By the end of 2018, more than two-third of the global community subscribed to a mobile service. The falling price of connectivity and the rollout of 5G networks have encouraged many more to adopt the innovative digital technology ( 5 ). The increasing digital solutions have opportunities to transform health systems from reactive to proactive to predictive systems that consolidate integrated care and sustainable developments in countries ( 7 ). This has led to increased access to reliable health information and has strengthened TB and HIV outcomes ( 8 ) as well as psychiatric outcomes ( 9 ) among others.

While innovative digital technologies have opportunities to bridge systems for sustainable developments in countries, studies show that digital fragmentation arising from systemic proliferation of systems have opportunities to exacerbate inefficiencies ( 10 , 11 ). The rising pace of digitization poses threats to the digital health ecosystem as numerous digital solutions compete with each other with no systemic integrations for impacts. Most solutions are standalone and are deployed in response either to specific needs or to support specific programs, with significant gaps in collecting and analyzing real-time digital data ( 12 , 13 ). The Ebola response in the Democratic Republic of the Congo presents a topical use-case where lack of connectivity, systemic integrations and coordination led to redundant efforts that mitigation efforts. Multiple vertical solutions deployed by partners without systemic integrations with national infostructure could not share real-time data, and lacked consistency in data entry and coding protocols. These decreased data quality and created opportunities for errors, thereby impacting surveillance mechanisms ( 14 ).

Siloed solutions led to increased burden on system users as well as overall medical practice errors ( 15 ). Gleiss and Lewandowski ( 15 ) reported an increased misdiagnosis, inappropriate medication dispensing and duplicate services following numerous standalone solutions. These introduced systemic inefficiencies as they require healthcare workers and system administrators to use multiple, unconnected digital applications iteratively. Healthcare worker were made to login into many applications with different access methods and identifiers to be able to do a particular work that could be essentially interrelated. The duplicated efforts introduced systemic confusion, data entry errors and staff burnout, and impacted the overall quality of service delivery ( 15 ).

These translate to constraints to innovation ( 16 ). Software developers spend time writing redundant codes for standalone applications that could be shared as common core technologies. According to WHO Reports (2019), this status quo impacts the development of an integrated national infostructure that connects multiple systems, and undermines governments' efforts on delivering quality health services ( 17 ). In addition, data security, privacy and identification issues remain a concern for both users and the government ( 10 ). The question pertinent is whether it is feasible to develop an integrated solution that could solve regional information solutions challenges. Yes, this is possible; the technology exists. The WHOAFRO DHP has opportunities to address identified challenges through robust planning, implementation, and review mechanisms including the establishment of regular reviews, communities of practice, and capacity improvements supported by technical experts at WHOAFRO including other implementing partners. Such mechanisms encourage governments to be accountable and committed as they are guided to prioritize deploying integrated solutions that serve the needs of the people and are linked to prioritized service outcomes ( 18 ).

Integrated Response to Fragmented Digital Solutions Among African Health Systems

To address health systems' challenges and strengthen regional health systems for the SDGs, the WHOAFRO proposed the use of a comprehensive DHP to address peculiar regional digital challenges and provide integrated digital solutions that align with the needs of countries ( 1 , 18 ). The WHOAFRO DHP is a facility-wide electronic health records system that ensures the realization of UHC pillars of “Accessibility, Quality and Affordability” and has opportunities to accelerate innovation at country levels. It enables individual applications and systems to interoperate and work together in an integrated manner for robust outcomes. The platform fosters interoperability through standard-based Health Information Exchange and health information architecture known as infostructure. DHP infostructure comprises a set of integrated common and reusable components, which are core technology services required by applications for the efficient running of digital health systems including registries, data repositories and identity authentications among others. It is one component of the complex systems that make up national health systems. Thus, with infostructure as part of the DHP, the influential impacts of governmental leadership on DHP institutionalization could be exponential, and have opportunities to impact its scope and scale ( 1 , 2 ).

The DHP is an open-source, open-standard public good that provides robust digital solutions that facilitates comprehensive electronic management of patient health records. It supports ICT infrastructure principles for digital development and investment, as well as provides a framework for sustainable implementation and capacity-building ( 19 ). The platform corroborates other regional goods as it upholds the core principles and values of WHOAFRO's Action Framework, which highlights the interconnected nature of health systems and services through effective, equitable and efficient service delivery ( 18 ). The basic elements of the WHOAFRO DHP is represented thus:

The WHOAFRO DHP could provide a horizontal base digital solution that connects vertical siloed information systems including functional and non-functional requirements that are housed within individual digital health applications. Through DHP's interoperable standard-based design, exchange of information is facilitated efficiently whenever the need arises: All data passes through the DHP hub, whether they are stored on the DHP alone or divided among multiple external repositories and applications. Such information exchange occurs through DHP integrated services, authentication services, common workflows support services, consistent terminologies and reference data, and other components that help streamline and improve efficiency ( 1 ).

The WHOAFRO DHP enables users to collect, analyze and interpret clinical information ( 1 ). Being modular, the system can be manipulated to fit specific hospital needs and workflows. In addition, modules can be customized to specific needs of a given hospital business processes. The WHOAFRO DHP is an open source modular system for use by service providers to capture and record interactions with clients from entry to exit of a hospital ( 1 ). It is built as an extension of the open source OpenMRS (version 1.98 with the 2.0.4 UI Library Module). Frontend application architecture comprises ASP.NET, Bootstrap, XML, XSLT and Pooper, and it uses ICD-11 standards ( 20 ). The platform is built on a Model View Controller (MVC) design pattern; and on a framework which is an object-relational mapper (O/RM) that enables.NET developers to work with a database using.NET objects ( 20 ). It is designed to capture real-time service delivery and management events as they occur in a facility; Provide standard guidance to service providers during the process of care—for example standard clinical practice, use of ICD-11 for diagnosis, use of essential medicines list for drug management; Build a repository of health and management events occurring in facilities; Monitor adherence to clinical and management guidelines during provision of clinical and public services; Highlight real-time notifiable events as they are captured in the facilities; and Allow for information sharing across facilities ( 1 , 2 ).

The scope of WHOAFRO DHP hardware requirements are dependent on the hospital. It is recommended to use existing hardware, but plan for medium to long term Information Technology (IT) improvements to maximize the use of the DHP. Equipment to consider include but not limited to: Computers, tablets, server point, single finger print reader (if biometric information is needed), printing services, power solutions, and communication and networking equipment, to allow the different service points be interlinked with each other, and to the server. It is preferable that both cabling, and an intranet wireless system are installed; though this would depend on country context and needs that should be determined following site assessments ( 1 ).

Potential products of the WHOAFRO DHP solution are pragmatic. In line with the needs of a hospital, the WHOAFRO DHP solution can be customized to provide the following: Modules of care based on the specific focus services of a hospital; Automated summary of records and analysis of data arising from the DHP data that is collected, in line with the specific needs of the hospital; An Application Program Interface (API) to link the DHP to any previous IT system the hospital was using, and so access past electronic records; A client portal, where patients can access and enter records for data they need to collect from home, and receive key information/messages and interact with their providers; A “How to” guide to facilitate self-training by providers in the installation and use of the DHP with limited need for external expertise; and Access to a wider DHP “Community of Practice” where issues and solutions can be discussed with a global pool of OpenMRS experts ( 1 , 2 ).

Developed by the WHOAFRO, this platform is expected to evolve and mature over time depending on country needs, context and complexity. It begins with a core set of functionalities necessary to support initial digital health applications that any country wishes to integrate and evolve over time. More functionalities are added in-view of country DHP's maturity and sophistication to support more services and programs prioritized by countries. It has globalization flexibilities, as it can be translated into different languages per country needs and contexts. The DHP supports integrated service delivery through four perspectives including Health Providers' Portal, Health Managers' Portal, Community Statistics Portal and Personal User Portal.

Health providers' portal and health managers' portal are part of the enterprise resource platform and represent health facility events at the enterprise level ( Figure 1 ). It documents real-time case management of health events from first interaction with the patient to resolution, as well as highlights relevant support systems that are available in health facilities including Human Resources for Health, Health Facility Management, and Central Sterile Service Department among others. Actions defined around this domain are mainly those related to health systems' building blocks including service delivery, health workforce, health infrastructure, medical products and health technologies. Others are health governance, health financing, and health information ( 1 , 21 ). Performance under this domain is measured by health system resilience, efficiency and equity of access, quality of care, and service demand ( 18 ).

Figure 1 . Comprehensive WHOAFRO Digital Health Platform elements.

Community health platforms define points where health investments are made on the use of community statistics for routine monitoring, evaluation and surveillance. Such health investments are made in the form of data systems, hardware/software tools and community-support processes that enable community surveillance and translates to defined outcomes and impacts. Actions defined under this domain are mainly those related to birth and death registration, household registries, and verbal autopsy tools ( 1 ). Performance under this domain is measured by improvements in life expectancy, morbidity and mortality reductions, and risk factor reductions mainly at the individual and community levels ( 18 ).

Lastly, the personal user portal represents individual events at the patient and client-level, and comprises personal data repository, vital signs data (weight, height, temperature etc.,) and targeted health messages amongst others ( 1 ). Elements under this portal comprises: Availability of essential services for care users, coverage of essential services for target groups, client satisfaction, health financial risk protection, and cross-sector coverage of essential health services ( 18 ). Thus, clients and care-seekers are able to access information related to the care and services they need ( 22 ).

The DHP infostructure enables interoperability of the listed portals for system efficiency. Information and data systems from the portals pass through the data hub of the DHP to the data warehouse enabled by robust Master Facility Index and Master Person Index ( Figure 1 ). Agile health big data systems, management and analytics enabled by Machine Learning (ML) and Artificial Intelligence (AI) applications facilitate programmatic data analytics for policymaking, system improvements and intervention mapping ( 23 ). This also facilitates the generation of real-time data on national repositories like the District Health Information System-2 platforms, and sends live information updates on national dashboards like national health observatories for health statistics (health indicators, trends and distribution), health information data (analyses profiles) and health knowledge (policy briefs and best practices). Others are live information updates on patient user portals for patient health records, targeted health messages, service reminders and user data entries among others. It also facilitates real-time updates on quality of care standards including standard guidance (ICD, ICME and Clinical standards), care adherence (care audits) and care monitoring (effectiveness, equity and cost) among others ( 1 ).

Operationalizing the WHOAFRO Digital Health Platform: Consolidating Strategies for Integrated Regional Digitization

Overall, the DHP is more encompassing than the Electronic Health Record as it captures personal health records, and places the management of health within country systems as well as in the hands of health-seekers. It facilitates the attainment of UHC from healthier populations perspectives by ensuring that individuals are able to receive health services without any financial hardship. Through this holistic approach, need is addressed through the perspective of demand (and not merely supply) for services that would help populations achieve healthy lives and wellbeing. As low demand translates to low utilization, populations must be aware of what is available, accessible and useful for them. This will help in improving health-seeking behaviors, decisions and actions of individuals ( 12 , 24 ). Proper community engagement, enlightenment and capacity-building on health are critical to the change management and knowledge translation processes involved in the successful implementation of the platform ( 1 ).

The adoption of the WHOAFRO DHP provides the opportunity to translate robust frameworks into operational strategies for countries to strengthen national health systems for the SDGs through effective digital approaches. The WHOAFRO DHP supports the development of an integrated health sector digitization strategy for Member States, which aligns and incorporates other national e-government initiatives for improved national outcomes. Digital Health Strategy creates a clear path that guides the investments of the Governments and their development partners. It outlines a time-bound, practical, sustainable, and cost-effective plan for the deployment of a set of integrated information systems that supports the achievement of national goals, targets and priorities ( 6 ).

The Estonian model highlights critical pathways the DHP connects with the e-government frameworks. The Ministry of Social Affairs, Estonia established a unified digital platform that linked public and private enterprises through efficient interoperable secured architectures. The platform leveraged on existing cross-institutional digital integrations of key governmental sectors including but not limited to e-taxation, e-banking and e-school through unique national electronic identifiers ( 1 , 13 ). The Estonian model corroborated the mHero deployed in Liberia during the Ebola outbreak of 2014. The Ministry of Health (MoH) connected existing systems- human resources information systems (HRIS) with Short Message Service (SMS) through efficient RapidPro platforms that facilitated information exchange between health workers. This provided real-time information exchange harnessing OpenHIE frameworks for integrated disease surveillance and response ( 1 ). Thus, the mHero of Liberia, the FamilyConnect of Uganda and the Sistema Electronico de Logistica de Vacinas of Mozambique are other related digital platforms with integrated e-government frameworks and robust trust frameworks ( 19 , 25 ).

Aerts and Bogdan-Martin documented the use of the Broadband Commission's framework for evaluating digital technology proliferations, including its strengths in identifying and addressing critical digital gaps ( 10 ). This corroborated the study by Moore et al. ( 13 ) which highlighted the use of an integrated digital health framework to design effective health information systems with system-wide impacts. They emphasized the need to consolidate technologies which are integrated, scalable and interoperable ( 11 ). Thus, the WHOAFRO envisages that the development of the regional DHP and its country-specific implementations will strengthen regional health systems for the SDGs. To achieve this, there will be a need to accelerate the shift from targeted solutions to interoperable system-wide solutions with enhanced system performance for improved health outcomes ( 1 ).

The implementation of the DHP is never linear in practice, but has areas of overlap of activities in accordance with the WHO Digital Implementation and Investment Guide (DIIG). Key implementation steps include: Conduct context analysis; Design and establish DHP architecture; and implement DHP by institutionalizing the DHP among national health systems. Countries implementing DHP are guided through a systematic approach of gathering functional and non-functional requirements for developing, designing and implementing meaningful digital health interventions in-line with recommendations from DIIG. However, system governance, local configuration needs and data hosting is at the country level/servers with technical support from WHOAFRO and other implementing partners ( 1 , 2 ).

Thus, the DHP improves health systems at scale by fostering linkages and interconnections that dissuades redundancy and silos approaches to health system thinking ( 3 ). The DHP has mechanisms adaptable to differing settings that allow Member States to contextualize the solution based on their contexts, capacity and needs while allowing WHOAFRO and other implementing partners provide the necessary technical assistance. This includes providing guidance on technology selection, capacity development and Monitoring & Evaluation (M&E) frameworks as necessary. This helps appraise the DHP performance data, identifies training needs, facilitates identification of platform bottlenecks, and optimizes systems' performance. It also supports the identification of DHP's potential advancements, interventions and accomplishments, DHP infostructure design, its development stage and uptake by users ( 1 ).

The gap is a lack of integrated conceptualization of digital health needs. For instance, interoperability challenges are due to piecemeal digital solutions that do not talk to each other. Thus, emphasis should be on building and sustaining people-centered integrated solutions with system-wide impacts. The prevailing COVID-19 pandemic has reinforced the need to have integrated solutions given the range of possible digital needs. Countries are willing to adopt the DHP solution, but the challenge amidst many others, is in current technology vendors that develop and maintain independent systems ( 1 ). Thus, moving forward, evolving technologies of interest should be embraced including big data management, AI and ML innovations to improve AI-powered predictions, analytics and optimizations for sustainable health outcomes ( 26 , 27 ).

The Future of African Health Systems' Digitization: Bringing the Best of Technology to Health

As part of the global efforts to transform health, the WHOAFRO through effective mechanisms has continued to harness the power of innovative technology to support countries to achieve health SDGs including emergency preparedness and response. A key lesson learned is the importance of taking holistic approaches when developing digital health systems. Building standalone solutions should be discouraged including the existence of too many redundant solutions that conflict with one another. Countries should address this on time as they begin health system digitization discussions. They should move toward single, dominant modular home-grown systems that integrate all elements. Such systems should be open source and open standard systems ( 27 ). The DHP infostructure offers efficient foundations for cohesive systems, and is built and designed through holistic approaches that enables systems' expansion, integration and updates. Such solutions enable interoperability and are tailored to the needs of specific health systems involved ( 1 ).

Digital health applications and solutions should be government demanded, and not market-driven solutions. Governments are to map requirements according to needs and contexts, for which the digital health community can work concertedly to address prioritized national needs: It should not be the other way round. This exercise should be informed by countries' digital health strategy, standards, enterprise architecture and other regulatory protocols as necessary. Such governance mechanisms should focus on how to build and sustain integrated solutions in countries. Implementing partners are to provide support and guidance to the government on digital health strategy development, solution procurement and enterprise architecture ( 17 , 26 ). This should conform to national infostructure which enables greater flexibility that facilitates reusability and interoperability with external systems through recognizable standards and APIs. Thus, this consolidates health systems efficiencies and improvements by allowing more national digital health interventions to plug in, thereby accommodating evolving digital technologies including AI, Internet of things and new medical technologies as necessary.

The eGovernment overarching architecture should always be adhered to, as this guides the overall government's expectations with e-solutions. It facilitates the linkage of solutions, and takes advantage of eGovernment support to ensure system integrations with existing national systems and repositories. Thus, vendors including implementing partners are encouraged to map existing solutions against country digital health standards, infostructure and enterprise architecture. Collaboration is key in digitization ( 21 ). Public private partnerships should always be consolidated for sustainability. It enables exchange of experiences for faster uptake of lessons learned. Cross-country collaborations for learning and sharing of experiences foster communities of practice roles and designs. This fosters efficient health systems' digitization of scale and scope. Such knowledge exchanges by digital health professionals have opportunities to leapfrog national health systems to new frontier technologies, while building competencies and skills to scale and sustain investments ( 21 , 27 ).

In addition, the DHP could foster a culture of data use within the health sector. It could also be used to recognize burgeoning disease epidemics or community health trends by routinely tracking and analyzing service delivery data. Once identified, the various digital tools available on the DHP can be used to help address such events. DHP enables detailed understanding of different COVID-19 needs by population demographics, and provides real time progression of COVID-19 within a population. The platform supports real-time monitoring of medical interventions– ensures and monitors treatment standards, surveillance protocols, as well as collates data on treatment regimens and outcomes. There are interlinkages of different data to understand trends, distribution impacts, including prediction and attribution information at the individual and population levels. The platform also populates long-term follow-up data which are part of policy data to inform policy-making, intervention mapping and overall system improvements ( 28 ).

Lastly, with a digital health platform in place, African countries can embark on more successful digital health programs that can rely on built-in system infostructure to access important and reliable information; connect national/rural health facilities and workers to specialist care and higher-level professional training through well-coordinated telemedicine networks; improve health financing processes including fraud detection; as well as identify the users of the applications and data on the DHP infostructure. Patient care options could also be expanded by DHP enabling home-based monitoring and electronic health records and prescriptions that can be accessed and updated iteratively wherever patients seek services, no matter the device and location ( 1 ). Thus, the need to adopt and implement an integrated solution with robust regulatory frameworks cannot be over-emphasized.

Conclusions

This paper contributes to the ongoing Regional conversations on the need to harness innovative digital solutions to improve healthcare delivery in Africa. The paper summarized topical information systems' challenges among African health systems, and enumerated the possible ways of addressing identified challenges using the WHOAFRO DHP, including how the platform could be operationalized to strengthen Regional health systems for the SDGs.

Notable challenges anticipated with implementing the WHOAFRO DHP include but limited to: High cost of software; Lack of in-country capacity to manage the software; Lack of unique patient identifiers among most African economies; Poor internet and power capacities; Lack of standard management; and resistance to system use by service providers among others. Thus, in the future, we expect more collaborations and partnerships to address listed challenges. For this solution to scale and achieve impact; strong, country-led partnerships are encouraged among governmental systems. African governments are encouraged to focus on effective capacity building, sustainable business model, and rigorous M&E frameworks to advance and scale health sector digitization. In addition, DHP implementers should work concertedly with the government to shape national healthcare ecosystems that connect multiple healthcare journeys, adapt innovative technologies and aggregate robust data systems into a streamlined cohesive whole to advance Regional health goals.

Author Contributions

SI, DM, HK, and JO conceived, coordinated, and wrote the first draft of the manuscript. KG and NC participated in the study conception and overall study coordination. SI, DM, and KG contributed in writing the subsequent drafts of the manuscript. NC, HK, and JO did the final review and edit of the draft manuscript. All authors read and approved the final draft of the manuscript before publication and contributed to the article and approved the submitted version.

Conflict of Interest

HK and JO were employed by World Health Organization – Africa Regional Office. DM was employed by World Health Organization. KG was employed by World Bank Group. NC was employed by World Bank Group.

The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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26. Meyer C, Kim, E, Husain, I,. Developing Economic Impact Assessment Methods to Identify the Costs of Artificial Intelligence-Driven Health Technology. United States Agency for International Development Policy Paper. (2021). Available online at: https://pdf.usaid.gov/pdf_docs/PA00XGXF.pdf (accessed November 11, 2021).

27. World Health Organization. Classification of Digital Health Interventions: A Shared Language to Describe the Uses of Digital Technology for Health. Geneva: World Health Organization (2018). Retrieved from: https://www.who.int/reproductivehealth/publications/mhealth/classificationdigital-health-interventions/en/ (accessed October 24, 2021).

28. Uohara MY, Weinstein JN, Rhew DC. The essential role of technology in the public health battle against COVID-19. Popul Health Manag . (2020) 23:361–7. doi: 10.1089/pop.2020.0187

Keywords: Africa, Digital Health Platform, health systems strengthening, Universal Health Coverage, Sustainable Development Goals

Citation: Ibeneme S, Karamagi H, Muneene D, Goswami K, Chisaka N and Okeibunor J (2022) Strengthening Health Systems Using Innovative Digital Health Technologies in Africa. Front. Digit. Health 4:854339. doi: 10.3389/fdgth.2022.854339

Received: 13 January 2022; Accepted: 14 March 2022; Published: 31 March 2022.

Reviewed by:

Copyright © 2022 Ibeneme, Karamagi, Muneene, Goswami, Chisaka and Okeibunor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sunny Ibeneme, drsunnyibeneme@gmail.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Open Access

Peer-reviewed

Research Article

Digital literacy as a new determinant of health: A scoping review

Roles Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Intermediate Care Unit. Hospital de Niños Ricardo Gutierrez Buenos Aires, Argentina, Argentine Society of Intensive Care. Management, Quality and Data Committee Buenos Aires, Argentina

Roles Investigation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, Ohio, United States of America

Roles Conceptualization, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing

Affiliations Department of Anesthesiology and Intensive Care. Hospital Clínic de Barcelona, Barcelona, Spain, Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, Massachusetts United States of America

Roles Conceptualization, Formal analysis, Investigation, Writing – original draft, Writing – review & editing

Affiliation Argentine Society of Intensive Care. Management, Quality and Data Committee Buenos Aires, Argentina

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing

Affiliation Research Medical Library, University of Texas MD Anderson Cancer Center, Houston, Texas United States of America

Roles Formal analysis, Investigation, Writing – original draft, Writing – review & editing

Affiliation College of Medicine, University of the Philippines Manila Manila, Philippines

Roles Conceptualization, Supervision, Writing – review & editing

Affiliations Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, Massachusetts United States of America, Division of Pulmonary, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America

• Maria del Pilar Arias López, 
• Bradley A. Ong, 
• Xavier Borrat Frigola, 
• Ariel L. Fernández, 
• Rachel S. Hicklent, 
• Arianne J. T. Obeles, 
• Aubrey M. Rocimo, 
• Leo A. Celi

• Published: October 12, 2023
• https://doi.org/10.1371/journal.pdig.0000279
• Reader Comments

Introduction

Harnessing new digital technologies can improve access to health care but can also widen the health divide for those with poor digital literacy. This scoping review aims to assess the current situation of low digital health literacy in terms of its definition, reach, impact on health and interventions for its mitigation.

A comprehensive literature search strategy was composed by a qualified medical librarian. Literature databases [Medline (Ovid), Embase (Ovid), Scopus, and Google Scholar] were queried using appropriate natural language and controlled vocabulary terms along with hand-searching and citation chaining. We focused on recent and highly cited references published in English. Reviews were excluded. This scoping review was conducted following the methodological framework of Arksey and O’Malley.

A total of 268 articles were identified (263 from the initial search and 5 more added from the references of the original papers), 53 of which were finally selected for full text analysis. Digital health literacy is the most frequently used descriptor to refer to the ability to find and use health information with the goal of addressing or solving a health problem using technology. The most utilized tool to assess digital health literacy is the eHealth literacy scale (eHEALS), a self-reported measurement tool that evaluates six core dimensions and is available in various languages. Individuals with higher digital health literacy scores have better self-management and participation in their own medical decisions, mental and psychological state and quality of life. Effective interventions addressing poor digital health literacy included education/training and social support.

Conclusions

Although there is interest in the study and impact of poor digital health literacy, there is still a long way to go to improve measurement tools and find effective interventions to reduce the digital health divide.

Author summary

This scoping review aimed to investigate the impact of low digital literacy (DL) on health as well as DL and digital health definitions, instruments used to assess it and interventions useful for its mitigation. We performed a comprehensive literature search strategy which identified 53 articles for analysis. Digital health literacy was the most commonly used term to describe the ability to find and use health information using technology. The eHealth literacy scale (eHEALS) was found to be the most utilized tool to assess digital health literacy. Higher scores on the eHEALS were linked to better self-management and participation in medical decisions, improved mental health, and overall quality of life. Overall, this study highlights the need to address the digital health divide and improve access to digital health information and tools for those with low DL. This can be achieved by developing effective interventions to improve digital health literacy, like education/training and social support and increasing awareness of the importance of digital health literacy for better health outcomes. The findings of this study can inform policymakers and healthcare providers on the need to address the issue of low digital health literacy to improve health equity and outcomes.

Citation: Arias López MdP, Ong BA, Borrat Frigola X, Fernández AL, Hicklent RS, Obeles AJT, et al. (2023) Digital literacy as a new determinant of health: A scoping review. PLOS Digit Health 2(10): e0000279. https://doi.org/10.1371/journal.pdig.0000279

Editor: Jennifer Ziegler, University of Manitoba Faculty of Medicine: University of Manitoba Max Rady College of Medicine, CANADA

Received: December 20, 2022; Accepted: May 19, 2023; Published: October 12, 2023

Copyright: © 2023 Arias López et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data are in the manuscript and supporting information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Digital technologies are transforming health, health care, and public health systems across the world, and they have a great potential to improve population and individual´s health and wellbeing [ 1 ]. Technology has advanced in such a way that it has made it possible to expand the type of interactions available between the user and the medical provider or the healthcare systems. Obtaining health information and requesting appointments online, virtual visits, asynchronous digital messaging with healthcare professionals, health tracking wearables and self-monitoring devices, are all technologies available nowadays. These systems bring many advantages; they make it possible to scale information processing, administrative processes and facilitate access to healthcare through virtual visits. Using a video or an online appointment app enables providers to serve hundreds of people that can be attended simultaneously and travel can be avoided for in-person appointments that do not require a physical examination or tests [ 2 ]. However, weak governance of digital transformations can also lead to uneven effects globally, increasing health inequities. This reflects the paradox of digital health that we are currently facing: the potential that digital health innovations hold can be transformational for delivering care to underserved population groups (rural areas, aging patients, minorities, or persons with disabilities) but these groups are most likely to be excluded from the digital world through their sociodemographic characteristics [ 3 , 4 ].

The digital transformation, which a priori has many advantages, may contribute to further increasing the inequalities that already exist in access to healthcare thus generating a “digital divide”. “Digital divide” is a term used to encompass a wide range of social differences in access to and use of digital equipment and services, especially personal computers and smartphones, and the ability to access the Internet, both in terms of physical connection and ease of use. As health care becomes more reliant on technology-based tools, the digital divide stands to further exacerbate existing health care access disparities [ 2 ].

Digital technologies should be recognized nowadays as a key determinant of health, similar to socioeconomic status, income, education, age, race, ethnicity and gender [ 4 ]. Although almost the entire world population now lives within reach of some form of mobile broadband or internet service and mobile phones are becoming ubiquitous, only half of people worldwide use the internet and have basic information and communications technology skills [ 5 ]. This gap between internet access and use shows that there are multiple barriers to meaningful access that need to be addressed, especially lack of science, technology, engineering, and mathematics education, digital skills and digital literacy.

Digital literacy can be defined as the varying ability of both children and adults to use digital technologies and understand their risks. It refers not only to the applied technical skills necessary to use and access the internet, but also to the capacity to critically and confidently engage with the online environment. More broadly, as a determinant of health, it has been emphasized that digital literacy substantially interacts with other intermediate health factors and social determinants, to influence both access to digital health resources and wider health equity outcomes [ 6 ]. Health literacy–the ability to obtain, read, understand and use health-care information to make appropriate/ informed health decisions [ 7 ]–is increasingly becoming a core skill for health-related information on the Internet. Digital health literacy, at first glance, can be regarded as the convergence of digital literacy and health literacy. However, the reality is likely more complex because each competence domain of digital and health literacy may affect one or more competence domains of digital health literacy [ 3 ]. On the other side, different terms are used interchangeably in the literature to refer to digital health literacy. According to the National Institutes of Health All of Us Research Program, digital health literacy is “the ability to seek, find, understand, and appraise health information from electronic sources and apply the knowledge gained to addressing or solving a health problem” [ 8 ]. Other terms are used depending on the source(s) of the health information. While mHealth literacy focuses on information gathered with the use of mobile devices, eHealth literacy focuses on information gathered from online resources and telehealth literacy specifically focuses on telehealth platforms [ 1 ]. In any of these cases, low digital health literacy can carry with it several consequences. Primarily, it can deepen health inequities in an increasingly digitized healthcare landscape. Patients who do not know how to use digital health tools, don’t see the importance of those tools, or can’t access them in their preferred language, ultimately won’t use them. And that puts them at a disadvantage for patient engagement and health improvement. Digital health literacy has recently been acknowledged as one of the “super social determinants of health” because it has implications for the wider social determinants of health [ 3 , 6 , 9 ] In order to design effective strategies to address this new health determinant, it is necessary to recognise its consequences and the populations it affects. We therefore decided to carry out this scoping review that seek to determine the effects of poor digital literacy on health, specifically looking to define poor digital health literacy, identify populations at risk, the health outcomes affected, its consequences, and interventions targeted to reduce the digital health literacy gap.

This scoping review was conducted following the methodological framework of Arksey and O’Malley [ 10 ]. The review process was structured according to the following stages:

Identification of the research question

The research question was stated as, “How does digital health literacy affect health?”. Specific objectives include (1) to define digital health literacy, identify existing assessment tools and groups potentially affected by poor digital health literacy (2) to identify the health outcomes affected by poor digital health literacy and its consequences, and (3) to identify interventions targeted to reduce the digital health literacy gap.

Identification of relevant studies

On May 11, 2022, a comprehensive search of the literature was constructed and performed by a qualified medical librarian. Medline (Ovid), Embase (Ovid), Scopus, and Google Scholar were queried using both natural language and controlled vocabulary terms for telehealth, digital health, digital literacy, computer proficiency, vulnerable populations, health outcomes, etc. We focused on recent (last 5 years) and highly cited references published in English. Conference abstracts were excluded. The search strategy is detailed in S1 Text . Reference lists of the studies found through database searches were also checked, especially for the systematic reviews and scoping reviews.

Selection of studies

Original articles on digital literacy and digital health literacy were included if these answered any of the study objectives. Papers that focused on technology use and access instead of digital literacy were excluded. Articles on interventions targeted to reduce the digital literacy gap were excluded if the intervention was not tested in a study population. The initial search returned a large number of results, including non-original articles (systematic reviews and scoping reviews), editorials, letters, commentaries, study protocols, and other publications not deemed relevant that were therefore excluded. Articles without available full text and papers that were not available in English were also excluded. Five authors (MA, BO, AL, XB, AO and AR) independently screened titles and abstracts identified by the electronic search and applied the selection criteria to potentially relevant papers. Any disagreements were resolved by consensus within the group. Data from the selected relevant papers were extracted by one author using a standardised checklist and checked by a second ( S1 Template ).

Charting of data

The following key items were obtained based on our consensus as to what information should be collected from the individual studies: author of the article; journal and year the article was published in; article type and objective; setting (country), study population, and sample size; definition and assessment of digital literacy or digital health literacy; health outcomes affected by digital health literacy and its consequences; and interventions targeted to reduce the digital health literacy gap.

The following data were sought for studies that defined digital literacy, digital health literacy, and its related concepts: concept(s) or term(s) used; definition; theoretical framework or model. For studies that employed assessment tools for digital health literacy, the following data were sought: assessment tool; author; elements considered by the assessment tool; aim or intended use of the assessment tool; mode (self-rated versus performance-based); scoring; language; and reliability, Cronbach α. For studies that tackled the correlation between digital health literacy and health outcomes, the following data were sought: health outcomes assessed; and main conclusion on the association between digital health literacy and health outcomes. For studies on interventions targeted to improve digital health literacy, the following data were sought: intervention category; intervention; author; setting; and study population.

Reporting of results

Pertinent data from the included studies were summarized and analyzed in a narrative, and presented in groups or themes wherever applicable. A critique of the methods and outcomes of the included studies is beyond the scope of this review.

This review was not registered and neither a protocol was prepared. All data are in the manuscript and/or supporting information files. The data used to construct Figs 1 and 2 are reported in table format in S1 Data .

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https://doi.org/10.1371/journal.pdig.0000279.g001

This figure shows the geographic gap in relation to the origin of the selected articles. If we consider that the determinants of poor digital health literacy (age, level of education, belonging to an ethnic minority) could be the same globally, this figure is indicative of the recognition and interest of the problem in the different countries. Figure created using the Natural Earth base layer from www.naturalearthdata.com under the PDDL license https://opendatacommons.org/licenses/pddl/.

https://doi.org/10.1371/journal.pdig.0000279.g002

A total of 268 articles were identified in the study. Of these, 263 came from the electronic search and five came from the references of the literature and systematic reviews identified from the electronic search. Fig 1 lists the number of studies included and excluded per step according to the diagram adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement [ 11 ].

Four duplicates were identified. Of the remaining articles, 199 did not proceed beyond the screening stage due to any of the following: no abstract; out of scope; non-original data, meta-analysis, or reviews; editorials, letters, or commentaries; or protocol. Twelve articles were further excluded due to unavailable full text.

Characteristics of included studies

The main characteristics of the included studies are described in S1 Table .

The 53 studies that reached analysis were published in a diverse range of journals. Among the included studies, the oldest was published in 2016 [ 12 ] while the most recent ones were published in April 2022 [ 13 , 14 ]. The majority of the studies were published in 2021 (19/53; 35.85%) followed by 2020 (15/53; 28.30%).

Of the 53 included studies, 44 were cross-sectional studies (44/53; 83.01%). Only six (6/53; 11.32%) studies were longitudinal: three of them experimental [ 14 – 16 ], the rest pre-post observational studies [ 17 – 19 ]. The last three studies were mixed methodology studies [ 20 – 22 ].

Most studies (20/53; 37.74%) were conducted in North America (17 of them in the United States of America, 2 in Canada, and 1 in Mexico), 17 in Asia (6 in China, 6 in Korea, 1 in Pakistan, 1 in Taiwan, 1 in Vietnam, and 1 in multiple countries), 9 in Europe, 2 in Australia and 1 in Africa ( Fig 2 ).

Definition of digital health literacy

Different terms were used across the studies to refer to digital health literacy, including electronic health literacy, eHealth literacy, mHealth literacy, telehealth literacy, and mobile health proficiency. Among these, the most frequently used in the included studies is eHealth literacy (30/53; 56.60%) followed by digital health literacy (12/53; 22.64%). These concepts similarly refer to the ability to find and use health information with the goal of addressing or solving a health problem using technology. However, these are differentiated by the source(s) of the health information [ 23 – 26 ]. mHealth literacy focuses on information gathered with the use of mobile devices [ 25 ] while eHealth literacy focuses on information gathered from online resources [ 23 ]. Telehealth literacy specifically focuses on telehealth platforms [ 27 ].

In the included studies, digital health literacy was most often used interchangeably with the earlier term eHealth literacy [ 23 ]. Whereas eHealth literacy is limited to information from Web 1.0 platforms viewed by users in a passive manner, digital health literacy incorporates information from Web 2.0 platforms with interactive content including social media, blogs, and video sharing sites [ 23 – 25 ]. Digital health literacy is therefore a broader concept compared to eHealth literacy.

A more specific concept related to digital health literacy encountered in one included study is digital healthy diet literacy, defined as the ability to access and appraise digital healthy-diet-related information to improve healthy eating behavior and health outcomes [ 28 ].

The term digital literacy instead of digital health literacy was used in seven of the included studies (7/53; 13.21%). Compared to digital health literacy and eHealth literacy, digital literacy is a broader term as it refers to the ability to find and apply digital information. Other terms used by the included studies for the same concept include digital competency [ 29 ], digital capability level [ 30 ], mobile phone digital literacy [ 31 ], new media literacy and technological literacy [ 32 ].

The conceptual framework of eHealth literacy by Norman and Skinner [ 23 ] was employed by the majority of studies (32/53; 60.37%). Four studies [ 33 – 36 ] employed the e-health literacy framework by Norgaard et al. [ 24 ] and one study [ 37 ] employed the transactional model of ehealth literacy by Paige et al. [ 38 ]. In Norman and Skinner’s framework, eHealth literacy is likened to the pistil that holds the petals of the lily flower together, similar to how eHealth literacy ties together six core skills: traditional literacy, health literacy, information literacy, scientific literacy, media literacy, and computer literacy [ 23 ]. In contrast, the framework by Norgaard et al. [ 24 ] encompasses domains largely dependent on the individual (domain 1: ability to process information; domain 2: engagement in own health), domains largely dependent on the system (domain 6: access to digital services that work; domain 7: digital services that suit individual needs), and domains on the dynamics between the individual and system (domain 3: ability to actively engage with digital services; domain 4: feel safe and in control; domain 5: motivated to engage with digital services). The transactional model of eHealth literacy, on the other hand, highlights the transactional features central to eHealth literacy and outlines four operational skills: functional, communicative, critical and translational [ 38 ].

In S2 Table , we detail the concepts related to digital health literacy and its corresponding theoretical framework employed in the included studies.

Measurement of digital health literacy

Twenty different assessment tools were employed by the included studies to assess digital literacy and/or digital health literacy ( Table 1 ).

https://doi.org/10.1371/journal.pdig.0000279.t001

Forty-five of the included studies (45/53; 84.90%) used at least one of these assessment tools. ( S3 Table ) The tools differ in terms of evaluation elements, applicable groups, and intended use. Six of these specifically focus on digital literacy [ 29 , 30 , 39 – 42 ], six on eHealth literacy [ 12 , 33 , 36 , 37 , 43 , 44 ], four on digital health literacy [ 45 – 48 ], one on digital healthy diet literacy [ 49 ], one on telehealth literacy [ 27 ], one on health information literacy [ 50 ] and one on a combination of eHealth and mHealth literacy [ 51 ]. Most of these tools are self-rated Likert scales except for eHealth Literacy Assessment [eHLA) toolkit [ 36 ] and Digital Health Literacy Instrument [DHLI] [ 45 ] which both employ a combination of self-rated and performance-based assessment, and Digital Literacy Evaluation [DILE) tool [ 41 ], which is performance-based.

The eHealth literacy scale [eHEALS) by Norman and Skinner [ 43 ] is the most widely used in the included studies (24/53; 45.28%). Five studies [ 13 , 22 , 52 – 54 ] used the DHLI [ 45 ], and two studies [ 49 , 55 ] used the Digital Healthy Diet Literacy [DDL) tool [ 49 ].

Twelve of the twenty assessment tools identified are available in English, five in Chinese, three in Danish, four in Korean, two in Vietnamese, and two in Spanish. Four of the assessment tools are available in several languages. The included studies used different versions of eHEALS (English [ 15 , 18 , 28 , 56 – 60 ], Spanish [ 17 , 61 ], Chinese [ 62 – 64 ], Korean [ 52 , 65 , 66 ], and Vietnamese [ 55 , 67 ]), eHealth Literacy Questionnaire (EHLQ) (Chinese [ 68 ], English [ 21 ], Danish [ 21 ]), DHLI (Chinese [ 53 ], Danish [ 22 ], English, [ 13 , 53 ], Korean [ 52 ]), and eHLA toolkit (Danish [ 36 ], English [ 36 ]).

Groups affected by lower digital literacy

Several of the included publications report that the level of health digital literacy was associated with gender, age and level of education.

Abdulai et al. [ 56 ], performed a survey with 268 respondents aiming to examine the digital literacy of lay consumers of online COVID-19-related information in Ghana. In their study the authors describe that males were more likely than females to have high digital literacy related to internet-based information. At the same time, according to this survey, digital literacy was likely to be lower among older people despite being the group more likely to suffer from COVID-19 complications.

Similarly, Guo et al. [ 62 ], in a random cohort of adults in Hong Kong, examined socioeconomic disparities in seeking web-based information on COVID-19 and eHealth literacy, and their associations with personal preventive behaviors during the COVID-19 pandemic. In this study the eHL and mHL literacy scores had significant and negative associations with age [eHL, r = -0.380, P < .001; mHL, r = -0.398, P = .036]. The results also show that the participants with higher education had a greater level of mobile eHealth literacy.

The association of level of education and digital literacy was also described by Adil et al. [ 28 ] In the survey that they performed among a sample of university students, the authors report that belonging to different categories of educational attainment affects the level of usage and of expertise in digital health literacy in varying ways. This study concludes that educational level is the major factor for unequal response towards digital health literacy. The study furthermore depicted that the students of BS/Master, MS/MPhil and PhD are substantially different from each other in their level of usage and expertise.

In order to recognize patient´s perspectives of the principal causes of digital divide, Alkureishi et al. [ 2 ] conducted 54 semi structured telephone interviews with adult patients and parents of pediatric patients who had virtual visits (phone, video, or both) between March and September 2020 at the University of Chicago Medical Center (UCMC) primary care clinics. The most common subtheme cited by the participants as a cause of medical divide was advanced age, which was considered a major contributor and limitation to their ability to learn and navigate technology. Cognitive and medical impairments, including memory loss and hearing and visual impairments, were also challenges that contributed to the digital divide among older individuals.

At the same time, the study of Aponte et al.[ 61 ], which evaluated the Spanish version of the eHEALS with an older Hispanic adult sample in a senior organization of a Spanish neighborhood in New York reported that the highest item in the eHEALS results was related with the importance that the persons assigned to being able to access health resources on the Internet (mean eHEALS: 4.4 (DS 0.7)) while the lowest item was the one related to their ability to use the Internet to answer their questions about health (mean eHEALS: 3.2 (SD: 12)), indicating that respondents knew how to find health-related information on the internet but were not confident in using that information to make health decisions.

In addition, a secondary analysis of the CALSPEAKS survey performed by Berkowsky et al. [ 70 ], showed that in the group of respondents older than 65 years of age, level of education (less of high school, high school, some college, associate’s degree, bachelor’s degree or postgraduate degree) and measures of digital experience and skill (e.g frequency of Internet use, breadth of Internet activities performed regularly) had strong and consistent associations with eHealth literacy.

Digital health literacy and health outcomes affected

Of the 53 studies included, only 13 (24.53%) studies reported on how digital literacy affected health outcomes. Health outcomes reported encompass health promotion, quality of life, mental and psychological states, disease prevalence, and health status. Table 2 describes the health outcomes related to the level of digital health literacy.

https://doi.org/10.1371/journal.pdig.0000279.t002

The most frequent health outcome reported was health promotion. Five of 13 studies (38.46%) reported health-promoting behaviors, including health responsibility, stress management, exercise behavior, self-realization, and social support. Both quality of life and disease prevalence were the second most common reported health outcomes in this study (4/13, 30.77%). This was followed by mental and psychological states (2/13; 13.58%), which involves managing negative emotions, meta-cognition, and psychological well-being. Lastly, 2/13 (15.38%) studies assessed how digital literacy affected the health status of patients. Individuals with better digital literacy were likely to have better disease control (type 2 diabetes patients) [ 51 ].

According to the patient’s perspectives, digital literacy can limit access to online patient portals. Without access to these tools, less technologically able individuals experience challenges in care coordination such as scheduling visits, communicating with their clinicians, and facilitating referrals and tests. Patients also consider that the divide can worsen personal health care outcomes because of limited opportunities and resources to coordinate health care needs. Less technology- savvy individuals had significant challenges to access to COVID-19 vaccine and to use online scheduling portals [ 2 ].

Interventions that address poor digital health literacy

Of the included studies, only 9 (9/53; 16.98%) evaluated interventions addressing poor digital health literacy ( Table 3 ). These interventions can be divided into 2 categories: education and training, and social support. Majority of the interventions which significantly improved digital health literacy were under education and training. Under education and training, massive open online courses, university training in e-health through tutoring, and online video-based portal training were reported to improve digital health literacy of both children and adults. On the other hand, 2 out of 9 reported interventions were categorized under social support. Social support from technology-savvy family members, professionals, and peers were shown to improve digital health literacy of adults and older adults.

https://doi.org/10.1371/journal.pdig.0000279.t003

Digital determinants of health, like insufficient technology access and digital literacy, are currently recognized as Social Determinants of Health (SDOH). However, they should not be considered merely the sixth domain on the list of determinants of health, as they are major controllers of every SDOH and the environment in which they can be accessed fully.

Instead, digital determinants should be considered “super determinants of health” taking into account that they are drivers of each SDOH profoundly influencing whether they are functional or dysfunctional and potentially impacting one’s overall health and quality of life.

Decision makers, health professionals, and researchers must consider and address the effects of digital determinants on population health in order to design and implement improvement strategies. Therefore, we decided to perform this scoping review with the aim to summarize current knowledge about digital literacy and its consequences on health, specifically searching to identify most frequently impacted groups, health outcomes affected and proposed interventions targeted to reduce the so-called “Digital divide”.

The body of existing literature on the topic is vast and growing, especially in the last two years. Although it is rich in definitions and author´s proposals of strategies to improve digital health literacy, publications that describe specific health outcomes affected or proven interventions are scarce. The overall level of evidence of the analyzed studies was low; only 4 of the 53 articles included in the review have levels of evidence of II and III corresponding to small randomized controlled trials and case control studies respectively; the rest are level V corresponding to observational studies and case series [ 75 ]. Most of the samples of the revised publications were small sized.

Although most studies show that patients with lower levels of digital literacy and access to technology are more likely to belong to marginalized backgrounds, including older persons, black and hispanic populations and non-English speaking patients, the vast majority of the studies were conducted in North America, Europe and China. In the selected papers, Africa, South America and a large part of Asia and Oceania are underrepresented and surely coincide with the regions most affected by the digital health literacy gap, since in these areas a large part of the population has similarities at the socioeconomic and educational level with the groups we have described as most affected by the digital health gap.

Defining and measuring digital health literacy should be the first step for bridging the digital divide. However, the definitions used in the different studies are heterogeneous as well as the instruments used for its measurement. Digital literacy can be considered an umbrella term for many different technologies (internet, mobiles, social media, etc) and affects various areas of human lives such as education, business, health, governance among others. It has been defined as “the skills required to achieve digital competence, the confident and critical use of information and communication technology for work, leisure and communication” [ 26 ]. At the same time, health literacy can be defined as “the degree to which individuals can obtain, process, understand, and communicate about health-related information needed to make informed health decisions” [ 23 ]. At first glance “Digital Health literacy” can be regarded as the convergence of digital literacy and health literacy [ 76 ]. However, the reality is more complex. In most published studies, both health and digital literacy are conceptualized through competency-based frameworks. Health literacy is elaborately expressed through a matrix of four dimensions (access/obtain information relevant to health, understand information relevant to health, process/appraise information relevant to health, and apply/use information relevant to health) that are applied across three domains (healthcare, disease prevention, and health promotion) [ 8 ]. A European Commission framework on digital competencies takes a similar approach to digital literacy by depicting five dimensions [information and data literacy, communication and collaboration, digital content creation, safety, and problem- solving], each with four to six sub-dimensions that illustrate a core competence of digital literacy [ 77 ]. The relationship between digital, health, and digital health literacy is a multi-dimensional one where each competence domain of digital and health literacy may affect one or more competence domains of digital health literacy [ 78 ], but certain competencies of digital health literacy may not be covered by neither digital literacy nor health literacy [ 7 ]. As an example of this statement, Abdulai reported that educational status, frequency of using the internet, and using the internet for social media and entertainment purposes were not significant predictors of digital literacy related to online COVID-19 information [ 56 ]. Though the overall literacy level was high, respondents had a relatively lower mean score on questions that indicate they may have some challenges locating the right kind of COVID-19 online resources, as well as a limited ability to distinguish high-quality information from those reflecting personal opinions or anecdotal stories [ 56 ]. Likewise, Guo et al report in their survey performed in a sample of people with diabetes in 3 taiwanise hospitals that, although they were confident in using mobile eHealth and technology, only 1.6% used health apps or adopted these tools in their daily lives [ 51 ].

The complexity and multidimensionality of health and digital literacy highlight the need to conceptualize digital health literacy in the context of a competence framework.

The analysis of the instruments used for digital health measurement showed that eHealth Literacy Scale (eHEALS) was the most widely used in several countries and populations.

This is an 8-item scale (measured on a scale of 1 = strongly disagree to 5 = strongly agree) for measuring participants’ self-reported skills at finding, appraising, and using health related information available on the internet. Higher scores represent higher perceived digital literacy, while lower scores indicate lower perceived literacy. The eHEALS has demonstrated considerable reliability and validity in studies performed in various settings (countries with different profiles of resources) and social groups (college students, undergraduate nurses, older adults). It was translated in different languages and was also adapted by some authors, limiting it to specific resources as COVID-19 resources instead of general health resources as contained in the original instrument [ 56 ] or particular topics such as digital dietary literacy [ 55 ]. Although eHEALS is frequently used, it is increasingly recognized that the success or failure of health information systems depends upon a match between the system demands and the end user’s level of electronic health literacy [ 59 ]. At the same time, it’s necessary to take into account that scales used in most studies are not objective measures. Sometimes self-evaluation could skew the findings as self-evaluated digital competencies do not translate into the efficacy of computer use [ 56 ]. As the relationship between self- perception and actual behavior is often weak, it would be important to ask not only for self-report about a skill but also skill demonstration as well [ 61 ]. At the same time, it’s necessary to consider that in some studies [ 20 ] the scales used were not validated and that none of the instruments had a specific cut-off to define poor digital literacy.

The complexity of the interaction between digital literacy, health literacy and health outcomes as well as the design of the studies reviewed, mostly voluntary surveys or interviews, did not allow for a strong identification of the effects of digital literacy on the outcomes for specific pathologies. Guo et al [ 51 ] aimed to demonstrate the relationship between eHealth literacy (eHL), mobile health literacy (mHL), and health outcomes, particularly HbA1c, in a sample of Taiwanese patients with type 2 diabetes. The study found that mobile eHL had a direct effect on self-care behavior as well as knowledge and skills of computers, the internet, and mobile technology, and had an indirect effect on health outcomes (glycemic control and self-rated health status). In statistical terms, higher mobile eHL cannot be assumed to reduce HbA1c in this study.

Instead, most general consequences could be identified according to the patient´s perspectives like decreased access to health care portals, increased wait time for medical appointments, inappropriate use of emergency services, and preventative care coordination. In this sense, poor digital literacy has the potential to worsen most healthcare outcomes.

At the same time, several authors propose that higher digital literacy could be correlated with better quality of life, health promotion and mental health [ 2 , 55 , 63 , 64 , 66 , 69 ]. G Kim et al [ 66 ] found that eHealth literacy was the strongest predictor of health behaviors after adjusting for sociodemographic and health-related characteristics. These findings indicate that eHealth literacy can be an important factor in promoting individual health behaviors.

Although most of the analyzed publications propose different strategies to improve digital literacy, we could find only 7 studies that reported interventions addressing the topic. These interventions can be divided into 2 categories: provision of education and training, and social support. Under education and training, massive open online courses, university training in e-health through tutoring, and online video-based portal training were reported to improve digital health literacy of both children and adults. On the other hand, social support from technology-savvy family members, professionals, and peers were shown to improve digital health literacy of adults and older adults.

According to the patient´s perspectives, instruction needs to be simple particularly for older adults or individuals with cognitive impairments such as memory loss. Patients recommended educational institutions such as universities and health care organizations as good venues for hosting workshops, ongoing classes, and even a dedicated technology help desk in clinics where patients and family members could learn how to navigate their online patient portals in-person, conduct a video visit, and use technology in general. Additionally, synchronous (eg, a phone line) and asynchronous (eg, preparatory instructional videos and written information) remote learning resources can help patients overcome technology issues related to video visits or the use of patient portals. Several patients also envisioned having technology champions and coaches directly in their community. In-person training was preferred because it was considered more relatable and easier to understand. Surprisingly, scarce literature is available that evaluates interventions based on the patient´s perspectives.

In order to address the impact of digital divide on overall health outcomes, we need to gain greater knowledge about patients´digital health literacy and design strategies based on their perceived needs. Ensuring technology access is only 1 facet of the divide, improved technology design and training are critical for improving patients’ digital health literacy. Future work should be focused on better quality studies that could assess digital literacy based on objective measures of skills and not only on the patient’s self rated measures.

Strategies to improve digital literacy should be designed taking into account patients’ perspectives and their effect needs to be evaluated in high quality research that could measure not only the initial improvement but also its sustainability over time.

Digital health information resources and digital interaction with providers have great advantages with the potential to improve the efficiency, quality and reach of healthcare systems while empowering the patient. However, it is very important that commitment to this strategy leaves no one behind. Ethnic minorities, the elderly and patients of low socioeconomic status are at risk of having low digital literacy and, therefore, of having increasing difficulty accessing healthcare as the wave of digital health unfolds.

Increased interest in this issue in the form of publications is a good starting point but there is a need to improve measurement tools, broaden the geographic diversity of studies, as well as insist on the creation, deployment and validation of interventions aimed at reducing poor digital health literacy.

Supporting information

S1 prisma checklist. prisma checklist..

https://doi.org/10.1371/journal.pdig.0000279.s001

S1 Text. Search Strategy: Master Medline (Ovid) strategy.

https://doi.org/10.1371/journal.pdig.0000279.s002

S1 Template. Template of the standardized data collection form.

https://doi.org/10.1371/journal.pdig.0000279.s003

S1 Data. Data used to construct Figs 1 and 2 .

https://doi.org/10.1371/journal.pdig.0000279.s004

S1 Table. Summary of included studies.

https://doi.org/10.1371/journal.pdig.0000279.s005

S2 Table. Concepts related to digital health literacy and corresponding theoretical framework in the included studies.

https://doi.org/10.1371/journal.pdig.0000279.s006

S3 Table. Assessment tools for digital health literacy.

https://doi.org/10.1371/journal.pdig.0000279.s007

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Exploring eHealth implementation: understanding factors affecting engagement and enrolment in consumer digital health

O'Connor, Siobhan Marie (2020) Exploring eHealth implementation: understanding factors affecting engagement and enrolment in consumer digital health. PhD thesis, University of Glasgow.

Introduction At the dawn of the 21st century, ageing populations combined with rising numbers of people with chronic conditions are placing burdens on patients, carers, professionals, and health systems worldwide. Digital health interventions (DHIs) such as mobile, online, wearable and sensor technologies are being used to promote healthy lifestyles and encourage self-management of disease in an effort to address some of these global health challenges. However, these kinds of electronic tools can be difficult to implement. Engaging patients, the public and health professionals in digital health and getting them signed up to these technologies can be challenging in real-world settings.

Aim The primary aim of this thesis is to examine the barriers and facilitators affecting engagement and enrolment in consumer digital health interventions. It examines these complex processes from the perspective of three key stakeholder groups: 1) patients and the public; 2) health professionals; and 3) those implementing the technologies. The secondary aim is to identify the strategies used to engage and enrol individuals in consumer DHIs.

Methods An exploratory, multi-method qualitative study design was adopted. This included a qualitative systematic review and collection and analysis of primary and secondary qualitative data, gathered as part of a large (£37 million) digital health innovation programme called Delivering Assisted Living Lifestyles at Scale (dallas). The dallas programme deployed a wide range of digital health products and services in the United Kingdom ranging from telehealth and telecare systems through to mobile health applications, personal electronic medical records, and online health and wellbeing portals. These were deployed among patients with chronic illness and healthy people providing an ideal opportunity to study engagement and enrolment in DHIs. The systematic review explored the experiences of patients and the public when engaging with or signing up to DHIs. Primary data collection during the dallas programme consisted of fourteen interviews and five focus groups with patients, carers, clinicians, and those implementing the various technologies. Secondary analysis was undertaken of forty-seven baseline, midpoint, and endpoint interviews with stakeholders implementing the DHIs during the dallas programme. All analyses followed the framework approach to identify key themes and subthemes. This was underpinned by Normalization Process Theory (NPT) to synthesise the findings and develop a conceptual model of digital health engagement and enrolment.

Findings A wide range of factors affected engagement and enrolment in DHIs for the three stakeholder groups. Where patients or the public were concerned, four themes emerged from the systematic review. These were; 1) personal agency and motivation, 2) personal lifestyle and values, 3) engagement and enrolment approach, and 4) quality of the DHI. A preliminary Digital Health Engagement Model (DIEGO) was developed along with an initial catalogue of engagement and enrolment strategies. The results of the dallas programme expanded on the barriers and facilitators influencing patient and public engagement and enrolment in digital health. The main themes that arose were; 1) personal perceptions and agency, 2) personal lifestyle and values, 3) digital accessibility, 4) implementation strategy, and 5) quality of the DHI. For health professionals, three overarching themes came to light; health professional role, health service organisation and culture, and digital infrastructure. Those implementing digital health products and services were slightly different as two main themes, each of which has several subthemes, appeared to affect engagement and enrolment in DHIs. These were organisation of engagement and enrolment, and implementation strategy. Hence, the conceptual model highlighting key issues affecting patient and public engagement and enrolling in DHIs was refined and developed further based on the findings from the dallas programme. In addition, the initial catalogue of engagement and enrolment strategies was extended.

Conclusion This thesis provides new insights into the digital health implementation process, in particular the early phases of engagement and enrolment. A preliminary conceptual framework of digital health engagement and enrolment, the DIEGO model, was developed which summarises key issues that need to be considered during the earliest stages of implementing digital health products and services. This new framework could help researchers, clinicians, businesses, and policy makers appreciate the dynamics of deploying digital interventions in healthcare. This work suggests that educating patients, the public, and health professionals about the benefits, risks, and limitations of health technology is needed, while supporting research that describes engagement and enrolment strategies for consumer digital health and examines their effectiveness. Implementation teams could benefit from building strategic partnerships with marketing specialists and third sector agencies, and having clear business plans and budgets to enhance the reach and impact of engagement and enrolment in digital health. A positive digital health culture also needs to be cultivated in the health service, with leaders that champion the appropriate use of technology. National policies and funding that supports health informatics education, digital literacy for citizens, and digital infrastructure may also be necessary to enable people to sign up for DHIs. These recommendations may help support implementation and improve uptake to digital health products and services in the future.

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• Open access
• Published: 12 February 2022

Towards digital health equity - a qualitative study of the challenges experienced by vulnerable groups in using digital health services in the COVID-19 era

• Anu-Marja Kaihlanen 1 ,
• Lotta Virtanen 1 ,
• Ulla Buchert 2 ,
• Nuriiar Safarov 2 ,
• Paula Valkonen 3 ,
• Laura Hietapakka 1 ,
• Iiris Hörhammer 4 ,
• Sari Kujala 3 ,
• Anne Kouvonen 2 , 5 &
• Tarja Heponiemi 1  

BMC Health Services Research volume  22 , Article number:  188 ( 2022 ) Cite this article

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The COVID-19 pandemic has given an unprecedented boost to already increased digital health services, which can place many vulnerable groups at risk of digital exclusion. To improve the likelihood of achieving digital health equity, it is necessary to identify and address the elements that may prevent vulnerable groups from benefiting from digital health services. This study examined the challenges experienced by vulnerable groups in using digital health services during the COVID-19 pandemic.

Qualitative descriptive design was utilized. Semi-structured interviews were conducted between October 2020 and May 2021. The participants ( N  = 74) were older adults, migrants, mental health service users, high users of health services, and the unemployed. Qualitative content analysis with both inductive and deductive approach was used to analyze the data. Challenges related to the use of digital health services were interpreted through digital determinants of health from the Digital Health Equity Framework.

For most of the participants the access to digital health services was hampered by insufficient digital, and / or local language skills. The lack of support and training, poor health, as well as the lack of strong e-identification or suitable devices also prevented the access. Digital services were not perceived to be applicable for all situations or capable of replacing face-to-face services due to the poor communication in the digital environment. Fears and the lack of trust regarding digital platforms were expressed as well as concerns related to the security of the services. Contact with a health care professional was also considered less personal and more prone to misunderstandings in the digital environment than in face-to-face services. Finally, digital alternatives were not always available as desired by participants, or participants were unaware of existing digital services and their value.

Several development needs in the implementation of digital health services were identified that could improve equal access to and benefits gained from digital services in the future. While digital health services are increasing, traditional face-to-face services will still need to be offered alongside the digital ones to ensure equal access to services.

Peer Review reports

Introduction

The COVID-19 pandemic has placed health care systems globally in an unprecedented position. The sudden spread of COVID-19 cases have required urgent actions and extension of services to digital form to maintain health care operations and reduce face-to-face encounters [ 1 , 2 ]. The variety and the number of digital health services has increased significantly over the past decade already before the pandemic, but it has been argued that the COVID-19 crisis will revolutionize the delivery of health services through digital technology [ 3 , 4 ].

Although the purpose of digital health services is to enable the availability and continuity of services during the pandemic, everyone does not have an equal opportunity to benefit from digitalization. The rapid digitalization of health services has posed a considerable risk of increasing digital inequality, which in turn may cause significant disadvantages such as an increased risk of health deterioration, exposure to COVID-19 if the necessary services cannot be obtained remotely, and social isolation, especially for those who already are in a vulnerable position [ 2 , 5 , 6 , 7 ]. Concerns have been raised about whether particularly those, who may not have equal access, ability or resources to use digital services have received the health services they need [ 5 , 8 , 9 ].

The aim of this qualitative study was to examine the challenges experienced by vulnerable groups in using digital health services during the COVID-19 pandemic. In this study, digital health services refer to electronic transactions related to health care, such as remote visits with professionals via video call, chat service or phone call, electronic health records, electronic symptom assessments, websites providing health-related information, health applications, or appointment booking system.

• Digital health equity

Facilitating appropriate use of digital technologies without leaving anyone behind, thus ensuring digital health equity is one of the guiding principles in the WHO global strategy on digital health 2020-2025 [ 10 ]. Digital health equity can be defined as an equal opportunity for individuals to benefit from the knowledge and practices related to the development and use of digital technologies to improve health [ 10 , 11 ]. Inequity in society is reflected in digital health equity, thus, those at risk of social exclusion (ie, those at a disadvantage due to, for example, unemployment, low education, and a weak economic situation) are also at greater risk of being excluded from digital health services [ 12 , 13 ].

The realization of digital health equity is closely linked to realization of “digital determinants of health” [ 10 ], which, in turn, reflects the socio-economic and socio-cultural context of individuals and the intermediate health factors [ 11 ]. The Digital Health Equity Framework (DHEF) by Crawford and Serhal [ 11 ] defines the digital determinants of health as (1) individuals access to digital resources, (2) use of these resources for health seeking, (3) digital health literacy, (4) beliefs about the potential help or harm of digital health care, (5) values and cultural preferences regarding the use of digital resources, and (6) integration of digital resources into community and health infrastructure. In order to improve the likelihood of achieving digital health equity, there is a need to identify and address potential gaps in digital determinants, in particular from the perspective of those who are at risk of being excluded from digital services.

Vulnerable groups as digital health service users

Previous literature has highlighted the need for public services to address the needs of vulnerable groups, those who are disadvantaged by health, economic, cultural or social conditions [ 14 ]. The key vulnerable groups include older people, migrants, mental health service users, high users of health services and the unemployed.

Older adults are the largest individual group that faces challenges in using digital health services [ 15 , 16 , 17 ]. Inexperience in the use of technology, poor motivation, financial difficulties, and insufficient technical skills have been shown to hinder older peoples’ opportunities to benefit from digital health services. In addition, poor health, cognitive decline, the lack of appropriate devices or internet access, and inadequate support and guidance, may prevent older people from using digital health services [ 15 , 16 , 17 ].

Migrants, with varying reasons for entering the country, such as family reasons, work, or refugee status, constitute an increasing group that can experience challenges in using digital health services in their new home country. Disparities have indeed been identified in digital health and in migrants’ access to digital health services in different societal contexts [ 18 , 19 , 20 ]. Previous studies have found, for example, that migrants and ethnic minorities search for health information online less often than the general population [ 6 , 21 , 22 ]. Migrant background has also been associated with lower understanding of the web-based health information [ 23 ].

The ‘high users’ of health services often have a chronic disease or disability requiring regular health check-ups and care. This group can be at a risk for digital exclusion as poorer health has been associated with lower levels of interest in digital health [ 24 ] and perceived benefits of its use [ 25 ]. Additionally, the evidence suggests that health systems do not sufficiently offer digital health for their complex health needs [ 26 ].

Another group whose well-being and continuity of care has been particularly at stake during the COVID-19 pandemic due to the avoidance of physical contact is mental health service users [ 27 ]. Poor mental health has been associated with negative attitudes towards digital health services, posing mental health service users, or those in the need of mental health services, at risk of digital exclusion [ 28 ]. Those with more severe mental disorders may also experience cognitive impairments that hamper the use of digital services and perpetuate digital exclusion alongside lack of digital skills or financial resources [ 29 , 30 ].

The unemployed represent another group that is under the threat of digital exclusion. For example, Helsper and Reisdorf [ 13 ] have discovered, that the unemployed is one group that is likely to include Internet non-users. Reasons for this include lack of access, skills and financial resources but also motivational reasons such as lack of interest in the Internet. A Finnish study discovered that unemployed persons are lacking skills for using digital health services and use digital services less often than others [ 31 ].

The present study

Obtaining up-to-date information on the experiences of vulnerable groups about the challenges related to the use of digital health services is paramount because the perspective of these groups has not yet been adequately addressed during the COVID-19 pandemic [ 5 ]. This task is important even if the COVID-crisis subsides, since the effects of the crisis on health are likely to be felt long after the pandemic. It is also likely that the provision of digital services will continue to grow alongside or instead of the traditional face-to-face services. While those at risk of digital exclusion are not a homogeneous group, qualitative interviews exploring the experiences of different groups and communities and thereby actively involving them is essential for the development of future digital services.

The aim of this qualitative study is to examine the challenges experienced by vulnerable groups in using digital health services during the COVID-19 pandemic.

The identified elements are viewed and synthesized by utilizing the DHEF framework [ 11 ].

In Finland, universal access and patients’ equal rights to public health services are defined by law [ 32 , 33 ]. In 2019, Finland also enacted a law on the provision of digital services, which aims to promote their availability, quality, information security and equal opportunities for people to use digital services [ 34 ]. Although Finland is a high-income country with advanced health policy programs, there are health inequalities related to socio-economic status. This is reflected in higher levels of morbidity and mortality in vulnerable groups, who often have cumulative social disadvantages, such as low levels of education, low income, and unemployment [ 35 , 36 ].

Public health services are divided into primary health care and special medical care, of which primary health care refers to health center services organized by municipalities, including the promotion of the well-being and health of the population and the prevention, diagnosis and treatment of diseases. In addition, health services are provided by private service providers including occupational health care. The third sector complements the provision. Their main tasks include the organization and implementation of volunteering and assistance work, as well as the provision of health services and related development activities complementing public services. Due to their typically having low income, vulnerable groups tend to rely on public health services and the third sector.

Finland is one of the forerunners of digitalization [ 37 ]. However, according to Statistics Finland, in 2019 up to 10% of the population did not have a computer at home, 17% did not own a smartphone and 8% did not have access to the Internet. Admittedly, in 2020 a considerable increase was seen in the use of the Internet for social networking and communication in Finland, especially in the oldest age groups [ 38 ], most likely due to COVID-19 crisis and the restrictions that forced social interaction online, pushing people to learn new social media skills. However, the ability to use the Internet does not necessarily imply an ability to use digital health services: a recent population survey (conducted during the COVID-19 pandemic) showed that only 22% of Finnish adults had communicated digitally with a social or health care professional [ 39 ].

This study was carried out as part of the DigiIN research project, funded by the Strategic Research Council, which aims to create solutions which will ensure that the social welfare and healthcare sector’s digital services are available and accessible to everyone. The authors are researchers of the project and are not involved in the provision or actual development of digital health services.

Study design

The research design was a descriptive qualitative study based on semi-structured individual interviews among five vulnerable groups at risk for digital exclusion.

Recruitment of participants

The recruitment process varied by group (detailed information is provided in Table S1 in Additional file  1 ). Participants were mainly recruited through a convenience sampling from third sector organizations that provided services for the target groups across Finland. With the help of the organizations, we forwarded an invitation letter to their clients, and those interested contacted the researcher, or the organizations delivered the client’s contact information to the researcher with the client’s permission. Some participants were reached through an online event or social media channels of the organizations, Facebook groups aimed at target groups, or using snowball sampling. As an exception, we reached high users by random sampling ( n  = 100) from the register data of one Finnish municipality. We mailed an invitation letter to these randomly selected persons, after which the researcher called everyone and inquired about their interest in participating. For participation in all groups, a small thank-you gift and an opportunity to participate in a lottery on a tablet computer were offered.

The participants ( N  = 74) were older adults ( n  = 16), older Russian-speaking migrants ( n  = 6), mental health service users ( n  = 12), high users of health services ( n  = 17), the unemployed (n = 16), and Russian-speaking unemployed migrants ( n  = 7). Russian speakers are the largest migrant group in Finland [ 40 ]. Most participants in the groups were women, except high users included more men. On average, the oldest participants (mean 75.4 years) were in the group of older people while mental health service users were on average the youngest (mean 30.7 years). Mental health service users, older migrants, and unemployed migrants had typically a higher education degree while the others most often had a secondary education. The life situations were heterogeneous within and between groups. Detailed information about the participants can be viewed in Table S2 in Additional file 1 .

Data collection

Data were collected using a semi-structured interview guide (Text file S1 in Additional file 1 ), jointly produced by the research group. The participants were told about the definition of digital services with concrete examples in the context of the Finnish health services. We asked questions such as what kind of experiences participants had about digital services during the pandemic, whether they perceived benefits from digital services or possible reasons for not benefiting, and how they considered that digital services could be developed. We piloted the interview guide with one older person and three mental health service users. No major changes were required to the interview guide, so the pilot interviews were included in the study with the permission of the participants.

Individual interviews were conducted by phone between October 2020 and May 2021 (the second and third waves of the COVID-19 pandemic in Finland). Each group of the participants had their own interviewer. The other groups were interviewed in Finnish but the migrants were interviewed in their native language Russian. The interviews were recorded into digital audio recordings with the permission of the participants. The mean length was 39 min (range 16–90 min) with the longest on average in older adults and shortest in high users. Transcription companies transcribed the recordings, resulting in a total of 1044 pages of transcribed text (Times New Roman font size 12, line spacing 1.5). The Russian transcripts were translated into Finnish for analysis.

Data analysis

We applied inductive and deductive content analysis to analyze the qualitative data [ 41 ]. The combined approach allowed us to first identify emerging themes in the data and then synthesize the findings using an existing framework [ 11 ] to develop a deeper understanding of the phenomenon.

The data analysis included three iterative steps of data reduction, grouping, and abstraction [ 41 ]. The unit of analysis was a set of ideas in which the participant described challenges related to digital health services. In the data reduction, researchers (LV, PV, LH, JK, UB) read through the transcripts and used open coding to summarize the set of ideas as accurately as possible. Each researcher coded the interview transcripts of one vulnerable group, whose interviews they had also conducted. Except for the migrants, whose interviews were conducted by one researcher in Russian, and another researcher coded the data after it was translated into Finnish. Codes were then separately grouped within each client group based on similarity and given a descriptive name. These subcategories ( n  = 44) were then reviewed by one researcher (A-MK) who further categorized them into upper categories ( n  = 6) that were retrieved from the digital determinants of health of the DHEF [ 11 ]. Discussions were held with the research group about the categorization to reach a consensus.

In the Results section, we provide direct quotations from the interviews (translated from Finnish into English).

The elements related to digital determinants of health that challenged the opportunities of vulnerable groups to benefit from digital health services were partly congruent, but also unique. The group-specific challenges for each determinant are presented separately in Table  1 and results are summarized in the following sections.

Access to digital resources

For the most participants, access to digital health services was hampered by insufficient digital skills, language skills, or both. In addition, a lack of support and training, poor health, and the lack of strong e-identification or suitable devices required for digital services prevented the access.

Regardless of age, the participants felt that the use of digital health services required significantly higher-level digital skills compared to the skills required to use every day digital devices and applications.

Especially for many older participants, poor basic computer skills and the lack of devices were considerable barriers to access digital health services. However, there were large differences in skills, and some older participants were able to use computers and smart devices completely fluently.

“These digital gadgets require a lot of competence, a lot of knowledge, skills that people in my age don’t naturally have. Such competence, know-how. That’s a bad thing. The terminology is unfamiliar, I don’t even understand the questions of what’s out there.” (Older adult, 69 years)

Older participants felt that they did not receive enough guidance on how to take advantage of digital health services. In the past, voluntary support and computer assistance had helped many older adults to access digital services, but due to the COVID-19 pandemic, many of the trainings or digital support had been canceled or converted into online remote events. Participants experienced difficulties in finding or joining these remote support events or existing equipment did not allow participation.

Some high users also described that learning digital skills to access digital health services was too demanding and time- and energy-consuming. Simultaneously, they raised concerns that they might fall out of a digitalizing society because they felt that their current life situation did not allow for learning.

Then I’ll fall out completely if I’m not there. It arouses fear and anxiety if you think about it. I’ve so much of everything else, I can’t get acquainted. I must manage to focus on and delve into it, then I’d learn those digital services. If someone were teaching nicely. But I should have enough strength to focus on the thing that I have enough strength to learn it. I should take time for that. (High user 15, 55 years)

High users and mental health service users also described that they had ability to access certain health services but considered access challenging to others, mostly due to problems in usability or language. Some participants described that they could not access the digital services at all independently.

Inadequate local language skills were shown to be a major barrier to migrant participants’ use of digital health services. Even booking appointments remotely using the Finnish language proved difficult for some participants. Moreover, in Finland, to be able to use digital public services one must have a strong electronic identification (e-ID). Obtaining an e-ID is not straightforward to non-EU migrants.

“In mastering language and computer, that’s my difficulty. My main challenge, yes, because you must use the language remotely, filling out the forms correctly, there you need to answer the questions, but you just don’t always succeed in it correctly. I use a translator for some things, translate something myself with the help of a dictionary but the translations aren’t always very accurate. There you’re afraid to make a mistake because it’s an official document.” (Older migrant, 72 years)

The migrant participants also pointed out that the use of digital services does not only demand a high level of local language skills, but also require mastering of specific administrative and medical vocabulary. This experience was shared by Finland-born older adults and high users who thought that services can include too difficult language or professional vocabulary.

For high users, poor health seemed to particularly challenge the use of digital health services. For example, some explained that they had even had a career in IT, but memory impairment had complicated keeping up with the changes and learning. A language disorder was a perceived barrier to use remote health consultations because the expression of service needs was considered more difficult without physical presence. Visual impairment was also described to challenge on-screen reading, and therefore, interviewees had preferred obtaining health information in a letter or they had printed it from a digital service on paper for reading. For some older participants, having a hearing disability also reduced the desire to use phone as a remote option.

For some of the participants, such as the unemployed and older adults, the lack of suitable devices, due to financial reasons or problems with the devices’ functioning at home for example, hindered significantly their possibilities to use and benefit from digital health services. Because of these device issues, some of the participants had been forced to seek services elsewhere.

The use of digital resources for health seeking

The participants highlighted that digital services were not applicable for all situations. Many of the participants experienced challenges related to the nature of communication and poor interaction in the digital environment.

Face-to-face services were perceived as a more effective in handling more demanding and complex matters, whereas, easy-to-do, or routine-like issues, such as booking appointments and checking the health records online were considered as more doable digitally. However, communicating was not always possible in services.

” The thing that annoys me in the My Kanta pages [where you can see your own health records] is that they are not reciprocal. You cannot comment anything there even if you find a clear mistake in the text written by a physician. They could add some chat function somewhere in there to enable commenting.” (Unemployed, 45 years)

Among migrant participants, the complexity of the health issue was also interconnected with local language skills. Face-to-face meetings were thought to reduce the misunderstandings because they provided the possibility to clarify the issue, ask questions, and also increased the experience that their health issue was properly understood. Similar experiences were expressed by high users and mental health services users, who felt that visiting the service physically would allow the professional to ask, see, and feel the situation comprehensively.

Poor interaction was considered as one of the major barriers to benefitting from digital services among the mental health service users. Some perceived it difficult to express their health service needs remotely. Mental health service users also felt that digital mental health consultations lacked warmth and the conversation felt distant without facial expressions and tones. Some described that in the remote group therapy sessions, people talked easily on top of each other, and therefore, the health professional had to assign turns to speak, which disturbed the natural rhythm of the conversation.

Some participants also described that using digital health services at home in the presence of another person (such as remote consultations or therapy sessions) was challenging and did not allow for privacy.

“We had a situation where I was at home with our child. How can you focus on discussing when you have a toddler rolling around? We also have a small home, so we do not have a place where I could lock myself into so that nobody is listening.” (Unemployed, 34 years)

Digital health literacy

The present study used the definition of digital health literacy as the degree to which individuals have the capacity to obtain, process, and understand basic health information from electronic sources to make appropriate health decisions [ 42 ]. Based on this definition, digital health literacy was not an issue that participants would have raised as a challenge.

Beliefs about potential of digital health to be helpful or harmful

Participants commonly raised some issues and concerns related to the security of digital health services, as well as fear and lack of trust regarding digital platforms.

Particularly due to the sensitivity of mental health issues, the mental health service users perceived that they did not feel as secure to discuss these matters remotely. The smaller group sizes meant that the service users felt safer in a digital environment as the interviewees described that the more customers were present, the less comfortable they were to discuss openly about their sensitive matters.

“People might not dare to talk about such personal matters as much via a computer compared to when we would see physically. I’ve also experienced it, especially if there are several listeners. But maybe if there were only a few people online, then maybe I could dare to talk about such more personal things. If there are more, then no.“ (Mental health service user, 40 years)

Digital health platforms were not necessarily considered safe systems, which generated security concerns that the personal data might be compromised. The rapid transition from face-to-face meetings to digital service due to the COVID-19 pandemic in Finland had sometimes resulted in providing services (e.g, a service supporting mental health provided by third sector organization) on platforms that were perceived insecure. Moreover, lack of sufficient security expertise worried the participants, as they felt that they did not have the ability to protect their computer from hackers, for example. They acknowledged that their individual computer behavior might cause risks for their health data if they used health services digitally.

Fear of making mistakes while using digital health services emerged especially among the older participants and migrants. They mostly feared that when trying to use digital services, something irreversible would happen and everything would go wrong. They doubted whether they would get any support if something goes wrong with the digital service. Because mistakes were thought to lead to potential significant errors with long-term consequences, such as non-renewal of prescriptions, delays in service or treatment or compromising their health information, participants were worried about using digital services and therefore contact-based service options (especially face-to-face meetings) were favored.

” When there’s no helper, if it’s the first time you’re using the system, you’ll face an obstacle. And there it’ll stymie that you’re afraid of pressing something wrong, that the computer crashes, the programs crash. Such senility of old age. The programs are difficult for us to use.” (Older migrant, 64 years)

In addition to safety concerns, some mental health service users described digital health services as a potential harm for mental health as they perceived that compared to attending traditional face-to face appointments, digital services lack an incentive to leave the house. The older participants similarly pointed out that digital services reduced their opportunities for physical activity, which was important for their well-being.

Experiences of distrust for the quality of digital health also emerged from the interviews and some participants indicated having less confidence in digital health services than in the face-to-face services.

Values and cultural norms/preferences for use of digital resources

Interviewees widely indicated their preference for traditional face-to-face meetings over digital ones, as digital services were not seen to provide a service experience equivalent to a face-to-face encounter. Many did not see the added value of digital services.

Among the migrant participants, the preference for face-to-face appointments was strong because they valued personal communication, including gestures, facial expressions, and touches. They felt that possibilities of showing emotions and using non-verbal communication disappear in digital services. Additionally, the contact with a health care professional was considered less personalized in digital health services compared to traditional face-to-face services.

“Personally, I like to visit in person because this human factor is very important to me as a computer is a computer, but when you talk to a person face-to-face, it’s a whole different thing.” (Unemployed migrant, 49 years)

Some of the high users perceived that identifying the service needs remotely requires more time and patients’ investment compared to face-to-face services, and therefore, they preferred visiting health services physically. Some older adults also felt that remote health service options, such as phone calls, were inconvenient as they often required time and waiting in line.

“Preferably I’d go physically to the service. There they’ll check the situation comprehensively. That I can say all things out. It’s possible even remotely, but it takes more time to discuss everything through calmly. (High user, 55 years)

Some older adults had doubts about treating health issues remotely, and things were thought to be handled worse or not at all compared to face-to-face services. In this group, lack of interest to use a computer or smartphone was also common. High users and the unemployed shared their thoughts and feelings about digital health services which tended to be negative irrespective of their level of digital skills. The participants often explained their attitudes by having an “old-school mind” and their habit of using health services physically.

Additionally, digital health services were not seen to have an added value when the participants repeated the view that living close to a health care center or a visit by a health care professional in a sheltered housing provided an easy access to care and created no need to use health consultations remotely.

Integration of digital resources into community and health infrastructure

The challenges associated with integrating digital resources into health infrastructure were mainly related to either the fact that digital alternatives were not always available as desired by participants, or participants were unaware of existing digital service options and their value.

In particular, some of the high users hoped that service providers would better inform them about the possibilities to use digital health services. Despite the high use of health services, some had never been instructed to take advantage of different digital platforms such as electronic health records. Moreover, it seems that in some cases, there was actually no option provided to a patient to use a health service remotely at all. Indeed, some of the mental health service users and the unemployed wondered why the public health sector did not provide more options to use services remotely, such as making appointments online or having health consultations via video call.

Among the migrant participants, one key challenge that emerged was that only some of the webpages were available in the participants’ mother tongue, Russian, despite Russian being the most widely spoken native language in Finland after Finnish and Swedish. Relevant information was difficult to find on the websites and the information was provided in a difficult to understand, not intuitive manner.

In this study we investigated the challenges experienced by vulnerable groups in using digital health services during the COVID-19 pandemic. Given the significant emphasis on the role of digital health services during the pandemic, which may also have increased health inequalities [ 2 , 5 , 6 ], this study provides valuable up-to-date information on those groups at particular risk of digital exclusion.

Principal findings and comparison with prior work

The results of this study indicate that vulnerable groups experienced problems with many digital determinants of health. The most obvious barriers to using the digital health services were the various challenges related to access to digital resources. The most typical challenge was that individuals, regardless of the age or group, felt that their skills were insufficient to access the services. Previous studies have also identified that inadequate digital skills widely affect vulnerable groups and the problem is not limited to older adults [ 26 , 43 , 44 ]. In contrast to previous studies, the notable finding of this study was that individuals may have good digital skills as such, and they may use the Internet and social media several times a day, but these skills did not seem to guarantee the ability to cope with the use of digital health services. This was mostly due to poor usability, difficult vocabulary in the services, or weak local language skills. This finding is in line with previous findings showing these factors as significant barriers to adoption of digital health services among different vulnerable groups [ 22 , 23 , 43 , 45 , 46 , 47 ]. In addition to the previous studies showing that migrants struggle with the difficult-to-understand language of the services, our results show that this challenge also affected those who spoke native language.

Weak digital skills were often linked to another common problem in access to digital resources: experiencing inadequate and difficult-to-find support for service use. Although this need for support and technical assistance has been discussed for years [ 48 , 49 ], it appears that despite the constant increase in digital services, support is still not adequate or appropriate for different users.

Not having an e-ID was a considerable barrier for some migrant participants. In Finland, as in other Nordic countries, having an e-identification is a prerequisite for using digital health services and the e-ID system relies mainly on online-banking identification methods [ 50 , 51 ]. To be able to authenticate in digital services, migrants from outside the EU must apply for a Finnish ID card first, and then apply for the possibility to have e-ID linked to their banking identifiers. This authentication problem has been noted previously, as in 2018, 98% of the general adult population in Finland were reported to have e-ID, while only 88% of migrant adults had it [ 52 ].

Participants commonly experienced that communication-related weaknesses prevented their use of digital resources for health care seeking. Due to poor communication, digital health services were not yet perceived to be able to meet complex service needs or the health issue were not seen to be fully addressed at once. Previous research has found similar kind of results showing that lack of interaction poses challenges to digitalization especially in mental health services, where patient-professional dialogue and interaction play a key role [ 53 , 54 , 55 ]. However, our findings add to these indicating that communication challenges in digital services can affect various service users and the challenges experienced also vary for different user groups.

An increased use of digital health services is known to increase the risk of security and privacy vulnerabilities [ 56 ]. This seemed to be a concern also in this study as the most typical belief about the potential harm of digital health. For many, fear and lack of trust hampered the use. This is in line with previous studies stating that security, privacy, and confidentiality concerns are considerable barriers to accessing digital health services for various vulnerable groups, such as mental health service users, people with multimorbidity, or older adults [ 24 , 26 , 49 , 53 , 55 ]. However, our results also emerged that the safe use of digital services require external resources for the private and confidential environment in which the service is used. We showed that privacy and confidentiality issues can be especially visible for those who are unable to use digital health services in private place or independently when sensitive information may need to be shared with another.

This study showed that traditional face-to-face health services are often valued and preferred over digital services. Some participants admitted to having a low motivation towards digital solutions, which is why the threshold for using digital services was partly high. The importance of attitudes and motivation in benefiting from digital services has been highlighted in previous studies as well [ 13 , 47 , 57 ]. Participants’ attitudes may have been influenced by the fact that many of them did not know that digital services were available and worth using. Thus, it seems that knowledge of digital services and their potential to promote health and well-being does not yet seem to reach everyone.

Practical implications: areas for the development of digital health services

Mitigating strategies such as increasing physical access, digital skills and social support and improving the digital remote support infrastructures have previously been proposed to reduce digital inequalities and increase the use of technology and digital services [ 5 , 6 ]. Moreover, the importance of hybrid strategies, including both high- and low-tech perspective and combination of online and offline strategies has been highlighted [ 2 ]. Based on the identified challenges experienced by vulnerable groups, we are able to suggest several areas for development that could improve the more equitable accessibility of digital health services. Development must focus both on better usability of digital services and on the opportunities and ability of individuals to benefit from them. Figure  1 illustrates the areas for development, which are described in more detail in Additional file  2 .

Suggestions for development to improve the accessibility of digital health services and increase digital health equity

Strengths and limitations

The main strength of this study is the large and diverse group of participants who are at a particular risk of being excluded from digital health services. The data collected during the COVID-19 pandemic also provide very up-to-date and unique information on the experiences of these vulnerable groups at this exceptional time. The fact that we did not directly ask the participants about the challenges related to certain digital determinants of health, but instead gave them a more open opportunity to raise the most important challenges for themselves, may have affected the content of the results. For example, it is possible that if we had asked directly about the challenges related to digital health literacy, the participants could have described them. Although in this study we looked at the participants’ experiences as part of the vulnerable group in which they were recruited, in practice the challenges related to digital services also varied within the groups. This shows that there are no convergent vulnerable groups, but individuals with individual needs and challenges.

We did not conduct a ‘member checking’ and ask participants to check the accuracy of the results in relation to their experiences, which would have increased the credibility of the results. However, the key strength of this study is researcher triangulation, as several researchers participated in the implementation of the study and in the analysis and interpretation of the data and findings. This allowed for a broad examination of the phenomenon and strengthens the validity of the results [ 58 ].

Conclusions

This study reinforces the view that not all people have been equally able to access and benefit from digital health services during the COVID-19 pandemic. Our results suggest that the major problems in accessing digital health services seem to be related to individuals’ access to digital resources, although, this study identified significant challenges in other digital determinants as well. There are several reasons for digital exclusion, such as insufficient digital skills or local language skills, or the fact that the use of digital services requires such effort and resources, which may be too much for some in their life situation. The health care needs of vulnerable people may also be complex and digital health services do not yet appear to be fully responsive to needs that require close interaction or clarification. In the future, it will be important to invest in information about digital health services through various channels because the opportunities and potential benefits of these services has not been disseminated widely enough to reach everyone. Moreover, traditional face-to-face health services will continue to be important and should still be maintained and provided alongside digital health services as there will always be people (eg, older adults with cognitive decline or sensory impairments, and illiterate migrants) who are not able to use digital health services.

Availability of data and materials

The datasets generated and analysed during the current study are not publicly available for the protection of the anonymity of the participants but are available from the corresponding author on reasonable request.

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Acknowledgements

We would like to express our great gratitude to all the persons who participated in the interviews as well as to those who assisted in the recruitment of the interviewees. Thank you also BSocSci Juuso Kilpinen and BSocSci Tatiana Glushkova for collecting the data and coding the interview transcripts.

This study was funded by the Strategic Research Council at the Academy of Finland (projects 327145, 327148 and 327147); THL coordinated funding for COVID-19 re-search included in the Finnish Governments supplementary budget; and the Academy of Finland [grant nos. 312310 and 336669] for the Centre of Excellence for Re-search on Ageing and Care RG 3 Migration, Care and Ageing. None of them had any role in the design of the study and collection, analysis, and interpretation of the data or in the writing.

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Substantial contribution to study conception and design: A-MK, LV, UB, NS, PV, LH, IH, SK, AK, TH. Data analysis: A-MK, LV, UB, PV, LH. Drafting of the manuscript: A-MK, LV, UB, NS, PV, LH, IH, SK, AK, TH. All authors read and approved the final manuscript.

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Supplementary Information

Additional file 1: table s1..

The eligibility and recruitment process of the participants. Table S2. The demographics and description of the study participants. Text file S1. The interview guide.

Additional file 2.

Descriptions on the suggestions for development to improve the accessibility of digital health services and increase digital health equity.

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Kaihlanen, AM., Virtanen, L., Buchert, U. et al. Towards digital health equity - a qualitative study of the challenges experienced by vulnerable groups in using digital health services in the COVID-19 era. BMC Health Serv Res 22 , 188 (2022). https://doi.org/10.1186/s12913-022-07584-4

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Rethinking digital transformation of healthcare: The role of technology and institutions in service innovation: Dissertation

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• digitalization
• service innovation
• innovation challenges
• institutionalisation
• healthcare renewal

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• Healthcare Keyphrases 100%
• Service Innovation Keyphrases 100%
• Digital Transformation Keyphrases 100%
• Role of Technology Keyphrases 100%
• Role of Institutions Keyphrases 100%
• transformations INIS 100%
• productivity INIS 100%
• Theses Social Sciences 100%

T1 - Rethinking digital transformation of healthcare

T2 - The role of technology and institutions in service innovation: Dissertation

AU - Wallin, Arto

N2 - Due to the mounting prevalence of chronic diseases, increasing demand for expensive treatments and the growing old-age dependency ratio, there is a pressing need to augment the productivity and quality of health and elderly care. Although the potential of digital technologies is widely acknowledged, focusing on technological innovations and incremental improvements originatingfrom the healthcare system does not appear to provide the desired results. Therefore, there is a need for innovation that breaks established rules and practices and enables systemic transformation in healthcare.This article-based doctoral thesis builds on four published studies employing abductive case research strategy: a dialogue between theory and empirical analysis. The first two studies were conducted under the framework of European innovation programmes. They explore how digitallyenhanced services improve service productivity in the elderly care setting, and provide insights intoinnovation challenges experienced during a three-year collaborative innovation project. The latter two studies focus on start-ups operating under a start-up business accelerator programme. They increase understanding of the institutional constraints experienced by entrepreneurs when developing innovations that diverge from the prevailing rules of healthcare, and of the ways in which they attempt to change the rules hindering the adoption of innovations.The thesis contributes to service research by constructing a more profound understanding of the mechanisms that advance, hinder, enable and constrain service innovation in the field of healthcare. In particular, the thesis contributes to integrating the perspective of institutional entrepreneurship in service innovation, highlighting the importance of actions that contribute tobreaking prevailing 'rules of the game' (i.e. institutions) and creating new ones. In addition, the thesis depicts how digitalization reveals the pervasive role of technology in innovation. Jointly, these contributions advance the synthesis view on service innovation – a view that highlights the importance of both technological and service aspects in innovation.The policy and managerial implications of the thesis suggest that, in addition to a complex set of institutions that guide innovation in the field of healthcare, the development context may also have a notable impact on innovation. The institutional structures of collaborative innovation programmes should encourage collaboration outside project boundaries, in order to foster theactors' awareness of the institutional and market environment. Exposing innovation to institutional forces makes it easier to comprehend the necessary institutional change and to develop ways of justifying the change to actors that are vital for its support. The institutional perspective should be more tightly linked to the practice of innovation.

AB - Due to the mounting prevalence of chronic diseases, increasing demand for expensive treatments and the growing old-age dependency ratio, there is a pressing need to augment the productivity and quality of health and elderly care. Although the potential of digital technologies is widely acknowledged, focusing on technological innovations and incremental improvements originatingfrom the healthcare system does not appear to provide the desired results. Therefore, there is a need for innovation that breaks established rules and practices and enables systemic transformation in healthcare.This article-based doctoral thesis builds on four published studies employing abductive case research strategy: a dialogue between theory and empirical analysis. The first two studies were conducted under the framework of European innovation programmes. They explore how digitallyenhanced services improve service productivity in the elderly care setting, and provide insights intoinnovation challenges experienced during a three-year collaborative innovation project. The latter two studies focus on start-ups operating under a start-up business accelerator programme. They increase understanding of the institutional constraints experienced by entrepreneurs when developing innovations that diverge from the prevailing rules of healthcare, and of the ways in which they attempt to change the rules hindering the adoption of innovations.The thesis contributes to service research by constructing a more profound understanding of the mechanisms that advance, hinder, enable and constrain service innovation in the field of healthcare. In particular, the thesis contributes to integrating the perspective of institutional entrepreneurship in service innovation, highlighting the importance of actions that contribute tobreaking prevailing 'rules of the game' (i.e. institutions) and creating new ones. In addition, the thesis depicts how digitalization reveals the pervasive role of technology in innovation. Jointly, these contributions advance the synthesis view on service innovation – a view that highlights the importance of both technological and service aspects in innovation.The policy and managerial implications of the thesis suggest that, in addition to a complex set of institutions that guide innovation in the field of healthcare, the development context may also have a notable impact on innovation. The institutional structures of collaborative innovation programmes should encourage collaboration outside project boundaries, in order to foster theactors' awareness of the institutional and market environment. Exposing innovation to institutional forces makes it easier to comprehend the necessary institutional change and to develop ways of justifying the change to actors that are vital for its support. The institutional perspective should be more tightly linked to the practice of innovation.

KW - digitalization

KW - service innovation

KW - innovation challenges

KW - institutionalisation

KW - healthcare renewal

M3 - Dissertation

SN - 978-952-60-8019-2

SN - 978-951-38-8638-7

T3 - VTT Science

PB - Aalto University

Persistent organic pollutants in the natural environments of the city of Bratsk (Irkutsk Oblast): Levels and risk assessment

• Degradation, Rehabilitation, and Conservation of Soils
• Published: 06 November 2014
• Volume 47 , pages 1144–1151, ( 2014 )

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• E. A. Mamontova 1 ,
• E. N. Tarasova 1 &
• A. A. Mamontov 1  

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The contents of persistent organic pollutants (POPs)—polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs)—in the natural environments of an industrial city (Bratsk) of Irkutsk oblast have been studied. Features of the spatial and seasonal distribution of the PCBs and OCPs in the soils and the atmospheric air have been revealed. The structure of the homological and congeneric composition of the PCBs in the soils and the atmospheric air has been shown. Parameters of the carcinogenic and noncarcinogenic risks for human health from the impact of the PCBs and OCPs present in the soils and the atmospheric air have been determined.

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Original Russian Text © E.A. Mamontova, E.N. Tarasova, A.A. Mamontov, 2014, published in Pochvovedenie, 2014, No. 11, pp. 1356–1364.

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Mamontova, E.A., Tarasova, E.N. & Mamontov, A.A. Persistent organic pollutants in the natural environments of the city of Bratsk (Irkutsk Oblast): Levels and risk assessment. Eurasian Soil Sc. 47 , 1144–1151 (2014). https://doi.org/10.1134/S1064229314110076

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Received : 09 January 2014

Published : 06 November 2014

Issue Date : November 2014

DOI : https://doi.org/10.1134/S1064229314110076

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43 Facts About Bratsk

Written by Elvira Llamas

Modified & Updated: 02 Mar 2024

Reviewed by Jessica Corbett

• Industrial Center Facts
• Industrialization Facts
• Russia Facts
• Russian Architecture Facts
• Siberia Facts
• Tourism Facts

Bratsk, a city located in the Irkutsk Oblast region of Russia, is a hidden gem worth exploring. With a rich history and a vibrant culture, Bratsk offers a unique experience to its visitors. From breathtaking natural landscapes to architectural wonders, there is something for everyone in this enchanting city.

In this article, we will uncover 43 fascinating facts about Bratsk that will pique your curiosity and make you want to pack your bags and embark on an adventure. Whether you are a history buff, nature enthusiast, or someone who appreciates art and culture , Bratsk has it all. So, let’s dive into this incredible city and discover what makes it so special!

Key Takeaways:

• Bratsk, a city in Russia, boasts a rich history, stunning landscapes, and a vibrant community, offering a unique experience for residents and visitors alike.
• With its impressive hydroelectric power station, beautiful natural reserves, and diverse cultural scene, Bratsk is a city poised for promising growth and development.

Bratsk is a city in Irkutsk Oblast, Russia.

Located in Siberia, Bratsk is situated on the Angara River and is known for its breathtaking natural landscapes.

The city of Bratsk was founded on August 26, 1947.

It was established as a residential settlement for the workers of the Bratsk hydroelectric power station.

Bratsk is home to one of the largest hydroelectric power plants in the world.

The Bratsk Hydroelectric Power Station has a capacity of 4,500 MW and plays a significant role in Russia’s energy production.

The population of Bratsk is approximately 246,000 people.

It is the third-largest city in Irkutsk Oblast, after Irkutsk and Angarsk.

The name “Bratsk” is derived from the word “brothers”.

It symbolizes the unity and cooperation of the workers who contributed to the construction of the city.

Bratsk experiences a continental climate with long, cold winters and short, warm summers.

The average temperature in January is around -19°C (-2°F), while in July , it reaches an average of 18°C (64°F).

The Bratsk Reservoir, created by the damming of the Angara River, is one of the largest artificial lakes in the world.

It covers an area of 5,470 square kilometers (2,110 square miles) and provides opportunities for various water activities.

Bratsk is a major transportation hub in Siberia.

It has a well-developed railway system and is connected to other cities in the region through an extensive network of roads.

The city of Bratsk is known for its vibrant cultural scene.

It is home to several theaters, museums, and art galleries that showcase the rich history and traditions of the region.

Bratsk is surrounded by picturesque natural landscapes, including dense forests, mountains, and rivers.

The area offers opportunities for outdoor activities such as hiking, fishing , and wildlife watching.

The Bratsk Dam, which forms the Bratsk Reservoir, was completed in 1967.

It stands at a height of 124 meters (407 feet) and is an impressive engineering feat.

The construction of the Bratsk Hydroelectric Power Station required the relocation of several villages and towns.

Efforts were made to ensure the smooth transition and well-being of the affected residents.

Bratsk has a diverse economy, with industries including energy, metallurgy, forestry, and agriculture.

The city’s development is closely tied to the Bratsk Hydroelectric Power Station and the surrounding natural resources.

Bratsk is home to several educational institutions, including universities, colleges, and vocational schools.

It serves as an educational center for the region, attracting students from different parts of Siberia .

The people of Bratsk are known for their warm hospitality and welcoming nature.

Visitors to the city often praise the friendly atmosphere and genuine kindness of the locals.

Bratsk has a rich cultural heritage, with influences from various ethnic groups living in the area.

The city celebrates traditional festivals, music, and dance, reflecting the diversity of its population .

The Bratsk Fortress is an important historical landmark in the city.

It dates back to the 17th century and serves as a reminder of Bratsk’s significant role in the region’s history.

Bratsk is known for its delicious cuisine, which features traditional Siberian dishes as well as Russian favorites.

Visitors can enjoy hearty soups, smoked fish , and locally sourced berries and mushrooms.

The Bratsk Museum of Local Lore showcases the history, culture, and natural wonders of the region.

It is a must-visit for those interested in learning more about Bratsk and its surroundings.

Bratsk has a well-developed sports infrastructure and supports various athletic activities.

The city has produced many talented athletes who have competed at national and international levels.

Bratsk is surrounded by beautiful nature reserves and national parks.

These protected areas are home to a wide range of flora and fauna, offering breathtaking sights for nature enthusiasts.

The Bratskaya street, one of the main streets in the city, is lined with shops, restaurants, and cafes.

It is a popular spot for locals and tourists to stroll, shop, and enjoy a meal.

Bratsk has a well-developed healthcare system, with modern hospitals and clinics.

The city prioritizes the health and well-being of its residents by providing quality medical facilities.

The Bratsk Opera and Ballet Theater is a cultural hub in the city, hosting performances by talented artists.

It showcases ballets, operas, and other musical events, attracting audiences from near and far.

Bratsk has a vibrant music scene, with local bands and musicians performing a variety of genres.

Music lovers can enjoy live performances at venues throughout the city.

The annual Bratsk International Film Festival celebrates the art of cinema.

It attracts filmmakers, industry professionals, and film enthusiasts from around the world.

The Bratsk Circus is a popular entertainment venue, featuring thrilling acrobatic performances and animal shows.

It offers fun-filled experiences for both children and adults.

Bratsk has a strong sense of community, with various civic organizations and volunteer groups working towards the betterment of the city.

Citizens actively participate in initiatives aimed at improving the environment, education, and social welfare.

The beautiful Bratsk City Park is a favorite spot for leisurely walks, picnics, and outdoor activities.

It offers a tranquil escape from the bustling city life.

Bratsk is known for its stunning sunsets, which paint the sky with vibrant colors.

The breathtaking views make for memorable moments and great photo opportunities.

The local markets of Bratsk are vibrant hubs of trade, showcasing a variety of local produce and goods.

Visitors can explore the stalls and sample fresh fruits, vegetables, and handicrafts.

Bratsk is an important center for scientific research and innovation.

The city is home to various research institutes and laboratories that contribute to advancements in different fields.

The Bratsk State University offers a wide range of educational programs across various disciplines.

It attracts students not only from Bratsk but also from other parts of Russia and abroad.

Bratsk is a city that embraces technology and digital connectivity.

The city’s infrastructure is well-equipped to meet the demands of the digital age.

Bratsk hosts various cultural events throughout the year, including music festivals, art exhibitions, and theatrical performances.

The city’s calendar is filled with opportunities to immerse oneself in the vibrant cultural scene.

Bratsk is a city where old traditions and modernity coexist harmoniously.

While the city embraces progress, it also values and preserves its rich cultural heritage.

Bratsk is surrounded by vast forests, making it an ideal destination for nature lovers and outdoor enthusiasts.

Hiking, camping, and wildlife spotting are popular activities in the area.

The Bratsk Philharmonic Orchestra is renowned for its exceptional performances and talented musicians.

It enchants audiences with a diverse repertoire that includes classical, contemporary, and traditional pieces.

Bratsk takes pride in its strong educational system, which emphasizes the importance of knowledge and skills.

It prepares the younger generation for bright futures and successful careers.

Bratsk is a city that celebrates diversity and promotes inclusivity.

It values the contributions of people from different backgrounds and fosters a sense of unity among its residents.

The Bratsk Mosque is an important religious landmark in the city.

It serves as a place of worship for the Muslim community and represents the city’s religious tolerance.

Bratsk is a city with a strong sense of environmental consciousness.

Efforts are made to protect and preserve the natural resources and promote sustainable practices.

Bratsk is a city that holds great potential for growth and development.

With its rich resources, vibrant community, and forward-thinking outlook, it is poised for a promising future.

In conclusion, these 43 facts about Bratsk showcase the fascinating history, natural wonders, and cultural significance of this city. From being home to one of the world’s largest hydroelectric power stations to boasting stunning landscapes like Lake Baikal and the Taiga forests, Bratsk has something for everyone. Its rich history, with traces of ancient civilizations and Soviet-era industrial development, adds a unique charm to the city.Whether you’re interested in adventure tourism, exploring historical sites, or simply immersing yourself in the local culture, Bratsk offers a myriad of experiences. The city’s warm hospitality, friendly locals, and delicious local cuisine make it a memorable destination for travelers.Don’t miss the opportunity to witness the breathtaking beauty of Bratsk. Visit this city and unlock its hidden gems, unforgettable experiences, and the chance to create lifelong memories.

Q: When is the best time to visit Bratsk?

A: The best time to visit Bratsk is during the summer months of June to August when the weather is pleasant and outdoor activities are in full swing.

Q: How do I get to Bratsk?

A: Bratsk can be reached by air through the Bratsk Airport, which has regular flights from major cities in Russia. Alternatively, you can also travel by train or bus from neighboring cities.

Q: Are there any popular attractions in Bratsk?

A: Yes , Bratsk is known for its popular attractions such as the Bratsk Hydroelectric Power Station, Lake Baikal, Taiga forests, and the Bratsk Reservoir.

Q: Is Bratsk safe for tourists?

A: Yes, Bratsk is generally safe for tourists. However, it is always advisable to take necessary precautions and be aware of your surroundings, especially in crowded areas.

Q: What are some traditional dishes to try in Bratsk?

A: Some traditional dishes to try in Bratsk include Siberian pelmeni, omul fish, stroganina, and local berry desserts.

Bratsk's stunning landscapes beckon nature enthusiasts to explore the wonders of the taiga biome, where cold climates shape unique ecosystems. This Russian city shares its rich history and culture with other fascinating destinations like Orenburg, inviting travelers to discover the depth and diversity of Russia's urban tapestry. Bratsk's massive hydroelectric power plant stands as a testament to human ingenuity, harnessing the immense potential of flowing water to power homes and industries, showcasing the transformative impact of hydroelectric technology .

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