Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions

By Miltiadis D. Lytras

Digital Innovation for Healthcare in COVID-19 Pandemic: Strategies and Solutions provides comprehensive knowledge and insights on the application of information technologies in the healthcare sector, sharing experiences from leading researchers and academics from around the world. The book presents innovative ideas, solutions and examples to deal with one of the major challenges of the world, a global problem with health, economic and political dimensions. Advanced information technologies can play a key role in solving problems generated by the COVID-19 outbreak. The book addresses how science, technology and innovation can provide advances and solutions to new global health challenges.

This is a valuable resource for researchers, clinicians, healthcare workers, policymakers and members of the biomedical field who are interested in learning how digital technologies can help us avoid and solve global disease dissemination.

• Presents real-world cases with experiences of applications of healthcare solutions during the pandemic of COVID-19
• Discusses new approaches, theories and tools developed during an unprecedented health situation and how they can be used afterwards
• Encompasses information on preparedness for future outbreaks to make less costly and more effective healthcare responses to crises

• Language: English
• Publisher: Academic Press
• Release date: Mar 11, 2022
• ISBN: 9780128232101

Book preview

Preface

Patricia Ordóñez de Pablos, Book Series Editor, The University of Oviedo, Oviedo, Spain

Introduction

The Elsevier book series Information Technologies in Healthcare Industry will offer a unique collection of books on innovative and emerging topics focused on the healthcare industry (products, services, processes, etc.) and the aging society. It will shed light on the latest developments in the fields of innovation and science in the healthcare industry and the opportunities for the future of digital healthcare. This book series will explore the deployment of digital solutions for person-centered integrated care in the health industry, security issues in health data access, ethical and compliant use and sharing of health data, and the power of artificial intelligence to deal with disease outbreaks, among other topics. Leading experts from around the world will contribute to the books in this collection, sharing their knowledge and expertise in the field of digital health.

Some books will analyze healthcare management, innovation, and digital health policies in specific regions—Europe, Africa, Asia, Asia-Pacific, United States and Canada, Latin America, the Gulf region—and will provide comparative analyses, actionable recommendations, and policy and regulatory discussions.

As editor-in-chief of this book series, I am very proud to present the first volume titled Digital Innovation for Healthcare during the COVID-19 Pandemic: Strategies and Solutions. This book contributes to the understanding of the role of information technology in the COVID-19 crisis and how to create a more digital future in the healthcare sector.

Contents of this book

This book is a collection of 20 chapters addressing key and emerging topics in the field of digital innovation, IT for healthcare, and COVID-19. A brief description of each chapter is presented in the following paragraphs.

Chapter 1, titled Social dimensions and preconditions of digitalization in healthcare: Implications of the COVID-19 syndemic (author: Florian Fischer), states that the manifold potentials and challenges of digitalization became apparent during the COVID-19 pandemic. This chapter will present and discuss the social aspects of digitalization in times of COVID-19 from different perspectives. In doing so, the focus will be on the following two aspects: (1) Interaction and handling of digital information place many demands on information users and on those who provide the information. This has been especially true since the COVID-19 pandemic, which was accompanied by an infodemic. This is where digital health literacy comes in, which is the ability to find, understand, assess, and apply digital information in the context of health. (2) The use of digital technologies on health-related topics is socially unequally distributed in society—both horizontally (gender, age, migration, place of residence) and vertically (socioeconomic status). For this reason, the digital health divide is a major obstacle for digital technologies in healthcare—during COVID-19 and beyond.

Chapter 2, titled Digital innovation for healthcare in COVID-19 pandemic (author: Elham Nazari), observes that in recent decades, complex and infectious diseases like COVID-19 have been increasing. New technologies, essentially computers and mobile phones, have become an integral part of all communities. No doubt, digital innovations are crucial tools, which can be used by healthcare organizations, care providers, patients, and decision and policy makers for improving the quality of services and reducing costs. Integrative healthcare with technologies has gained a lot of attention and would lead to remarkable revolution in service delivery. Early diagnosis using machine learning approaches, patient self-care with apps, remote access to medicine in rural areas, elderly condition monitoring through smart homes and robots are all applications of technologies. Therefore, the purpose of this chapter is to address the advantages, applications, and challenges of new technologies such as robots, black chain, data science, social media, internet of things, and telemedicine in healthcare, especially during the fight against the COVID-19 pandemic.

Chapter 3, titled A digital health ecosystem for Africa during the COVID-19 pandemic (author: Liezel Cilliers), proposes that digital health ecosystems can be used to improve the quality of life and healthcare for citizens in developing countries. Despite the literature that supports the benefits that these ecosystems can provide for healthcare and the considerable investment in health information systems by national governments, the implementation of these systems has not produced the expected return on investment in Africa. This chapter investigates what a digital health ecosystem means during the COVID-19 pandemic for the African continent. The chapter explores what digital innovations mean for healthcare and provides a comprehensive list of technologies that is included in a digital health ecosystem. For such an ecosystem to function effectively, a large amount of data is needed. The various sources and purposes for each of the sources are identified including the stakeholders that need to be included in the digital health ecosystem. This chapter recommends that integration of health information systems, commitment from all stakeholders, and political will is needed if Africa is to succeed in implementing a digital health ecosystem.

Chapter 4, titled Doctor @ home: New perspectives on telemedicine for women during the COVID pandemic (authors: Francesca Dal Mas, Helena Biancuzzi, Giuseppe Roberto Marseglia, Rym Bednarova, Lorenzo Cobianchi, and Luca Miceli), states that at present, telemedicine and remote visits represent one alternative to in-person visits to meet patients’ ambulatory care needs during the COVID-19 pandemic and its enforced social distancing requirements. Telemedicine is becoming popular in several clinical disciplines, including pain medicine and oncology. Two out of three chronic pain patients are women. Moreover, most women can be considered vulnerable patients, as they often need to take care of their families and jobs while under chronic pain or oncological treatment. By employing a case study, this chapter aims to delve deep into how this new paradigm can benefit patients’ quality of life.

Chapter 5, titled Implementing virtual patient rooming during telemedicine visits (authors: Teresita Gomez, Michelle A. Bholat, Blanca Campos, and Derjung M. Tarn), affirms that the COVID-19 pandemic caused a rapid expansion of telemedicine use in the outpatient setting. Although studies have proposed several workflows for implementing telemedicine visits, most have not considered integrating the traditional role of medical assistants and nurses in virtual office visits. We report the experience of implementing telemedicine visits in a large university-based primary care office in the United States during the pandemic, with particular emphasis on integrating ‘virtual rooming’ into the telemedicine workflow. This chapter describes the implementation of a virtual rooming model, including a discussion on facilitators, challenges, and suggestions for best practices. We examine these issues from the point of view of primary care providers, medical assistants (MAs)/licensed vocational nurses (LVNs), and office administration staff. Since telemedicine is likely here to stay, there is a need to develop, refine, and test effective and efficient workflows to integrate these visits seamlessly into office workflows without compromising the quality of patient care.

Chapter 6, titled Embracing digital technologies in the healthcare setting (authors: Sangeeta Gopal Saxena and Thomas Godfrey), states that the COVID-19 pandemic has catalyzed the pace and scope of digital technology (DIT) use in healthcare. It has facilitated health promotion, disease prevention, diagnosis and treatment of secondary health concerns, patient engagement, monitoring adherence to treatment, and surveillance. COVID-19-related large databases and medical and public health research have been shared freely and rapidly. Continued adoption of technology can lead to better and faster diagnosis of health conditions and accelerate attainment of sustainable development goals (SDGs). However, many barriers still remain. Key issues are high costs, lack of interoperability of technology, frequent need for software updates, training and development, concerns about privacy, technological disruption, and network coverage issues. Greater involvement of end users in the development and rollout of new digital technologies is needed to ensure faster and deeper implementation of technology in healthcare as uneven implementation can exacerbate the divide between the haves and the have-nots.

Chapter 7, titled Impact of COVID-19 on the adoption of digital pathology (authors: Mustafa Yousif, Lewis Hassell, and Liron Pantanowitz), observes that digital pathology was developed decades ago to allow pathologists to remotely collaborate on cases and improve the accuracy of diagnostic techniques by sharing digital images across laboratories. Prior to the COVID-19 pandemic, the United States lagged behind most other developed countries in terms of digital pathology adoption due to strict federal regulations of the US Food and Drug Administration (FDA) and the Clinical Laboratory Improvement Amendments (CLIA) from the Centers for Medicare & Medicaid Services (CMS). The FDA relaxed some of its requirements to approve and validate digital pathology-related technology to meet the pandemic response’s needs. Similarly, the CMS waived restrictive CLIA rules that now allowed pathologists to use digital pathology platforms from home. Thereby, the COVID-19 pandemic accelerated broad adoption of digital pathology for remotely rendering pathology diagnoses. This imaging technology has provided pathologists and pathologists-in-training with a variety of resources to help them continue to remotely care for patients, collaborate, and support virtual education. This paradigm shift will impact not only how we routinely work in the postpandemic era but also how we will virtually teach pathology in the future and possibly even modify regulations that govern how digital pathology systems can be used and get approved for diagnostic use. The focus of this chapter is on digital pathology in relation to the COVID-19 pandemic.

Chapter 8, titled The COVID-19 pandemic in an interdependent world: Digital health as a tool for equity and gender empowerment (authors: Mouna Ghanem, Danielle Drachmann, Lars Münter, Nicolaj Holm Faber, Bogi Eliasen, Robert Fullilove, and Kristine Sørensen), observes that throughout history, pandemics have paved the way for the development of public health. The current COVID-19 pandemic is no different as it is taking advantage of our flat and interconnected world, posing a threat to global health in a pace as never seen before. This chapter presents an analysis of how digital health and gender empowerment can bridge the inequity gap caused and sustained by disparities related to social determinants of health. COVID-19 has struck certain groups disproportionately; this has an increased the need for availability and accessibility of health services. Our findings suggest that COVID-19 is a gender-sensitive virus relying on access to digital health means. Multiple examples and case studies are provided to illustrate the relationship between inequity, gender, and digital health. Moving forward, the pandemic has crystalized the need for paradigm shifts. In this regard, the achievement of equity in health is one of the only ways to control and ultimately eradicate COVID-19 in order to leave no one behind.

Chapter 9, titled The study of the dilemma on the control of COVID-19 spread and face-to-face learning and its trade-off solutions (authors: Lap-Kei Lee, Kwok Tai Chui, and Yin-Chun Fung), recalls that to control the COVID-19 spread, face-to-face learning has been prohibited. Instead, some of the classes have been canceled and some are being conducted in e-learning mode. Both teachers and students have encountered difficulties in the unusual and less-effective online learning environment. Particularly, the situation is getting worse from the senior group (university) to junior groups (secondary school, primary school, and kindergarten) as students’ maturity levels are closely related to learning. Various research studies and surveys have summarized that the educational standard and learning outcomes are generally lowered during the pandemic. To address the dilemma between health and face-to-face learning, cutting-edge techniques should be introduced to provide trade-off solutions for school management and government. Case studies are discussed to examine the dilemma and trade-off solutions. The pros and cons of the solutions have been summarized. We have highlighted some emergent research directions as future works.

Chapter 10, titled Digital tools for direct and indirect citizen empowerment: The retaliatory response against COVID-19 in India (authors: Subhanil Banerjee, Shilpi Gupta, and Souren Koner), states that the COVID-19 pandemic is one of the most dreadful pandemics in human history. It has tested human resilience like no other pandemic so far. However, the indomitable human spirit has fought back and digital intervention, especially mobile app-oriented retaliation, has created mobile magic. India is the second most populated country in the world. Owing to its close proximity to China from where the virus spread, India was exposed to a high volume of risks. Mobile apps like CoWIN, Aarogya Setu, Corona Kavach, COVA, CG Teeka, Mahakavach helped India to bounce back. People were empowered with their own safety literally at their fingertips. On the basis of this background, this chapter analyzes the relevant data of 136 countries and emphasizes on the mobile magic. Furthermore, it also highlights India’s superior performance in taming COVID-19 compared to the rest of the world.

Chapter 11, titled Continuum of care through patient relationship management approach in Indian public healthcare system (authors: Sumita Dave and Varun Sahu), proposes that patient relationship management is a system-designed strategy for healthcare that has the potential to improve patient satisfaction while also lowering healthcare costs. The main goals of this concept are to create an effective referral model that provides a continuum of care while managing patient relationships with a cutting-edge digital healthcare system that manages a patient’s healthcare data, to keep track of people’s healthcare needs and develop a healthcare referral model, to provide effective and timely care by continuous follow-up, involving patient relationship management in the public healthcare system, and to develop a new healthcare delivery model. The application of digital solutions to health systems can help address constraints that have hindered the optimal delivery of equitable and high-quality care.

Chapter 12, titled Using machine learning methods to understand COVID-19 inpatient medical health records in a US hospital system (authors: Dezhi Wu, Yang Ren, Long He, and Joseph Johnson), states that coronavirus disease 2019 (COVID-19) has become a global pandemic that significantly challenged healthcare systems worldwide, with over 4 million deaths among 18.6 million identified cases as of June 2021. Understanding the current COVID-19 cases and determining clinical solutions is of paramount importance. In this chapter, we describe an exploratory study of identifying risk factors associated with COVID-19 inpatient care. Based on a set of COVID-19 inpatient medical health records in a US hospital system, we used both unsupervised and supervised machine learning methods to explore risk factors associated with hospitalized COVID-19 patients. We found that the most important features related to the COVID-19 disease include (1) influenza vaccines, (2) pneumococcal vaccines, and (3) weight-related variables (i.e., weight, height, and BMI). As such, we provide a use case that machine learning methods are valuable for predicting COVID-19 inpatient risk factors, and the results are promising to guide further research in this area.

Chapter 13, titled Geospatial analysis of COVID-19 distribution and its relation to public transportation services (authors: Magdalena Saldana Perez, Victor Garrido-Gutierrez, Cornelio Yáñez-Márquez, Miguel Torres-Ruiz, and Marco Moreno-Ibarra), affirms that COVID-19 has changed our lifestyle; nowadays, activities such as studying, working, and meetings, among others, have drastically changed from being face to face to being remote; however, there is still an activity that has not changed as quickly as needed because of its main purpose, i.e., transportation. In this approach, a complete COVID-19 geospatial analysis is conducted correlating official reported cases of COVID-19-infected individuals and those who died with the data of public transportation, focusing on specific areas and the subway service in Mexico City. The geospatial analysis allows identifying the importance of some subway stations and their influence on the rate of infected people and also allows visualizing the distribution of COVID-19 all over the geographic areas near the subway stations and understanding the distribution of COVID-19 in the city. Finally, the approach generates a visualization model of the distribution of COVID-19 and its relation to the subway service using geospatial intelligence.

Chapter 14, titled M-health system for cardiac and COVID patient monitoring using body sensor networks and machine learning (authors: Francisco Beltrán-Chávez, Félix Mata-Rivera, Mario Rivero, Miguel Torres-Ruiz, Roberto Zagal-Flores, Giovanni Guzmán, Rolando Quintero, and Marco Moreno-Ibarra), states that the COVID-19 pandemic has promoted the need to take care of health at home, using M-health systems to monitor vital signs in healthy people and in those with heart conditions. Thus, body sensor networks (BSNs) are extremely useful for sensing and alerting when some type of health risk is identified such as arrhythmia and low oxygen levels as well as for helping to make a decision. This chapter describes a home health monitoring system to identify cardiac risk events and monitor oxygenation levels in a person using a BSN simulator and exploring the energy performance of the network, considering the IoT devices installed at home. The work is oriented toward monitoring and identifying risk events in closed spaces, and it is addressed to people with two types of conditions: (1) those with heart diseases and (2) those who need to monitor their oxygen levels after recovering from the COVID-19 disease.

Chapter 15, Pandemic-driven innovations contribute to the development of information-based medicine (author: Jan Kalina), considers that the outbreak of the COVID-19 pandemic accelerated trends toward introducing innovative digital tools tailor-made for various applications in medical care or public health. This chapter focuses on decision support systems as important examples of artificial intelligence tools with increasing popularity. Their potential to contribute to targeting measures adopted against the COVID-19 pandemic is discussed. In connection with applying artificial intelligence tools in healthcare, their ability to perform epidemic modeling or to contribute to targeting public health interventions is also discussed. The expected remarkable transforms of medical care, including its informatization, are described here by the concept of information-based medicine, which exceeds the limited prepandemic ideals of evidence-based medicine. The same is true for the concept of information-based public health.

Chapter 16, Enabling healthcare 4.0 applications development through a middleware platform (authors: Nader Mohamed, Jameela Al-Jaroodi, and Eman AbuKhousa), discusses that smart healthcare is a promising direction for healthcare services and can be facilitated by adopting the Healthcare 4.0 vision, which utilizes new technologies to provide value-added healthcare services to patients. Developing and integrating Healthcare 4.0 applications is challenging in terms of design complexity, architectural choices, support services, reliability, security, and privacy. This chapter discusses these challenges and identifies the requirements for enabling the Healthcare 4.0 vision. It also proposes H4Ware, a service-oriented middleware, for Healthcare 4.0. H4Ware helps utilize new and emerging technologies to relax some of these challenges and provides a coherent collection of support and advanced services, enabling simpler development, integration, and deployment of healthcare applications. An example application illustrating how these services can be integrated is discussed in addition to introducing the core services in H4Ware and a prototype implementation. H4Ware will enable fast development of healthcare applications that will help handle diseases such as COVID-19.

Chapter 17, Healthcare 4.0 significance and benefits affirmed by the COVID-19 pandemic (authors: Jameela Al-Jaroodi and Nader Mohamed), affirms that when a pandemic happens, our first line of defense is the healthcare system, which must be effective, agile, and efficient in handling the pressure, and Healthcare 4.0 is a good way to achieve this. However, we are nowhere near a real implementation of Healthcare 4.0. When COVID-19 hit, it stretched resources beyond the limits and drove healthcare organizations to move quickly to automate procedures, introduce remote and mobile healthcare services, and enhance the value chain. This affirmed the importance of a well-designed, highly efficient, and smart healthcare infrastructure to better handle future healthcare crises. A Healthcare 4.0 infrastructure will create a framework allowing healthcare systems to expand their capabilities quickly. In this chapter, we investigate what went on during the pandemic and highlight the areas where Healthcare 4.0 could have made a difference. We also discuss how we need to move forward for better adoption and a more effective Healthcare 4.0 infrastructure.

Chapter 18, Improving the diagnostic accuracy using amplification and sequencing of the SARS-CoV-2 genome (authors: N. Marline Joys Kumari, Debnath Bhattacharyya, and N. Thirupathi Rao), states that deep learning involves using deep neural networks with multiple hierarchical hidden layers of nonlinear processing of input to allow complex patterns to be discovered from vast volumes of raw data. Performance is improved through adjusting, optimizing, and regulating hyperparameters. Unsupervisedstudy finds patterns in the data when we have no labels and the distribution of probability in data. The study of genomic sequencing and genome expression is typically characterized by deep learning. Predicting genomic profiles based on around 1000 programmes programs of the NIH Integrated Network (LINCS) that have dramatically surpassed linear regression in both the RNA-seq findings and the microarray in terms of predictive precision. Deep CNN is used to predict the transcription factor binding sites, like Deep CNN inputs have been encrypted, protein binding, and the true value is feedback indicating whether the sequence is boundary. By retrieving higher levels from those in raw nucleotides, the deeper model would make categorization more accurate. Genetic variations may affect transcription of DNA and mRNA.

Chapter 19, Telecardiology COVID-19 cryptographic system: Security reinforcement through metaheuristics and artificial neural networks (authors: Joydeep Dey, Anirban Bhowmik, and Sunil Karforma), affirms that in this critical phase of COVID-19, cryptographic and nature-inspired innovations help communicate confidential data inside electronic telehealth systems. The novel corona virus has shattered all formats of life. In medical sciences, patients are advised to opt for remote-based telemedicine support. Cardiac patients are highly susceptible to corona virus. It is highly recommended that patients with chronic obstructive pulmonary diseases (COPDs) as comorbidity stay safe at their remote quarantines. Through such telecardiology systems, they may transmit and communicate their critical and secret information related to multiple cardiac reports to different stakeholders for better treatments, views, and expert opinions. This will reduce their chances of contracting COVID-19 due to no physical movements outside their homes. Such heterogeneous cardiac-related reports are to be secured with a view to restore the patients’ confidentiality clause. Cardiovascular diseases (CVDs) are a type of disease related to the blockage of arteries and veins. Patients suffering from CVDs require proper diagnosis and treatment by cardiologists. Contemporary flaws in a patient’s private information are a significant and open challenge in such telecardiology systems. Electronic cardio records are extremely sensitive in nature. Hence, it is very important to impose an advanced security technique in such COVID-19 systems. In this chapter, we have developed a cryptographic system based on a metaheuristic harmony search algorithm and an artificial neural network. This system acts against different security conducts in communication.

Finally, the last chapter of this book, Chapter 20, The use of digital technologies in the response to SARS-2 CoV2-19 in the public health sector (authors: Eali Stephen Neal Joshua, Debnath Bhattacharyya, and N. Thirupathi Rao), observes that in order to promote public health response to COVID-19, digital technologies are being used around the world. These include population surveillance, case identification, contact tracking, and intervention assessment based on mobility data and public communication. These rapid responses are made possible by the millions of mobile phones in use, massive online data sets, connected devices, low-cost computer resources and machines, and advances in natural language processing. To achieve this goal, a comprehensive review of digital innovations for COVID-19 response to public health around the world is being conducted, including a look at their limitations and implementation obstacles such as legal or ethical issues, privacy concerns, and organizational and personnel issues. We investigate the need for international strategies to improve pandemic control and future preparedness for COVID-19 and other infectious diseases through the regulation, assessment, and use of digital technologies, as well as the need for international strategies to regulate, assess, and use digital technology in pandemic management.

I hope this first volume of the book series motivates our readers to dive deeper into digital health challenges and opportunities and also contribute to shaping the future of digital innovation in the healthcare sector. Dialogue and collaboration with different stakeholders (patients, health providers, health ecosystem) in the e-health industry will accelerate the digital transformation of this industry.

Acknowledgments

I thank Elsevier and especially Rafael Teixeira and Pat Gonzalez for their continuous support and help with the development of the book series and this first volume. Finally, I cannot forget to send a thank-you note to the authors of the chapters of this first volume for sharing their valuable latest research outputs.

Chapter 1: Social dimensions and preconditions of digitalization in healthcare: Implications of the COVID-19 syndemic

Florian Fischera,b,c    a Institute of Public Health, Charité – Universitätsmedizin Berlin, Berlin, Germany

b Institute of Gerontological Health Services and Nursing Research, Ravensburg-Weingarten University of Applied Sciences, Weingarten, Germany

c Bavarian Research Center for Digital Health and Social Care, Kempten University of Applied Sciences, Kempten, Germany

Abstract

The manifold potentials and challenges of digitalization became apparent during the COVID-19 pandemic. This chapter will present and discuss the social aspects of digitalization in times of COVID-19 from different perspectives. In doing so, the focus will be on the following two aspects: (1) Interaction and handling of digital information place many demands on information users and on those who provide the information. This has been especially true since the COVID-19 pandemic, which was accompanied by an infodemic. This is where digital health literacy comes in, which is the ability to find, understand, assess, and apply digital information in the context of health. (2) The use of digital technologies on health-related topics is socially unequally distributed in society—both horizontally (gender, age, migration, place of residence) and vertically (socioeconomic status). For this reason, the digital health divide is a major obstacle for digital technologies in healthcare—during COVID-19 and beyond.

Keywords

Health literacy; Digital divide; Inequity; Social determinant of health; Public health

1: Introduction

The occurrence of SARS-CoV-2 and its global spread has led to a public health emergency of international concern (WHO, 2021). At the beginning of the pandemic, it was frequently claimed that COVID-19 is a great equalizer, because it affects people irrespective of age, gender, or socioeconomic position—we are all at risk (Mein, 2020). However, the longer the pandemic lasted, the more obvious it became that it does not level out existing inequalities—rather, the COIVD-19 pandemic deepens these inequalities. This is not only due to vulnerabilities (e.g., in terms of age (Chen et al., 2021) or chronic illness (Geleta et al., 2020)). COVID-19 is a burning glass for inequalities, as it strikes people who are not equally able to protect themselves from the virus, severe courses of the disease, as well as adverse—economic and, thereby, health-related—consequences of lockdowns (Burström & Tao, 2020). Resilience and coping strategies are unequally distributed (Norris, Stevens, Pfefferbaum, Wyche, & Pfefferbaum, 2008)—across countries and within societies. Social determinants of health—such as poverty, adverse physical living conditions (e.g., homelessness), or ethnicity—have been shown to have a considerable effect on COVID-19 outcomes (Abrams & Szefler, 2020; Burström & Tao, 2020). Furthermore, the risk of severe COVID-19 is higher in older individuals and among those with underlying health conditions (Clark et al., 2020). These (disease) interactions and their association with social determinants of health make COVID-19 not only a pandemic but a syndemic (Bambra, Riordan, Ford, & Matthews, 2020; Horton, 2020; Singer, 2009).

Already before COVID-19, it has been apparent that the social status of an individual is determined by social determinants of health. These include horizontal determinants (such as age, gender, marital status) and vertical determinants (which is particularly the meritocratic triad of education, occupation, and income) impacting health (Mackenbach et al., 2008). Previous research on the social gradient in health has led to progress in understanding disease causation and effectiveness of political actions for reducing social inequalities and, thereby, health inequalities (Marmot, 2017). However, the medical-sociological phenomena of health inequalities are merely constant but are influenced in the course of social stress situations, such as economic, financial, and political crises. Currently, this is obvious in the COVID-19 pandemic. Nevertheless, the impact of socioeconomic disparities on morbidity and mortality has already been described in past pandemics (Quinn & Kumar, 2014; Rutter, Mytton, Mak, & Donaldson, 2012; Sydenstricker, 2006).

2: COVID-19 and digitalization

The COVID-19 pandemic goes along with another major transformation: Digitalization has already been underway for several decades but has gained substantially more attention and relevance due to the pandemic in almost all areas of life (OECD, 2020). Digitalization is transforming almost all phases and areas of our everyday life. It offers a wide range of potentials and challenges due to its comprehensive diffusion throughout society. Manifold challenges of digitalization became particularly apparent during the COVID-19 pandemic (e.g., related to the home office or digital school teaching). At the same time, digital innovation and transformation can serve as valuable tools for fighting against COVID-19—directly related to monitoring, surveillance, detection, and prevention (Ting, Carin, Dzau, & Wong, 2020), related to the rapid adoption of digital tools and technologies such as telemedicine for enabling the delivery of healthcare services in digital or hybrid forms for treating patients (Bokolo, 2020), but also related to adverse impacts of COVID-19 and containment measures on society (Hovestadt, Recker, Richter, & Werder, 2021).

Within the months of the pandemic, it became obvious that digital access needs to be considered as a social determinant of health because it is a prerequisite not only for healthcare (Eruchalu et al., 2021) but also for (health-related) information (van Deursen, 2020). However, this does not merely apply to those digital applications that are used in the healthcare system itself (Dorsey & Topol, 2020). Rather, the direct and indirect effects of digitization influence all social and health contexts (Daniels, Gregory, & Cottom, 2017) and thus affect the fields of action of public health (Dockweiler & Fischer, 2019; Dockweiler & Razum, 2016).

Digitalization is more than just the introduction of technology; rather, it is a transformation process. This is because the dynamic interrelationships between digitalization and society unleash possibilities that have a (re)structuring effect on social contexts in a variety of ways (Dockweiler & Fischer, 2019). The impact of digitalization is amplified by the fact that this transformation process is occurring simultaneously and in part interdependently with other megatrends (Berger, 2020). Against the backdrop of these societal megatrends, which are further amplified by the opportunities but also challenges of digitalization, a critical perspective is needed on what implications digitalization brings with it. For that reason, this contribution aims to exemplify social dimensions and preconditions of digitalization in times of COVID-19, focusing on two major themes relevant for healthcare-related digital applications: digital health literacy and digital health divide. The arguments which are made subsequently are conferrable to almost all digital applications. Technological innovations (also outside the scope of health-related or medical interventions) have to be seen more holistically, because they lead to direct and indirect, as well as intended and nonintended, impacts on health, and, therefore, go beyond a purely medical or economic consideration of effectiveness and efficiency. However, these considerations related to social aspects of digitalization—which have become particularly apparent during the COVID-19 pandemic—are also highly relevant for digital applications directly related to healthcare. Further considerations in terms of the development and implementation of these technologies are needed because they also serve as social innovations (Maiolini, Marra, Baldassarri, & Carlei, 2016).

3: Social dimensions of digitalization in times of COVID-19

When introducing digital innovations in healthcare, one needs to pay attention to whether certain (sub-)populations receive better access to health-related information due to a low threshold or whether privileged groups—in the sense of a good state of health and showing a high affinity for health—are (once again) preferentially reached. In the latter case, persons with low educational status are mainly disadvantaged—both in comparisons between and within countries (Makri, 2019).

3.1: Digital health literacy

A major prerequisite for enabling patients or persons to act on their behalf is empowerment. By giving patients a stronger voice and empowering them to be active participants in healthcare, they can develop their decision-making and shared decision-making skills (Conard, 2019). Empowerment is the ultimate goal of health literacy (Smith & Carbone, 2020), which is defined as the ability to access, understand, appraise, and apply health information (Liu et al., 2020; Sørensen et al., 2012). Digital health literacy includes both analytical (i.e., traditional literacy and numeracy, media literacy, and information literacy) and context-specific (i.e., health literacy, computer literacy, and science literacy) skills (Norman & Skinner, 2006).

Previous studies have illustrated that patients with low levels of health literacy were significantly more likely than individuals with adequate health literacy to have a poorer health status, to delay or forgo needed care, or to report difficulties in finding a healthcare provider (Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011; Levy & Janke, 2016). This effect remained even after controlling for other factors such as health insurance coverage or socioeconomic status (Levy & Janke, 2016). With advances in digitalization, particularly the increasing use of the internet as a source to get informed about health-related issues (Swire-Thompson & Lazer, 2020), digital health literacy deserves much more attention (Jackson, Trivedi, & Baur, 2021). Digital health literacy, also phrased as e-Health literacy or e-Literacy in healthcare, is a highly dynamic area because innovative ways of delivering healthcare demand new and constantly changing skills both from healthcare professionals and patients (Klecun, Lichtner, & Cornford, 2014).

The COVID-19 pandemic has shown that fast and low-threshold access to health-related information for the public is crucial (van Deursen, 2020). Adequate knowledge, attitudes, and practices in times of a crisis depend on evidence-based and quality-assured information. However, the COVID-19 pandemic was also associated with uncertainties, which gave rise to a hidden epidemic of false or misleading information—a so-called (digital) infodemic. A plethora of misinformation, rumor, and conspiracy theories was visible in social media as well as other digital platforms (Banerjee & Meena, 2021). It impacted on public's reaction toward the pandemic related to perceived threats and applying preventive behaviors (Banerjee & Meena, 2021; Mahmood, Jafree, Mukhtar, & Fischer, 2021). The third-person effect hypothesizes that people—based on personal biases—tend to perceive that messages presented in mass media have a greater effect on others than on themselves. This in turn manifests in an individual's overestimation of the effect of a mass communicated message on the generalized other, or an underestimation of the effect of the respective message on themselves (Davison, 1983). Research on digital disinformation with a theoretical foundation on the third-person effect has shown that COVID-19 digital fake news exposure impacts an individual's perceived susceptibility of influence on themselves, their close others, and their distant others (Liu & Huang, 2020). In this regard, low levels of (digital) health literacy adversely impact accepting and applying containment measures (e.g., vaccination) during the pandemic. However, digital health literacy is not merely important for health promotion and disease prevention, but also for understanding basic healthcare information (McCray, 2005). Previous studies have shown that low literacy skills hamper patients’ interactions in the healthcare setting and complicate navigating the healthcare system (Hersh, Salzman, & Snyderman, 2015; Smith & Magnani, 2019).

However, promoting digital health literacy is not the exclusive task for professionals in healthcare. Since making adequate health information accessible and understandable to everyone is one of the most pressing issues in our society, it is a task for all of society. It needs a comprehensive program that promotes health literacy in the living environment and everyday life of the public (e.g., in school education or at the workplace) (Schaeffer, Hurrelmann, Bauer, & Kolpatzik, 2018). For creating a user-friendly and health literate healthcare system, Schaeffer et al. (2018) recommended

–to integrate health literacy as a standard at all levels of the healthcare system,

–to facilitate navigation within the healthcare system, increase transparency, and reduce administrative barriers,

–to create comprehensible, effective communication between health professions and users,

–to create user-friendly health information, and

–to facilitate and strengthen patient participation.

These recommendations are not new, but the COVID-19 pandemic—in interplay with increasing digitalization—has reinforced the need; particularly in a healthcare system that is fragmented, complex, and technologically sophisticated (Parker, 2000).

3.2: Digital health divide

Although the challenges of preparing and receiving evidence-based and quality-assured health-related information are ubiquitous, they are not equally distributed. Health literacy is associated with many antecedents of health disparities (Mantwill, Monestel-Umaña, & Schulz, 2015). New technologies also lead to new disparities (Smith & Magnani, 2019). Therefore, in the context of digital health-related applications, fundamental aspects of social justice and equal opportunities, as well as competencies in the use of these digital health-related technologies, have to be considered (Mantwill et al., 2015).

Barriers by which people are excluded from benefits of digital technologies can be differentiated in three levels: (1) lack of access (e.g., due to inability to pay for devices and their running costs or due to missing infrastructure), (2) lack of motivation among people who do not believe that connectivity is relevant to their lives or worth the effort, and (3) lack of digital skills and education (e.g., digital health literacy) (van Deursen & van Dijk, 2014; Watts, 2020). All of these factors adversely impact the digital (health) divide, which refers to the gap between individuals, households, organizations, and geographic areas at different socio-economic levels concerning both their opportunities to access digital technologies and to their use for a wide range of activities (OECD, 2001), which may directly or indirectly affect health behaviors and health status.

Research conducted in the context of the COVID-19 pandemic showed that several population groups identified as vulnerable (e.g., older people, less educated people, and people with health problems) were less likely to use information and communication opportunities provided by the internet (van Deursen, 2020). The same has been observed for the use of digital technologies in healthcare: Differences exist between individuals and social groups in terms of access to digital technologies but also in terms of their capacity to obtain benefices from their use of the respective technology (Beaunoyer, Dupéré, & Guitton,