Successfully Implementing Digital Health to Ensure Future Global Health Security During Pandemics: A Consensus Statement

Key Points

Question  What digital health recommendations should be adopted by the global health community to address the challenges of current and future pandemics?

Findings  By engaging a diverse stakeholder group of 13 leaders in the fields of public health, digital health, and health care, a consensus was reached on how to implement digital health recommendations to address the challenges of current and future pandemics across 5 main themes: team, transparency and trust, technology, techquity (the strategic development and deployment of technology in health care and health to achieve health equity), and transformation.

Meaning  This consensus statement provides a roadmap for the implementation of digital health policy by stakeholders, including governments, to prepare for and address current and future pandemics.

Importance  COVID-19 has highlighted widespread chronic underinvestment in digital health that hampered public health responses to the pandemic. Recognizing this, the Riyadh Declaration on Digital Health, formulated by an international interdisciplinary team of medical, academic, and industry experts at the Riyadh Global Digital Health Summit in August 2020, provided a set of digital health recommendations for the global health community to address the challenges of current and future pandemics. However, guidance is needed on how to implement these recommendations in practice.

Objective  To develop guidance for stakeholders on how best to deploy digital health and data and support public health in an integrated manner to overcome the COVID-19 pandemic and future pandemics.

Evidence Review  Themes were determined by first reviewing the literature and Riyadh Global Digital Health Summit conference proceedings, with experts independently contributing ideas. Then, 2 rounds of review were conducted until all experts agreed on the themes and main issues arising using a nominal group technique to reach consensus. Prioritization was based on how useful the consensus recommendation might be to a policy maker.

Findings  A diverse stakeholder group of 13 leaders in the fields of public health, digital health, and health care were engaged to reach a consensus on how to implement digital health recommendations to address the challenges of current and future pandemics. Participants reached a consensus on high-priority issues identified within 5 themes: team, transparency and trust, technology, techquity (the strategic development and deployment of technology in health care and health to achieve health equity), and transformation. Each theme contains concrete points of consensus to guide the local, national, and international adoption of digital health to address challenges of current and future pandemics.

Conclusions and Relevance  The consensus points described for these themes provide a roadmap for the implementation of digital health policy by all stakeholders, including governments. Implementation of these recommendations could have a significant impact by reducing fatalities and uniting countries on current and future battles against pandemics.

The COVID-19 pandemic has highlighted weaknesses in global health care delivery systems and public health responses, particularly the long-term national underinvestment in digitization.¹ Many found it surprising that health care data still predominantly exist in silos and are not easily accessible among health care systems because of human and technical factors (ie, little collaboration between teams and a lack of interoperability) and a lack of integrity (thereby compromising trust in those data), and they are underpinned by redundant or not-fit-for-purpose technology. It also became clear that health care data are unequally available across the world, ultimately compromising the quality of health outcomes for individuals and society. At the onset of the COVID-19 pandemic, digital health care was highly fragmented in its support of population health, health systems, and individual patient management at the local, national, and international levels. The collection of data for public health surveillance was irregular owing to a historic lack of investment in digital technology,² and few countries or communities had pandemic preparedness plans that enabled them to rapidly expand their data capture abilities to accurately monitor and track key outbreak information.³ Contact tracing had previously relied heavily on analog systems and could not be scaled up rapidly.⁴ These shortcomings, in turn, limited countries’ abilities to develop informed public health policies, plan appropriate and timely responses, or coordinate action. Illustrating this point, the New York Times called reliance on fax machines a “bottleneck” in the US’s coronavirus response.⁵ Similarly, in Australia, the second wave of infections sent Melbourne into strict lockdown when contact tracing teams were overwhelmed by a slow, manual, paper-based system of collecting, storing, and using health information.⁶ In health care delivery systems (community, primary, and secondary), electronic health record (EHR) use varied widely and ranged from the most mature systems, in which a single EHR was used across a health care organization spanning many health care facilities, to organizations that used different EHRs in different specialties or those that remained paper based.^7,8 The importance of interoperability between health care systems for the transfer (and reuse) of data was recognized and widely discussed but rarely implemented in practice.⁹

Thus, the COVID-19 pandemic has focused the minds of health care professionals, policy makers, scientists, politicians, and citizens on these issues, highlighting the intertwined relationship of health care data, its management, and its impact on public health and generating widespread interest in digital health. Many of the shortcomings highlighted by the pandemic can be addressed through the application of data science and digital health,¹⁰ which allow data to be effectively managed, shared, and used. Although there is no single agreed-on definition of digital health,¹¹ for the purposes of this consensus statement, we consider digital health to mean digital tools, technologies, and services that enable health teams (including all public, private, and academic organizations that provide or support health care) to transform care delivery and empower individuals and society to manage health and well-being.

Recognizing the impact of health care data and data management on public health, in August 2020, an international interdisciplinary team of medical, academic, and industry experts formulated the Riyadh Declaration on Digital Health at the Riyadh Global Digital Health Summit, a Group of Twenty (G20)–related event that provided an international forum to discuss the role of digital health in addressing pandemics.¹² This declaration presents 9 recommendations on data and digital health (Box) for adoption by the global health community (health care professionals, hospital administrators, local or national politicians, policy makers, academics, and scientists) to address the challenges of the COVID-19 pandemic and future pandemics. However, the declaration did not specify how to implement the recommendations in practice.

Box Section Ref ID

We therefore reconvened the expert panel to reach a consensus on how best stakeholders can deploy digital health and data and support public health in an integrated manner to overcome the COVID-19 pandemic and future pandemics. This consensus statement provides a roadmap for digital health policy implementation by all stakeholders, including governments. As a foundation for this consensus statement, we propose that stakeholders must consider digital health, data, and public health collectively to overcome the challenges of the current pandemic and, importantly, any future pandemics (Figure). Such a holistic view of the digital health environment is required to enact the 9 recommendations from the Riyadh Declaration on Digital Health in an effective, practicable, and impactful manner. Perhaps more important, however, implementing the guidance set out in this consensus statement lays the foundation for a more efficient and effective global health delivery system to face future global health threats.

This study followed the Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) guidelines.¹³ The 13 expert panel members were selected based on their internationally recognized expertise in the fields of public health, digital health, or health care leadership across the government, industry, nongovernmental organizations, and academic sectors. Most of the panel members were involved with formulating the Riyadh Declaration on Digital Health¹²; all were participants at the G20 Riyadh Global Digital Health Summit. The evidence used to reach consensus was from the presentations at the Riyadh Global Digital Health Summit from various interest groups and experts who were not members of the decision-making group, as well as PubMed and Google Scholar database searches for relevant articles related to our synthesis. Therefore, all evidence can be regarded as level 5 evidence (opinion of respected authorities) according to the Oxford Centre for Evidence-based Medicine Levels of Evidence.¹⁴

Recommendations were determined by first reviewing the literature and conference proceedings and by the authors independently contributing ideas. Then, 2 rounds of review were conducted until all experts agreed on the recommendations, using a nominal group technique to reach consensus.¹⁵ Prioritization was based on how useful the recommendation might be to a policy maker. The group was encouraged to attempt to reach a consensus, but the chair also encouraged members to include minority or alternative views when a consensus could not be achieved.

Participants came to consensus on high-priority questions within 5 themes: team, transparency and trust, technology, techquity (decreasing inequities in digital health capability and access), and transformation. The concrete action points for adopting digital health to address the challenges of current and future pandemics build on the previously published Recommendations on Digital Health (Box)¹² and are described.

Collaboration between stakeholders in health teams during pandemics to promote the flow of data must be prioritized.

• Create health teams that include the full range of major stakeholders including policy makers (governments and local authorities), education and research institutions (laboratories and universities), funders (insurers and investors), companies (eg, the airline industry and telecommunications), the third sector (charities and associations), health and social care (professionals and clinicians), and, most important, patients and citizens.

• Build competencies in data and digital technologies and systems among health teams, especially, but not limited to, health care workers, so that they have the knowledge, skills, and training to address pandemics.

• Collaborate across sectors to move rapidly from the development to the in-person or virtual delivery of new health innovations.

• Coordinate public health messaging among stakeholders to ensure clear communications and combat misinformation, recognizing that communicating effectively is critical for health and other sectors, government authorities, the media, and the general public.

• Ensure joint planning and action by ministries of health and other government ministries, national pandemic management agencies, the private sector, communities, and community-based organizations, assisted by the international community.

• Place strong emphasis on community participation and action to build resilience and establish the foundation for effective prevention, preparedness, response, and recovery.

The consensus panel recognized that health is already a core dimension in disaster risk management, and health emergency and disaster risk management (Health EDRM) has recently emerged as a critical field for research, policy, and practice that provides an existing and successful framework for pandemic preparedness, particularly in the area of collaboration.¹⁶ Although the World Health Organization (WHO) Health EDRM aims to build capacity and systems across both health and nonhealth sectors to reduce the health risks and consequences associated with all types of emergencies and disasters, the principles can as easily be applied to pandemic preparedness. Although not specifically related to digital health, this framework nevertheless provides a proven model for the scale and composition of the teams required to respond to major health threats and disasters and has formed a solid foundation for consensus around relevant stakeholders, collaborations, and community involvement.

Another existing and useful model for collaboration related to data is the Committee on Data (CODATA) of the International Science Council, which promotes international collaboration to advance open science and to improve the availability and usability of data in research. CODATA supports the principle that research data should be as open as possible and as closed as necessary. CODATA also works to advance the interoperability and the usability of such data, with the view that research data should be FAIR (findable, accessible, interoperable, and reusable). CODATA achieves these objectives through several standing committees, strategic executive-led initiatives, and its task groups and working groups. For example, in the related field of disaster risk reduction, the CODATA task group FAIR Data for Disaster Risk Research develops clear processes to ensure that data are accessible and available following the FAIR principles for disaster risk reduction and climate risk management, but as applicable to pandemic preparedness.¹⁷

Digital health approaches must preserve rights to privacy and consent.

• Securely interconnect data sets using agreed-on data standards, produce common outputs (such as standard minimum data sets), and account for their inherent biases.

• Especially for patients and citizens, practice transparency regarding data collection, generation, and use; biases in the data; and the adoption of new technologies and systems. If machine learning is used to make important decisions, be transparent about how those decisions were made.

• Ensure that data and insights belong to the stakeholder organizations who generate them and that data policies are fair and equal. Empower patients and citizens with their data, including consideration of policies such as “the right to be forgotten” (eg, Europe’s General Data Protection Regulation¹⁸).

• Ensure that surveillance systems combine an effective public health response with respect for ethical and privacy principles.

• Make relevant health data disaggregated by population cohorts and interoperable to support public health, and foster the collaboration that is necessary to do so.

• Enable the aggregation of large quantities of health-related data from multiple pandemics and establish appropriate rules regarding who can use the data and for what purposes, and whether the data will be identifiable.

• Enlist trusted community leaders to bolster public trust in digital health care tools and systems. Invest time in building relationships so that trust exists prior to an emergency, such as a pandemic.

• Accelerate the scientific review process and keep the scientific review process objectively focused on the data.

Discussions highlighted an issue that the blurring of lines between objective scientific debate and politics could potentially erode trust in data. A notable example of this issue is the ongoing debate around the benefits associated with face masks, with the most important factor associated with mask use often cited as political partisanship rather than COVID severity.¹⁹ Therefore, an important aspect of building trust is to ensure a clear separation between science and policy (ie, let data be data and leave policy making to policy makers).

Public health systems should use necessary technology to create and share health intelligence and to collect and use high-quality data.

• Leverage digital technologies for surveillance and crisis communication to unlock meaningful information for public health and research and to provide public health interventions. This information should encompass consumer-generated data and should complement traditional surveillance data by providing (1) information about heterogeneous populations, including those with a range of symptoms; (2) information about individuals’ daily experiences of a condition or disease state outside the clinic; (3) longitudinal data; and (4) timely data and information.

• Ensure technology and data literacy and offer scalable information delivery via the cloud to disseminate timely information based on data-driven and evidence-based protocols.

• Use interactive data visualization techniques to impart necessary health knowledge (eg, how to properly wear a face mask) to the public, probably via the media, and improve citizens’ situational awareness.

• Adopt the “6 Vs” of big data^20,21 (ie, volume, velocity, variety, variability, veracity, and value of the data) to use them effectively.

• Ensure that data analysis systems are instrumental, interoperable, and intelligent to create meaning from the vast amounts of available data for the modeling and prioritization of policies in a pandemic situation.

• Gain valuable knowledge and insights through the application of traditional and nontraditional analytics, including artificial intelligence and machine learning methods.

• Given that the nexus of digital health is often clinical information systems, ensure their interoperability through preemptive discussions between health care professionals, EHR vendors, and public health authorities.

• Put processes in place to ensure that data are FAIR.

Inequities in digital health capability and access at the individual, local, national, regional, and global levels should be decreased, and digital inclusion should be embraced.²²

• Continue to support internet connectivity in its many forms while increasing efforts to improve digital skills.

• Monitor health inequities in the relevant dimensions (demographic, socioeconomic, geographical, and technological). Collect data for evidence-based, equity-related policies, programs, and practices that aim to bridge gaps and promote health and well-being.

• Mitigate inequities by enhancing access to digital health services, developing the accessibility and use of services and devices, training staff, providing local community organization support, hosting local community events, and promoting digital champions. At the global scale, digital inequality can be addressed through policy work and advancing internet connectivity in its many forms while increasing efforts to enhance digital skills.

• Invest in technology and infrastructure, such as low-cost wireless and satellite connectivity, subsidized mobile phone plans, loaner devices, free WiFi hotspots, and training programs. Federal and private sector investments should be devoted to technology and infrastructure.

Digital health should transform individual and population health and the health and care systems that support them.

• Implement data-sharing standards and a standard global minimum data set for public health data reporting, as well as a data governance structure tailored specifically to communicable diseases.

• Embark on a digital transformation of existing health care systems to strengthen the public health surveillance system by using health technologies, such as public health surveillance systems, EHRs, clinical decision support systems, and patient management systems.

• Empower citizens to use mobile technologies to manage their health and thus contribute to disease prevention.

• Develop digital personal tools and services to support comprehensive health programs (in disease prevention, testing, management, and vaccination) globally.

• “Think locally and act globally” to ensure that the digital transformation shift is implementable to serve local needs yet interoperable across the wider health care digital environment globally and that it does not stray from its intended purpose to advance individual and population health.

• Implement public-private partnerships to support the development of systems and data sharing.

Using a nominal group technique, we engaged a diverse stakeholder group across multiple sectors to reach consensus on how best to deploy digital health and data and support public health in an integrated manner to overcome the COVID-19 pandemic and future pandemics. In doing so, participants came to consensus on high-priority questions within 5 themes: team, transparency and trust, technology, techquity, and transformation.

Working in teams and public-private partnerships represents a critical foundation of accelerated science (ie, delivering results based on data in a timely manner), such as witnessed for the COVID-19 vaccine development and delivery. Our action points encourage partnerships that intertwine comprehensive ecosystems, a culture of collaboration and cooperation, and engaged patients and citizens with full knowledge, rights, and consent on how their data are used and processed. Adopting such an approach from discovery to development to the delivery of innovation in health care should accelerate the delivery of regulatory requirements. In practice, stakeholders should have a diverse set of interests, but each should fulfill a specific role in the health of citizens, and this collaboration will act to integrate and synergize the best knowledge, skills, and training that all health team stakeholders (especially patients and citizens) have to offer.

However, engaging different stakeholders to effectively collaborate and share data and information relies on trust and transparency, without which they will be unwilling to share data to enable digital health technologies, such as digital surveillance, to address pandemics.²³ Our consensus action points specifically address the factors that erode trust, especially among the public, such as data generation in poorly secured systems²⁴ and restricting data sets to individual stakeholders in silos.²⁵ Our framework combines a public health response with a respect for ethical and privacy principles, which is fundamental for building trust and transparency in the use of digital tools,²⁶ because a lack of public trust may decrease compliance with public health advice or recommendations, adversely impacting health outcomes.²⁷ Community leaders should be enlisted at the grassroots level to bolster public trust in digital health care tools and systems wherever possible because it is difficult to build a trusting relationship through mobile technologies alone.

Digital health technologies and consumer-generated data have the potential to provide timely and accurate data and information about disease, but this potential is hampered by aging systems, obligations to submit data to multiple programs in different formats (potentially an error-prone process), and underreporting that may affect data quality and, ultimately, the sensitivity and predictive value of a surveillance system. There was consensus that digital technologies can overcome these problems. However, the existence of technology and data does not necessarily equate to usable data. Although most industrialized nations have extremely high EHR penetration and use, these technologies presented a limiting factor throughout the pandemic. Data remained trapped within EHRs and subject to software vendors and proprietary relationships and burdens placed on the EHR user. Essentially, the capacity for health care professionals to provide public health authorities with needed data became almost intractable. Compounding the issue was the public health authorities’ absence of understanding and knowledge of clinical and laboratory operations and information systems, limitations that ultimately led to untenable policies and rule making. For future pandemic preparedness, this bottleneck needs to be anticipated through an already existing collaboration.

Successful pandemic preparedness relies on uniform, global digital health capability and access. The rate of mobile technology adoption is very high in developed countries (94%) and is rapidly increasing in developing nations (78%),²⁸ but barriers to access to internet connectivity and, consequently, to digital health care can reinforce serious inequalities. Groups that are digitally excluded have a greater risk of poor health.²⁹ Techquity means that specific people or groups should not be denied the means of achieving a state of health that is available to others through digital skills development, internet access, digital health literacy, and minimization of the effects of harmful digital marketing on health and well-being. Our consensus mitigates against digital exclusion at the global, regional, national, local, and individual levels and addresses the need to train and include those from disadvantaged populations to contribute to and participate in decision-making related to digital health.

Will the COVID-19 pandemic be a tipping point for digital health? In 2022 and beyond, the inevitable transformation of health will be accelerated owing to a strengthened focus on the need for data and digital access to advance population health and wellness. The guidance provided in this consensus statement, if followed, would lay the foundation for much greater resilience to future pandemics.

Similar to our 5 themes, the WHO Global Strategy on Digital Health provides a blueprint for how to transform current systems to address future pandemics and has 4 main objectives: collaboration and knowledge transfer, implementation of digital strategy, digital health governance, and provision of human-centered health systems at the global level.³⁰ Furthermore, the recently published report of the Health Information Technology Advisory Committee (HITAC) Public Health Data Systems Task Force, which examined the effectiveness of public health data systems to support high-consequence public health threats, provides targeted actions and recommendations, including cross-cutting recommendations to create a preparedness plan and data standards for collecting public health information; working with federal partners to create a health data ecosystem that fully supports public health; working with payers to promote the adoption of health care information tehnology standards and secure data exchange; and supporting data modernization and standardization initiatives.³¹ As such, our consensus statement complements the WHO Global Strategy on Digital Health and HITAC recommendations by providing actions specific to pandemic preparedness that create the preconditions at local and national levels on which the WHO action plan and HITAC recommendations can be implemented at supranational levels.

This study has some limitations. The results and the derived guidance represent the consensus of 13 subject-area experts. Other stakeholders, including those from government and the community, must be included in ongoing dialogue and must represent a wider array of public and private sector entities (eg, artificial intelligence).

This consensus statement, building on the Riyadh Declaration on Digital Health, is intended to inform the digital health strategy for the broadest range of stakeholders around the world. We hope that the public, governments, the private sector, nongovernmental organizations, and/or civil society organizations will adopt these principles to influence national, regional, local, and international policies and actions and thereby achieve a connected global health system to prepare for and respond to the continuing COVID-19 pandemic and other global health crises to come.

Accepted for Publication: December 10, 2021.

Published: February 23, 2022. doi:10.1001/jamanetworkopen.2022.0214

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Al Knawy B et al. JAMA Network Open.

Corresponding Author: Bandar Al Knawy, MD, King Saud Bin Abdulaziz University for Health Sciences, PO Box 22490, Riyadh 11426, Saudi Arabia (knawyb@ngha.med.sa).

Author Contributions: Dr Al Knawy had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Crooks.

Drafting of the manuscript: Al Knawy, McKillop, Abduljawad, Tarkoma, Bates, Lee, Kozlakidis, Crooks.

Critical revision of the manuscript for important intellectual content: McKillop, Abduljawad, Tarkoma, Adil, Schaper, Chee, Bates, Klag, Kozlakidis, Crooks, Rhee.

Administrative, technical, or material support: Al Knawy, Abduljawad, Tarkoma, Lee, Crooks.

Supervision: Al Knawy, Chee, Rhee.

Conflict of Interest Disclosures: Dr Bates reported receiving grants from EarlySense; personal fees from CDI Negev; equity from ValeraHealth, CLEW, MDClone, and FeelBetter; personal fees and grants from IBM Watson; and equity and personal fees from AESOP outside the submitted work. Dr Rhee reported beng a former IBM employee and current CVS Health employee during the conduct of the study. No other disclosures were reported.

Disclaimer: Although Dr Kozlakidis is identified as personnel of the International Agency for Research on Cancer/World Health Organization (IARC/WHO), the author alone is responsible for the views expressed in this article, which do not necessarily represent the decisions, policy, or views of the IARC/WHO.