Revolutionary advances in digital health are transforming health, medicine, and biomedical science. Technological developments such as cloud computing, artificial intelligence, machine learning, digitally mediated diagnostics and treatment, telehealth, and consumer-facing mobile health applications are prevailing. These developments promise to drive earlier diagnoses and interventions, improve outcomes, and support more engaged patients. However, the promise of digital health remains illusory, authors say. U.S. health policies and health system investments remain misaligned with these insights. Despite tremendous advancements, digital health is still in its infancy. The COVID-19 pandemic marked a pivotal event that might result in rapid transformation. Therefore, digital health adoption requires careful consideration and effort to guarantee that underserved people are not left behind. The promises of improving patient access to data and boosting health equality may be realised via inclusive methods.
Digital Health in the 21st Century
Digital Innovation and Medical Care
Advancing Diagnosis and Treatment
Facilitating Off-Site Patient Management through Telemedicine
Partnering with Individuals to Support Self-Management
Reducing Error and Waste in the Delivery System
Digital Innovation and Population Health
Digital Innovation and the Social Determinants of Health
Digital Innovation and Health Behavior
Digital Innovation, Genomics, and Precision Health
Digital Innovation and the Learning Health System
Leveraging Big Data for Knowledge Generation
Leveraging Big Data for Population-Level and Public Health Insights
Requirements for the Digital Health Infrastructure
Individual Access and Engagement and Equity and Ethics
Privacy and Identifier Protocols
Data Quality and Reliability, Storage, and Stewardship
Artificial Intelligence and Machine Learning
Stewarding Digital Innovation for Our Health Futures
Embedding Equity and Transparency as First Principles
Reforming Health System Payments in Support of Outcomes and Value
Nurturing a Learning Health System Ethos
Establishing Seamless System Interoperability
Expanding Algorithm Validation and Real-World Testing
Digital Health in the 21st Century
Digital health has evolved as a broad term encompassing electronically captured data, along with technical and communications infrastructure and applications in the healthcare ecosystem. Developments such as cloud computing, artificial intelligence, machine learning, blockchain, digitally mediated diagnostics and treatment, telehealth, and consumer-facing mobile health applications are now routinely used in self-management and health care.
Digital Innovation and Medical Care
Digital technology has now been developed and applied to every aspect of health and health care. Figure 1 groups the various digital health tools into a dozen application areas. The individual applications number in the thousands.
Advancing Diagnosis and Treatment
Research shows that a significant proportion of health spending is attributed to chronic diseases, with individuals experiencing multiple comorbidities accounting for a disproportionate share of expenditures. To address these problems, innovators, software vendors, payers, and government regulators are investing heavily in digital health solutions.
Ensuring Care Continuity
Even the most sophisticated digital diagnostics will have little impact on clinical outcomes if they are implemented in a fragmented health care ecosystem. Regulations promulgated by the 21st Century Cures Act Final Rule (Cures Act) have the potential to address this shortcoming by promoting seamless interoperability.
Facilitating Off-Site Patient Management through Telemedicine
Consumer-facing apps and clinical monitors that actively or passively collect data can also serve as an early warning system for prevention and disease management. Digital tools that collect data and support interventions outside the clinical setting offer meaningful opportunities to identify risks and engage patients. Remote patient monitoring (RPM) tools increased during the COVID-19 pandemic.
Partnering with Individuals to Support Self-Management
Most chronic disease management occurs outside of the traditional health care setting. Partnering with individuals so that they can fully engage in their care and meeting people where they are physically and mentally is essential. But meeting individuals on their terms may present multiple challenges to both individuals and the delivery system. Basic knowledge gaps about anatomy and physiology are worsened by issues of language fluency, health and reading literacy, numeracy, conflicting cultural beliefs, and limitations in cognitive capacity.
Reducing Error and Waste in the Delivery System
Extensive research indicates that health care resources are inappropriately allocated within the current system. Disruptive innovation has been foundational across sectors to reduce waste and increase efficiency. By 2017, 80% of office-based physicians and 96% of non-federal acute care hospitals had adopted certified EHRs.
Digital Innovation and Population Health
The importance of using digital tools in helping to integrate social services into care delivery has been clearly demonstrated by the nation’s experience with COVID-19. Digital health tools can potentially improve the identification, measurement, and modification of the root sources of illness, health, and well-being.
Digital Innovation and the Social Determinants of Health
Kaiser Family Foundation defines the social determinants of health (SDoH) as the conditions in which people are born, grow, live, work and age that shape health. Approximately 15% of premature deaths are attributed to SDoH; these upstream drivers of health have largely been considered out of scope and not yet routinely addressed by providers or health care systems.
Digital Innovation and Health Behavior
Digital health technologies are developing new use cases to address various environmental factors, including air pollution and climate change. Digital inhaler sensors have been used to monitor when and where patients with asthma used medications and needed adjustments to treatment plans. Consumer-facing tools also can provide smartphone alerts for heat or air pollution data.
Digital Innovation, Genomics, and Precision Health
Digital technologies are accelerating the health implications of structural and functional variations in the human genome. Whole genome sequencing and digitally enabled risk scores generated by such sequencing will help identify individuals and groups at risk for common health conditions in their earliest stages. This data can be used to support mitigation strategies such as behavior change, medication use, or early screening (to know more, please check out the talk by Dr Fergus Imrie and Dr Michiel Niesen).
Digital Innovation and the Learning Health System
Digital health will be critical, and its promise must be fully leveraged. Effectively applied, digital health tools have the potential to catalyze progress on each of the key principles for a digitally facilitated learning health system.
Leveraging Big Data for Knowledge Generation
Much of the data collected in clinical care or recorded in consumer apps are available for further research and learning. There is an unrealized opportunity to share, aggregate, and analyze that data in alignment with the goals of a learning health system. Virtual health data trusts, with shared governance and individuals controlling and contributing their data to support scientific discovery, present an important opportunity to distribute the costs and maximize research output.
Leveraging Big Data for Population-Level and Public Health Insights
To apply analytics tools to health care will require significant investment. The Cures Act authorized $1.5 billion over 10 years to support the NIH’s All of Us Research Program. Public health agencies are positioned to seamlessly collect data and apply advanced analytics for health surveillance.
Requirements for the Digital Health Infrastructure
Digital technology serves as the nervous system for the learning health system. It accelerates the identification and elimination of wide-scale disparities in individual, local, regional, and global health care. As individuals gain more access to their health data via application programming interfaces (APIs), it is essential to consider several foundational infrastructure requirements.
Individual Access and Engagement and Equity and Ethics
To ensure digitally facilitated health for all, access to digital health writ large, supported by widespread broadband internet access, is essential across all economic strata and all regions of the U.S. The public has routine exposure to digitally facilitated convenience, agency, transparency, and privacy based on their experience with other industries.
Privacy and Identifier Protocols
The opportunity to share, aggregate, and analyze health data to improve individual health and advance the learning health system is significant. Consumers have a limited but growing understanding of the risks (including loss of privacy) and benefits of sharing their health data. The expansion of HIPAA to redefine and protect health information outside of covered entities could mitigate risks to individuals. (More about computational privacy beyond consent and anonymisation is discussed in this talk from Prof. Ramesh Raskar (MIT))
Cybersecurity
Cybersecurity and privacy concerns are major obstacles to digital health adoption. A public-private partnership is necessary to develop a superstructure framework to ensure the safety, security, and privacy of digital health architecture. Privacy and security risks with big data and AI require special attention.
Data Quality and Reliability, Storage, and Stewardship
Foundational to digital health, the standards and curation protocols for data and information are not required by regulation. Data standards and stewardship guidelines and national cooperation are critical, while attention must be paid to economic, legal, philosophical, and practical issues relating to health data (NASEM, 2020)
Interoperability
The COVID-19 pandemic illuminated the needs and opportunities for digital health. The rapid pace of the pandemic emphasized the need for a rapid learning system that relies on capturing, organizing, sharing, and analyzing large amounts of data digitally across public health, research, and clinical systems.
Artificial Intelligence and Machine Learning
As the U.S. moves to value-based payment models, transparent and advanced analytics are needed to calculate population risk. Harnessing AI will depend on coherent data architecture and diverse training datasets, which are large, sampled adequately. The regulatory framework for AI as a medical device is nascent.
Workforce
To support digitally enabled health in a learning health system, the workforce of the future will require a comprehensive set of skills that are currently rarely seen. Clinicians, health system staff and management, and vendors/innovators will all require at least basic or conceptual knowledge of data management (collection, storing, normalizing), interoperability, data governance and collaboration, ethics, process improvement, and implementation science.
Stewarding Digital Innovation for Our Health Futures
Key priorities must be identified and pursued within both the environmental and the technical contexts to achieve the full potential of digital health. The key priorities in the environmental context include focusing on the individual, embedding equity and transparency as first principles, reforming health system payments in support of outcomes and value.
Focusing on the Individual
Health data are intensely personal, and unintentional exposure of that data has the potential to upend an individual’s life. Capturing the full potential of digital health will require broad confidence in health systems and commercial ventures to protect the individual from negative outcomes.
Embedding Equity and Transparency as First Principles
The rapid development and application of digital health is also accompanied by the need for vigilance on equity and equality issues. Data must reflect diverse communities and populations across the U.S. Here again, the health system, researchers, and commercial ventures must address issues of mistrust.
Reforming Health System Payments in Support of Outcomes and Value
COVID-19 has provided a further reminder of the systemic shortcomings of fee-for-service reimbursement. Policymakers must also address concerns that extending digital technologies will increase costs and the risk of fraud and abuse. Infrastructure improvements required to advance the digital functions of a learning health system are often unfunded.
Nurturing a Learning Health System Ethos
The vision of digitally facilitated health depends on a continuously learning health system. The delivery system has an opportunity to reimagine and recreate a care system that is culturally attuned, personalized, holistic, and comprehensive. Rapid cycle learning must also be employed, as it will enable the necessary organizational agility to respond to an accelerated rate and nature of change.
Establishing Seamless System Interoperability
Seamless connectivity and communication among healthcare-related devices are essential prerequisites for promoting optimal health. Progress is uneven across the industry, with some health systems being pioneers in real-time data sharing while others are lagging.
Ensuring Cybersecurity
The rapidly evolving landscape of cyberattacks highlights the need for collaboration across the government, health organizations, and consumer-facing vendors to develop a consensus on security protocols. Places to start could be the expansion of HIPAA, the national application of the California Consumer Protection Act.
Expanding Algorithm Validation and Real-World Testing
There is a clear need to invest in the capacity and cooperation necessary to advance data science and AI. A regulatory framework must address certification of constantly changing algorithms and hold vendors accountable for valid and reliable processes.
Priority Near-Term Actions
A multi-stakeholder panel should be convened to develop recommendations to meaningfully engage the diverse individual consumers of health care in all health care sectors. Congress should promulgate rational, right-sized, risk-based regulation, standards, and frameworks to enable the seamless flow of data while protecting privacy. CMS should lead the effort to ensure sustainable payment coverage to ensure equal access to digital health tools for all individuals and providers. Finally, the digital health future is focused on predictive, proactive care keeping individuals healthy based on their particular needs.. Healthcare organizations may reduce costs, boost operational efficiency, and improve patient outcomes by deploying the correct tools, technology, and strategy.