Nothing less than a digital health revolution is at hand, the effects of which will be very apparent by 2030. We focus here on the nexus between digitalization and healthcare challenges, including the personalization of healthcare to individuals’ needs, the centrality of data, and the role of the social contract within healthcare.The digital health revolution
The unsustainable rise in healthcare costs around the globe, currently estimated to be approximately USD 9 trillion1 annually and projected to increase to USD 24 trillion by 20402, represents a major challenge to global health. All levels of the healthcare ecosystem are facing unprecedented societal burdens, including a world population projected to grow to 8.5 billion by 20303.
Individuals are living longer, with some countries like South Korea preparing for an average life expectancy of 90 years by 20304. Increasing age is associated with a growing number of health issues, while unhealthy lifestyle choices are leading to a rapid global growth in the prevalence of noncommunicable diseases (NCDs) and multiple chronic conditions (MCCs). Today, it is estimated that one in three adults globally, and up to three in four adults in developed countries, suffers from MCCs, a variable combination of chronic respiratory, cardiovascular, metabolic, cancer and mental health disease5.
SDG#3, “Good Health and Well-being”, aims to ensure healthy lives and promote well-being for all, at all ages. It addresses the widening economic and social inequalities that impact access to basic services, consistent care and medication. It confronts the disparities between countries with the shortest and longest life expectancies, and demands action on emerging illness trends, from antimicrobial resistance to noncommunicable diseases.
Partly as a response to these challenges, the healthcare ecosystem is experiencing a revolution through continuous scientific discovery such as genomics and new forms of molecular therapies, accompanied by a boom across the technology landscape that has sparked the development of new and innovative hardware, software and digital applications in medicine. Together, these offer a next-level collaborative approach whereby software, connected devices and data analytics are combined in increasingly creative ways to improve the individual’s experience of and access to care – including from the comfort of their home.
Portable devices, including extending and augmenting use of the mobile phone and other sensors, have allowed individuals to monitor and share real-time medical information with providers. However, research and clinical data is being collected at a rate that has outpaced the ability to aggregate, curate and systematically leverage its best uses in healthcare globally or even on a national scale.
Nevertheless, these data hold the power to positively impact quality of life for millions around the world and provide widespread improvements at every level of the health ecosystem, including in locations where access to care has been more limited.
The World Bank Group provides a guide6 by which the impact of technology on the global healthcare ecosystem by 2030 can be assessed through describing the need for a substantial pivot in both health financing and public health approaches. Many barriers and challenges remain unresolved, so the aim is to focus upon the potential global impacts of digitalization in 2030, as well as society’s collective needs and capabilities for preparedness in the coming years. In this process, it is important to address specifics behind the need for a digital technology revolution, challenges within, and the steps that can be taken in order to ensure our 2030 success.
Current approaches to healthcare need to improve - individually, socially and systematically. A better understanding of personal and social roles can translate into wellness and prevention, thus superseding the current sick-care focus. There is some optimism: by 2030, the healthcare industry is likely to have shifted towards a more integrated ecosystem, enabled by the digital health revolution and supported by the development of new frameworks and systems. An example of this is in the US, where major tech companies such as Apple, Amazon, and even Uber are moving into the healthcare space.
The patient-provider relationship has begun to shift from a paternalistic model of prescriptive treatment and compliance, towards a more open dynamic where patients are increasingly integrated into the care process.
However, this needs to be improved and accelerated to reduce costs and improve outcomes. Rather than a system built upon linear, episodic reactions to illness, benefits are more likely with a closed-loop model, guided by wellness and more actively addressing personal responsibility, continuous transparency and information ownership. Technology holds the power to impact each step in the closed-loop model by improving individual awareness and engagement, automating processes for both providers and management systems.
One of the most powerful ways to incentivize individuals to actively invest in their own wellness future is to empower them with information. With the right information available, individuals can better recognize what they can control. Populations currently least well-served by advances in healthcare – those with lower education and income levels – stand to gain the most from information that is presented intelligibly. This should be a key focus area for the likes of Google, Facebook and public health and/or hospital care providers.
The practice of defensive, liability-driven medicine is one of the costliest aspects of healthcare and arose from a paternalistic system in which individuals had little understanding of or participation in their own care. Transparency fosters trust, which can improve individual engagement and reduce the likelihood of litigation, thus leading to better overall outcomes and reduced costs.
Technology holds the power to bridge the gap between patient and provider, shifting the healthcare ecosystem from defensive to collaborative care. As individuals better understand how their data is used and are able to interact more with their own information, the trust gaps that normally hinder the sharing and transformation of data into actionable information can narrow, and the ecosystem as a whole will be poised to advance7.
As global trends related to illness, disease and healthcare costs continue to escalate unsustainably, technology has enabled the collection of health data at an exponential rate. Data collection in healthcare has outpaced all other sectors, and our ability to translate that data into knowledge and actionable information is increasing.
While the collision of these global trends creates the possibility for a new model of sustainable healthcare delivery, it also requires a continuous and balanced dialogue around the risks and opportunities afforded by integrating both formally and informally generated health data.
The dimension of privacy is an ever-greater concern across the globe, underlining the urgent need for more current policies, and regulatory and governance mechanisms that have until now not been required. Without these, the danger is very real that today’s defensive, risk-averse, and, in some geographies liabilitydriven medicine, will add substantial cost to digital health in the same way, thus slowing its adoption.
Data holds little or no value when it is static or pure, but when it is dynamic, placed in new contexts, combined and reused, it grows exponentially in value. In order to translate the ever-increasing amounts of collected healthcare data into valuable and actionable information, a multi-pronged approach is needed between the individual, provider and system. Individual access to and ownership of health data, as well as the understanding of how that data can be used, will allow for dynamic consent on its use. Participants in research studies, for example, are required to sign formal agreements that specify the use of information in a particular study.
These agreements outline data use, storage location and retention time, the involvement of third parties, the sensitivity exchanged, and whether consent to use can be revoked. As the boundary between health data gathered for clinical and research purposes blurs however, such agreements do not have to be isolated to research and could be made available across clinical settings.
Individual ownership alone, however, does not improve the system, which remains largely siloed in how it collects and uses data. Healthcare data collected for research and clinical purposes, for example, are widely separated and, within each framework, are often owned and protected by a large number of parties unable or unwilling to share with one another. In addition, great challenges exist in the ability to bridge national and international data sources. Inevitably, this leads to the costly practice of duplicating research that could otherwise translate globally.
Legacy systems are often founded in more conservative ideals that view IT over data as the primary asset, and are reluctant to adopt new technologies that enable improvement in data use. By 2030, the creation of structured and functional specifications governing safe and trustworthy data sharing and use can reduce current reluctance at national and international levels, across sectors and industries, and allow for actionable information to flourish.
Providers would be armed with information for better tracking of their patients, trend identification, prediction of illness and disease, and decision-making support. Providers would also be better equipped to engage patients in understanding their activity levels and vitals, as well as how these numbers play into their overall health profile. In addition, with machine learning and digitalized records, hospital systems could improve pattern-of-care recognition, thereby allowing for earlier and more accurate treatment, as well as a reduction in unnecessary treatments, tests and overnight stays. Staffing and billing problems, both of which account for a large proportion of hospital expenditures, could also be automated and streamlined, thus freeing additional resources for more direct patient care.
When entering the medical field, providers take an oath created for patient benefit, including the responsibility to provide lawful, competent and professional medical care with compassion and respect for human dignity and rights; a commitment to continued medical education, including improvement of the community and public health; and supporting the best interests of the patient, including access to care for all8.
In return, society agrees to a social justice that providers will be granted sufficient autonomy to act in the best interests of their patients, to trust in the provider’s competence and devotion, to allow a degree of self-regulation guided by the law, and to provide a functioning healthcare system that includes proper resources9.
Originally, social contracts were geographically determined, mainly because local taxes helped define the benefits of the region to which taxes were paid. However, the digital age has surpassed jurisdiction and, as technology advances in parallel with an increasing need for structured, aggregated and usable data, a new, triangular contract is needed between the system, the provider and the society or individual. This promotes co-management of health, a shift in responsibilities to be more proactive, management of expectations, and a movement from blind trust towards accountability. Such a contract needs to account for the fact that health data ownership and use is more easily accessed by those of higher income and education.
Technology integration and data sharing are limited in practice, not only because of individual consent, but also because of infrastructural inertia. For example, the technology to drive integration of personalized data into the healthcare system is available, but large separations between institutions, sectors and systems have hindered its use, and any new social contract will need to address such alignment barriers. Were functional specifications and policy to be placed at the forefront of the initiative, such channels could be opened, and a more connected ecosystem would be fostered.
Transparency remains a key enabler for improvement, particularly within the patient-provider relationship and for those who face additional educational or socioeconomic hurdles within the system.
As the demand for interconnected IT environments for data sharing increases, by 2030 cybersecurity will be a top priority for the industry. Stakeholder engagement to increase levels of transparency while protecting patients is recognized as vital. Patient advocacy groups can support the translation of these topics to their individual members, including the idea that enlightened altruism will need to drive individual participation.
When asked to share personal health information, the individual question is, “What’s in it for me?”, and the answers are: the collective good, and the knowledge that, should you one day need to benefit from proper data use, you will have access to better healthcare.
While the last twenty years were focused on the human genome, the next twenty will focus on new biology, with collaborations across the biological, computational and mathematical spaces to identify solutions to improvement in human health and sustainable food production.
Food companies are investigating macronutrients in food development, as well as sustainable production for both preventive health and the environment. Consumer-facing platforms are starting to connect traditionally disjointed health-related services.
Thus, industries are merging, and partnerships are forging across health, food and pharmaceutical lines. In other examples, a growing number of pharmaceutical companies are partnering with medical devices, delivery devices and software technologies to improve both the efficacy of treatments, as well as the availability of real-world data captured during the treatment process. Financially incentivizing such collaborations and the outcomes they deliver could be one way to drive additional progress.
- Deloitte. (2019) Global health care outlook
- Global Burden of Disease Health Financing Collaborator Network. (2017) Future and potential spending on health 2015–40: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries. The Lancet, DOI
- Kontis et al. (2017) Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. The Lancet, DOI
- Kontis et al. (2017). Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. The Lancet, 389(10076), pp. 1323-1335
- Hajat et al. (2017) The case for a global focus on multiple chronic conditions. BMJ Glob Health, DOI
- World Bank. (2019) High-Performance health financing for universal health coverage
- Sharma. (2018) Who Really Owns Your Health Data?
- Copenhagen Institute for Future Studies. (2019) Nordic Health 2030