Diffusion of Technology in Health Care

How innovation affects the health economy Sudha Shenoy and Geof Hileman November 2020

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Photo: iStock.com/MF3d

What is innovation? How does technological innovation take place?

Throughout the COVID-19 pandemic, each of us has wondered when life will get back to “normal.” This is a natural, human response to trauma. However, as 2020’s interruption of normalcy continues, we must begin to question whether a return to normal is necessarily what we should desire.

In the American health economy, “normal” is broken. In 2018, health care represented nearly 18 percent of gross domestic product (GDP), a figure higher than at any other point in history¹ and far higher than any other industrialized nation.² Initiative 18|11,³ a joint effort of the Society of Actuaries and the Kaiser Family Foundation, has brought together key thought leaders to further illuminate this problem and begin to offer solutions. This article explores some of the key factors that lead to technological innovation, how new technologies are disseminated to society and how such innovation may soon impact our health economy.

Drivers of Innovation

Innovations can be driven either by technological advancements or societal calls for action. One of the most well-known and impactful inventions in world history is the printing press, which arose from a confluence of other technological progress such as the development of manufactured paper and ink. Gutenberg corralled these into a machine that helped propel the world toward modernity.

In more recent times, an economic collapse into the Great Depression led to the development of policies under President Roosevelt that would transform American society and government. In 2020, the American health care system is at an intersection of a clearly defined crisis point,⁴ and the rapid development of new technologies is sure to be part of a solution.

A 2006 paper⁵ in the Harvard Business Review defined three distinct types of innovations in health care.

1. First, consumer-focused innovations are those that improve the experience of being a patient. This can include enhanced access to providers, tools that encourage shared decision-making or price transparency initiatives.
2. A second category is innovative business models. This is a wide category that encompasses novel insurance designs, provider-centric risk-sharing arrangements, direct primary care or centers of excellence for specialized treatment of infrequent conditions.
3. The third category of innovation is technological innovation, which will be the primary focus of this series of articles. Technological innovation in health care can take the form of improved treatment protocols, new drugs or medical devices, or applying artificial intelligence (AI) and machine learning to an ever-expanding library of medical data.

In the rest of this article, we will explore the factors that can result in technologies being adopted—or, ultimately, discarded—and introduce the short- and long-term outlook for technologies that may be well-positioned to help provide a resolution to the problems identified through Initiative 18|11.

How Does Technological Innovation Spread?

In what has become a foundational text in the study of innovation,⁶ Everett Rogers lays out five attributes of innovations that hold the key to how quickly and widely they are likely to spread. In the context of a system as complex as U.S. health care, none of these five factors is straightforward.

• The idea of relative advantage puts forth that an innovation must be perceived as actually being better than the element it would replace and not simply just different. With the range of often conflicting objectives among the stakeholders in health care, an innovation may hold relative advantage to some parties while others view it as a relative disadvantage.
• Compatibility refers to the degree to which an innovation is consistent with the values and principles that underlie the system in which the innovation will be implemented. Even when an innovation is clearly advantageous, it must not violate some key foundational principle. In health care, we have preconceived notions about who should make decisions and how easily care should be accessed. A solution that jeopardizes one of these ideological underpinnings may be difficult to carry forward.
• Complexity is, expectedly, the degree to which an innovation will require extensive training or new understandings to implement. This can be manifested both in the understanding of an innovation (i.e., it is difficult for a stakeholder to understand why an innovation is needed) or in the manner in which existing systems and processes will be disrupted and require reengineering. In the highly complex health care system, innovations are rarely made in isolation without affecting other system components.
• Trialability is the ease in which an innovation can be tested to determine if the required outcomes are likely to be achieved. Incredible amounts of effort go into implementing trials of innovations in health care, from costly clinical trials of treatments and pharmaceuticals, to demonstration efforts that aim to test new payment models. These trials are complex, costly and often complicated by ethical concerns. Very large samples and, sometimes, long periods of time can be required to demonstrate improvements in cost or other outcomes.
• Observability relates the degree to which the successes of an innovation are visible to others. Especially in health care, innovation can be costly. Reducing that cost can require assembling a critical mass of participants. To do this, information about innovations and their benefits must be readily shared among prospective adopters. In an environment where outcomes are difficult to measure and sometimes in conflict from one stakeholder to the next, the visibility of innovative success can be an imposing challenge.

A 2006 case report⁷ identifies six key barriers to the adoption of new technology in health care:

1. Cost
2. Legality
3. Time
4. Fear
5. Usefulness
6. Complexity

There are antidotes to these barriers, as evidenced by the great strides that have been made in medical technology over recent decades. One key factor driving new technology in health care has been the influence of venture capital. It has been reported⁸ that in the third quarter of 2018 alone, more than $4.5 billion of venture capital funds were invested in digital health efforts. This funding can provide a critical impetus to drive stakeholders toward adoption. The influence of regulatory bodies, as well as Medicare covering the payment, also can help encourage the adoption of new technologies.

While funding and regulatory actions can play a key role in determining which new technologies are primed for widespread adoption, ultimately the diffusion of a new technology into common practice requires the individual decisions of caregivers to change the way that medicine is practiced. This often requires that a critical mass of early adopters be accumulated so that the benefits of a new technology can be realized. A recent example from health care is the adoption of electronic health record (EHR) systems. Once a technology has been adopted by a significant number of users, the benefit of using the technology could increase while the cost decreases because the fixed costs are spread across a larger pool of users. Many new technologies are poised to achieve this critical mass necessary to start making a difference across the health care system.

The Future of Technological Adoption in the Health Care Space

In the short term, both emerging health care technologies and the COVID-19 pandemic have primed the health care consumer for using new technologies. Total health innovation funding for the first half of 2020 hit $9.1 billion, up nearly 19 percent compared to $7.7 billion invested during the same period in 2019. StartUp Health cofounders Steven Krein and Unity Stoakes observe that there has been tremendous momentum in the adoption of technologies in the last few weeks versus the slower progress that was seen in the last few years.⁹

Digital companies like Livongo and Proteus Digital use wireless devices to automatically read and report patient vitals and exceptions to clinicians. Livongo’s CEO Zane Burke feels the pandemic has accelerated a more extensive virtual care delivery model and that remote monitoring will be an important part of personalized care for high-risk patients.¹⁰ Broad population surveillance, early monitoring and warnings can be communicated to patients, and they can be reached when they need care the most—wherever they may be located. Proteus Digital has developed an ingestible drug that monitors patients’ compliance with medications. Virtual health care is becoming mainstream, according to Teladoc’s CEO Jason Gorevic.¹¹

Many digital health companies are using AI behind the scenes in their devices to enhance decision-making by providing more personalized care management and patient guidance. The use of AI has gone beyond identifying fraud, waste and abuse, as well as providing automated responses to common questions or care management protocols. We can expect these types of applications to continue, and patients as well as providers will adopt these technologies.

AI is the perfect platform to help with complex modeling and to sift through the data to help select variables to model the spread of COVID-19. Bio pharma is looking at gene and cell therapies to help deal with HIV, COVID-19 and other viruses, while Stanford University and other pharmaceutical companies such as Editas are developing a gene-editing technology called CRISPR that inhibits 90 percent of the coronaviruses, including COVID-19. The pandemic has broken down some barriers, and there is a greater degree of collaboration among scientists of the world as various pharmaceutical companies are collaborating to develop solutions to the virus that causes COVID-19. Eli Lilly, AstraZeneca, Roche’s Genentech unit, Amgen, GlaxoSmithKline and Lilly partner AbCellera are all in different stages of antibody development—and they share information about their manufacturing facilities, capacity, raw materials and other supplies needed to pump out successful monoclonal antibodies. Through the collaborative effort, the six firms aim to lock down manufacturing capacity so they can deliver their COVID-19-fighting treatments right out of the gate after regulatory approval.¹²

Therefore, the genie is out of the bottle, and there is no going back on the use of various technologies by different stakeholders in the health care system—the momentum will carry us forward. The only question that remains is the degree of adoption by payers, providers and members on how they want to receive health care education, guidance and communication. Therefore, we may see a short-term increase in adoption of some technologies and a slightly longer adoption curve for others. We also expect to see increased virtual health care, and the degree of other technological adoption to vary by population and, therefore, by line of business.

For younger populations, more and more of their lives are conducted online, and it is very natural for them to shop for health care services in the same manner. We expect younger populations will use and demand more digital apps and greater transparency. This population also will be more open to wearable digital devices and convenient options to accessing health care information and conducting virtual health care transactions.

For older individuals, the need for continued social distancing and “business not as usual” will drive behavior change. Medical appointments for Medicare members using telehealth will become common, and as we have seen during this pandemic, it has been accepted by providers and patients. The Centers for Medicare & Medicaid Services (CMS) is evaluating whether expanded telehealth policies should remain, and legislation is being drafted to make telehealth changes in Medicare permanent.¹³

Third-party data management has handled more medical data during the pandemic, and this newfound portability may save on costs for health insurers and providers going forward.¹⁴ Third-party technologies that facilitate disease prevention and management include wearable devices that warn users who come within six feet of other users; technologies that provide appointment reminders; and applications that disseminate health information, provide guidance and alert users if they suspect an infection. AI has been used for emergency room triage during the pandemic, and it can be leveraged in even more ways in the future.

For the longer-term outlook, we can point to some of the more advanced technologies that may have a longer timeline, such as gene therapy and personalized medicine. We need to ask ourselves what we think could happen when the digital generations drive the delivery of medicine. Today’s youngest doctors grew up in the digital age, which may increase the momentum of technology adoption. The Mayo Clinic has appointed a digital officer¹⁵ and is partnering with Google to transfer data to a secure Mayo cloud—to provide data security and use cloud-based computing to develop insights and knowledge derived from the data. The industry has made a series of decisions predicting that emerging technologies will shape the future of health care in the United States.

Implications for Actuaries

What do actuaries need to know about diffusion and costs of technology? What forces impact adoption of technological innovation?

Providers are generally risk averse and have a certain amount of inertia that resists adopting new technologies. This inertia can be selectively overcome. Providers have busy lives and will continue practicing in the traditional way unless an external force—like a regulation or health care crisis—forces them to change their behavior. Health care technologies can save costs; add to costs but improve quality; and a few even can improve both cost and quality. We may need a combination of employers, payers and providers to address funding mechanisms for these technologies in the long run.

The use of big data and technologies can aid health plans and providers in monitoring high-risk patients on a remote basis, tracking compliance with medications and other treatment protocols. For average-risk patients, the use of technology can provide an improved experience through greater data coordination. Technologies like AI can help combine the best clinical practices and insights and make them available to the doctor at the time of treatment. Wellness programs easily can be designed and shared with patients to meet their unique needs. The pressures of current medical practices rarely allow for many wellness discussions with providers, except perhaps during the annual physical examination.

Technology diffusion can be driven by a combination of payers, regulatory bodies, pandemics, consumer demand and technologies like AI to stretch the capacity of providers and assist them in patient care. As we know, selective technologies were put in the spotlight during the pandemic and will continue to grow, but we also can expect additional momentum due to the increased investment in health technologies by new “med tech” firms. We should expect continuous demands from consumers as innovation continues in the health care space.

Copyright © 2020 by the Society of Actuaries, Chicago, Illinois.