Policy Research Institute page Thinking about the ecosystem in the healthcare field Discussion Points on the Data Ecosystem

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It has been six years since the Pharmaceutical and Industry Policy Institute (Policy Research Institute) began studying the use of big data in the medical health field. There is a growing awareness that large volumes of diverse information will become a source of new value in the next generation society (super-smart society) as an alternative resource to oil, and a deeper understanding of the data-driven society that will arrive in the near future is also growing. The focus of future discussions is shifting to how to increase the types and accuracy of this information, and how to build a mechanism from collection to utilization, in other words, how to realize the creation of a "data ecosystem" that will develop autonomously and continuously. We have considered the "future of healthcare" from the perspective of data ecosystems, which encompass medical care and are becoming borderless with the rest of society.

With the rapid progress in the IT field, major changes (paradigm shifts) in industries, systems, and society are being born, and the word "ecosystem" is often heard in the midst of these changes. As you know, the term originally referred to an ecosystem that is in continuous harmony with the interaction between living organisms and the environment in the natural world. It is truly a buzzword, but it has also become a key word in the great social transformation known as the Fourth Industrial Revolution.

This transformation can be seen as the embryo of a new social model, a data-driven society, that is being born. It is said that this is an era in which those who control data control business and society. In the field of medicine and healthcare, the analysis of the relationships among various data is progressing, including not only medical data and health-related data, but also lifestyle data, preference and behavior data, and data on the individual's genome, omics, and other biological molecules, as well as data on the environment that surrounds the individual. This is about to change to a stage where value such as new discoveries and solutions will be created.

In order to promote and revitalize this trend, it is necessary to share widely at the national level the recognition and realization that the utilization of such data creates great social and economic value, and to build a "data ecosystem" in which the flow of data generation, distribution, utilization, and implementation of results (enjoyment of benefits) circulate smoothly. I feel that it is necessary to build a "data eco-system" that smoothly circulates the flow of data generation, distribution, utilization, and implementation of results (enjoyment of benefits).

I would like to take a look at the "future of healthcare" from the viewpoint of data ecosystems, which will encompass medical care and become borderless with the rest of society. I would like to take a look at the "future of healthcare" from the viewpoint of data ecosystems.

Ecosystem Concept

First, let us consider the ecosystem. It is said that the concept was first widely used in the business field in the early 1990s as an explanation of the success or failure of startup ventures in Silicon Valley on the West Coast of the United States. *1As a term to describe the environment surrounding startups, the term "ecosystem" was used to describe a situation of sustainable coexistence by promoting cooperation with venture capitalists and business-related companies, etc., leading to successful venture startups and creating a virtuous cycle of win-win for all cooperating parties. Currently, the expression "aiming for an ecosystem" is used for a wide range of subjects, including the introduction of new systems and innovations in the ICT industry and other industries, and the establishment of new businesses and open-platform research systems.

For example, in the case of a new ICT-related business, the main player driving the business (often described as the keystone*2), various companies involved in the business (niche players; borderless across industries), and in many cases, various stakeholders including consumers and society are all involved in the collaborative economy. In this "ecosystem," the main players are the main players. In this "ecosystem," the main players are able to create new value and innovations that would be difficult to obtain through traditional "self-focused" approaches, and to collaborate to expand complementary relationships in the value chain. Furthermore, the system will be sustainable and expand as many participants and society can benefit from the system together.

It is difficult to define the broad "ecosystem" expressed in business terms, but it is often used figuratively, focusing on the process of "coevolution*3. The SOMPO Institute for the Future describes the pattern shown in Figure 1*4 (however, this is not an inclusive or exclusive classification).

Figure 1 Various ecosystems and keywords to be read
Source: Compiled by SOMPO Institute for the Future

This ecosystem typology is described below with a few additional details.

(1) Companies that grow together

It began to be used in the 1990s. The main players, upstream companies (suppliers of raw materials, parts, etc.), and customers form an ecosystem to promote overall business efficiency and compete with other main players and ecosystems. The strength of resource attraction*5 with upstream companies enhances competitiveness.

(2) Companies aiming for innovation

It began to be used in the 2000s. An ecosystem in which participants as a whole mutually utilize management resources, share roles, collaborate, and promote efficiency by utilizing external resources and collaborating in each phase of exploration, development, and monetization, as in the case of open innovation initiatives in research. The structure of a mature intellectual or industrial cluster is sometimes described as an ecosystem》.

(3) A place to create entrepreneurship and startups

The term "ecosystem" began to be used in the startup environment in the early 1990s, and the term "ecosystem" became widespread. Investors, incubators, and accelerators that support entrepreneurship are the constituent members of an ecosystem. The more successful a startup is, the more supporters it has, and the more the ecosystem grows. Furthermore, entrepreneurs will turn into investors, and so on, creating an ecosystem with circulation and growth. Location, such as Silicon Valley, is also an important factor.

(4) Economic sphere built by platformers

From the 2010s Ecosystems that involve platformers, such as GAFA*6. Digital is not essential, but in many cases, digitization and the collection and use of service recipients' information are the source of profits. The links among the members are loose, with the platformer, users (service recipients), and operators (suppliers of goods and services) as the constituent members.

(5) Companies that highlight their products and services

This is a relatively new type of ecosystem. The difference from (1) is that it is not a supply chain ecosystem, but an ecosystem in the sales process. The ecosystem consists of a product/service provider and other businesses that provide complementary materials*7 (content, usage, etc.) that make the product/service stand out.

Although organized by frequently used examples, it seems that the term "ecosystem" has already gone beyond these types of examples and is now being used by itself. However, it is important to understand that there is such a difference in the concept of business-related ecosystems. In addition, the term "ecosystem" is often used to describe an environment that is not structured for autonomous and continuous collaborative evolution, and is now also used metaphorically in social activities other than business.

（What is common to types (1) through (5) is that within each ecosystem, cooperative and competitive relationships are fostered among the participants, while the community as a whole aims for co-progressive development. In addition, competition, selection, interdependence, etc. are generated among similar ecosystems, creating a situation in which ecosystems are formed from a larger perspective. The scope of an ecosystem is not unitary.

In nature, there are forests, mountains, plateaus, and sand dunes, each of which has its own ecosystem, regional ecosystems that encompass multiple ecosystems, and ecosystems at the national and global levels.

Data ecosystem in the healthcare sector

So how should we conceptually view the data ecosystem in the healthcare sector in Japan?

In the "data-driven society" that we are about to see in the near future, all available data will be used as intermediaries to add and accumulate interpretations of data through collection and analysis, to make judgments and predictions about individual data, to elucidate the causes of events and to control them, and to discover new things that have gone unnoticed by humankind or that have been difficult to deal with, This gives new discoveries and value to matters that were previously unnoticed or difficult to deal with. The accumulation of such data leads to innovation that realizes a paradigm shift, and we would like to define a "data ecosystem" as an environment in which the collection and utilization of such data expands autonomously and sustainably.

In the healthcare field, data acquired from various data platforms, mainly in the areas of medicine, health, and nursing care, will be organically combined to form a data ecosystem that creates new value. The importance of building various platforms for data collection and utilization has been recognized.

On the other hand, it is not necessarily true to say that the use of a platform is an ecosystem. Although platforms and ecosystems are sometimes described as similar concepts, a situation that can be described as an ecosystem can be created by creating an environment where co-evolution can be achieved with suppliers and recipients of services, products, etc. provided by using platforms. In this sense, it is easier to understand if we view it as one of the important elements of ecosystem formation.

GAFA, a giant U.S. company (platformer), is building a platform in the healthcare field on a global level, and is also involved in services such as complementary devices and computer analysis within the platform itself. All information is being digitized and accumulated, and this digitization contributes to changing the cost structure and creating a situation where economies of scale can continue to work, while the convenience, efficiency, and low cost of using the platform for the companies and users who use it create a collaborative economy. The activities of platforms such as GAFA are exactly the type of (4) and (5) mentioned above. How to utilize these platforms in the creation of a Japanese healthcare ecosystem as a whole should be seen as a promising way to expand and improve the quality of the ecosystem as a whole.

When considering the data ecosystem at the scale of Japan's overall healthcare, there is a fluidity in the choice of platforms for utilizing the diverse data that is the source of the system. There is competition, selection, and interdependence among complementary platforms to remain in the ecosystem, and the ecosystem will grow with platform innovation. The dynamic movement in the formation and growth of platforms, including those already being formed domestically, is expected to continue, and progress in architecture (institutional design, legal reform, etc.) at the national and international level that links these useful platforms will support the construction of the overall data ecosystem. The development of architecture (institutional design, legal reform, etc.) at the national and international levels that connects these useful platforms will undoubtedly support the construction of an overall data ecosystem.

Solutions in the healthcare sector and the role of industry

As such a data ecosystem is formed, the target goals (solutions) for the next generation of medical and healthcare fields are changing. In other words, we are seeing a shift from conventional medical and healthcare treatment and health solutions to goals based on the ideal direction of society, such as "support for healthy longevity and independence in daily life. In other words, I believe that this also coincides with the objective of digital transformation in the healthcare domain. The source of such activities is digitized data, and the importance of each characteristic of the various types of data is expected to increase in the future.

When we consider what role the pharmaceutical industry is expected to play in creating "solutions" to advance this ecosystem, it is clear that it will not be limited to traditional drug discovery. Of course, the breakthrough new drugs that the pharmaceutical industry has been responsible for creating will never become less important, but when we think about health and disease management, preventive and preemptive medicine, disease treatment, rehabilitation, and quality of life in all these situations, the solutions are not necessarily drugs. They are increasingly being positioned as complementary materials such as apps and devices used for so-called digital health and disease management, and a major shift from "things" to "things (services)" has already begun to emerge.

Various data will be acquired in data-driven healthcare, and diverse outcomes and values are expected to be created in data-driven research that will progress from health management to disease management and disease treatment (prevention and preemptive medicine). Research to reach innovative new drugs requires a deep research phase that involves elucidating the cause and effect of diseases, but in the process of reaching this stage, a great deal of knowledge is accumulated, including factors that influence diseases and data that indicate disease-relatedness. Such information and discoveries are also expected to be fed back as new value that can contribute to data-driven medicine and healthcare. In the data ecosystem, the pharmaceutical industry will need to consider changing its strategy to seek a wider variety of outcomes, including digital health and digital therapeutics.

Healthcare data ecosystem from the viewpoint of data flow

The goal is to gather various platforms (or data ecosystems) and target mechanisms to utilize a wide variety of data and achieve significant results in terms of health, economy, society, and public satisfaction.

The main actor in the data cycle in healthcare (including medical care) is the data itself, which is digitized and can be analyzed and utilized in a wide range of ways. The key elements of this data are summarized in Figure 2. (1) Data diversity and connectivity, (2) Data continuity, (3) Ensuring data quality (quality of data according to purpose, standardization, structuring, cleansing, understanding of time-series outcomes, etc.), (4) Data accessibility (an environment that is accessible to both users and providers is necessary. It also includes addressing data security, ethics, etc.), and in addition to that, (5) smooth implementation of the return of analysis results and outcomes to the data providers (value creation and social return). We believe that the above five elements must be satisfied in order for a data circulation mechanism to be established, and that the formation of a data ecosystem can be ensured through the rotation of data as a cycle.

Figure 2 "Elements of data" to be considered in the data circulation (ecosystem) of Healthcare (including medical care)

Although many different stakeholders (players) exist for data distribution and utilization, let us consider a simple model to shorten the concept. Figure 3 looks at the relationships within the data utilization ecosystem among data providers (who provide data and use the data and results), data managers (who collect data and make primary use of the data), and data users (who make secondary use of the data and widely create results).

Figure 3 Ecosystem of data utilization for medical health

The "data providers" are generally patients and consumers. In other words, the entire population has the potential to be a data provider. The "data manager" is the entity that collects these data and attempts to make primary use of them. In many cases, it is a medical institution, a public agency such as the government or an insurer, or in the case of Personal Health Record (PHR) collection, a corporation or a private business. The collected health care information will then be distributed to "data users" such as public institutions, academia, and private health-related companies, where multiple analyses will be conducted and new value will be created from the consolidated data. The results are returned to data providers and society at large. We believe that the source connecting all players is "quality data," the "establishment of data accessibility (environment in which data can be used)," and the flow of "feedback of new value (deliverables)" created by the data.

How exactly to establish this flow is the point of contention in the construction of a data ecosystem in the healthcare field. We will not go into the details here, but from a macro perspective, it is clear that the key to achieving a "data ecosystem" that supports next-generation healthcare lies in the utilization of digital data in particular and the return of the results obtained to society. The approach of how to develop an architecture that facilitates the overall management and flow of data is important, but I believe that this must be left to the government and public administration in many areas. This approach is precisely the one that will lead to activities aimed at realizing Digital Transformation in Healthcare (Figure 4).

Figure 4 Data-driven medical health ecosystem

Discussion Points on Building a Data Ecosystem in the Healthcare Sector in Japan

In the "Future Investment Strategy 2018," the entire country is discussing Society 5.0 and the transformation to a data-driven society, and the healthcare sector has been taken up as an important area, with KPIs, issues, and measures being compiled. However, the discussion did not provide a concrete roadmap from a macro perspective, such as what kind of data ecosystem will be built, and the approach is not necessarily clear.

I would like to comment on four issues in particular from the perspective of data collection and utilization in this field.

(1) Build a platform that can link diverse data as a PHR

PeOPLe*8 was discussed, and I think it is important to build a platform that will be the key to data accumulation from the perspective of PHRs. The growing importance of PHRs in the future is mentioned in the study group report*9. I will avoid describing PHRs in detail here, but as we are seeing the progression of a major paradigm shift toward Precision Healthcare/Medicine, platforms capable of analyzing lifecourse health data are expected to be available. It is necessary to think of genome data and medical data as part of PHRs, and based on this, it is expected that "data ecosystems that enable data distribution platforms and PHRs to be utilized based on the individual" will be constructed.

(2) Build a platform for collecting medical information that prioritizes field use (field-first)

On the other hand, when considering data utilization in the healthcare field at this point, the importance of medical information such as individual disease history and medical record information is undeniable. The construction of a utilization-first system in the medical field is the second point of contention. I do not think there is any disagreement that the clarification of etiology and disease development process centered on medical information will be the key to the overall paradigm shift. The discussion on the future implementation of the Next Generation Medical Infrastructure Act also focuses on the accumulation and utilization of highly accurate hospital information, but unless the medical field and patients themselves are able to utilize this information and the incentives for data-driven medicine are clear, it will be difficult to accumulate highly accurate data in the first place. For many years, discussions on standardization and structuring of medical information and other efforts to promote its use in the field have been underway. For example, AI-assisted medical record systems, LHS*10 medical care improvement, and other systems are expected to be built that will be effective and show the benefits to the field.

(3) Implement architectural practices that promote a data-driven society and Society 5.0

The next step is to promote a national architecture that is effective in advancing innovation. In the approach to turning the data ecosystem around, it has long been pointed out that while innovative progress in technology and systems is being seen, it is important to harmonize innovation and architecture (development and design of legal systems and social systems), and in addition, a business mindset is an indispensable element. We believe that even public systems need to be designed in consideration of monetization, including by the private sector. It also goes without saying that discussions must be based on the premise of a major change in social systems, such as the realization of a paradigm shift. Especially in the utilization of data in this area, the harmonization of personal information protection and data utilization must be clarified. In addition, the architecture must reflect the social transformation (change to a super-smart society), in which the boundary between medicine, healthcare, and social life is disappearing.

(4) Building and accepting a wide range of platforms to improve and expand data

In addition, the construction of platform infrastructure has become a bottleneck in promoting data utilization in medical implementations (e.g., the spread of electronic medical records and the construction of Electronic Health Record (EHR) systems*11), and data collection and utilization leading to a data ecosystem have not yet become apparent. The data collection and utilization leading to a data ecosystem has not yet been manifested. On the other hand, there is an awareness of the problem of how to deal with the rise of platformers represented by GAFA. However, it goes without saying that the utilization of data related to life-course healthcare requires the construction of diverse platforms and data linkage mechanisms. A global data linkage perspective is also necessary, and the question is how to utilize existing services, including those provided by overseas platforms, as well as to build and link various unique Japanese platforms. Although an up-front investment approach is inevitable when building a new platform, the creation of a data-driven future healthcare system is an important theme for the future society, and a prompt national effort is needed, taking into account the expected effects of future value creation and global leadership. The creation of a data-driven future healthcare system is a key theme for the future society.

It is necessary to discuss what kind of data ecosystem will be established in the healthcare field in Japan, including the specific architecture that will lead to a future society. In this report, I have organized the ecosystem in terms of business concepts and considered the concept of a healthcare data ecosystem from the perspective of data distribution. I have also included comments on four macroeconomic issues that the author has focused on. I would like to continue my policy research on the ideal direction and role of the pharmaceutical industry in this context, while deepening my examination of these issues in concrete terms.

( Masami Morita, Senior Researcher, Pharmaceutical and Industrial Policy Research Institute)

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