Digital health policy leads, Data governance leads, data policy experts, and data and digital health managers across the health sector (pharmaceutical companies, healthcare providers, non-government organisations, community health, hospital networks, biotech, health tech startups)
What it’s about:
Our digital health ecosystem model maps the stakeholders and components that are needed for a functioning digital health ecosystem that generates a range of benefits for society, local economies and the environment.
Why it’s important:
Well crafted digital health policies across nations, regions and markets ensure multiple stakeholders can participate and co-create value in a people-centred healthcare approach. Understanding and mapping the digital health ecosystem can help analyse regulations and standards, identify gaps and opportunities, and create partnerships.
At Platformable, and in my previous work, we have been involved in defining and modeling digital health ecosystems in a variety of ways. This includes:
We mapped a digital health ecosystem model for the WHO's Data Governance Summit in 2021
We have built a global health policy maturity dashboard with some digital health ecosystem elements included (such as policies and strategies, key stakeholders)
I have presented at conferences globally on our model including in Brazil, UK, US and across Europe and Baltic regions.
An ecosystem approach refers to a holistic and interconnected framework for mapping, sharing, and utilising data across various stakeholders, systems, and processes. It emphasises the interdependence of data sources, technologies, platforms and users; creating a dynamic environment where data can flow seamlessly to generate value. This approach is increasingly important in today’s data-enabled world, where organisations and individuals rely on data to innovate, make decisions, and solve complex problems.
But to take an ecosystem approach you first need to understand and map the ecosystem in which you seek to play a participation role. There are ecosystem mapping approaches that start from an empty page and encourage you to identify all of the stakeholders. We have found this is can be a cumbersome approach if there is little time, and can sometimes leave out some stakeholders. We prefer to start with an ecosystem model template and encourage you to identify all of the relevant players in your local ecosystem (see the section below on how to build your ecosystem map using the appropriate lens to identify your stakeholders). We also step beyond stakeholders and map other components including the digital public infrastructure that is available and guides or mandates particular aspects of your digital health ecosystem. With these mapped, you can then look at the relationships between various actors and components, as discussed below in using your ecosystem maps.
Digital health ecosystem (Platformable's definition)
A digital health ecosystem is a network of stakeholders (including multilateral organisations, governments and regulators, standards bodies, industry associations, healthcare providers, pharmaceutical companies, public health and health promotion bodies, healthtech, data and digital tools and service providers, researchers, nonprofits, community organisations, patient representative groups, and individuals) able to co-create, collaborate, complement, coordinate and/or compete with each other equitably by using digital public and shared infrastructure, and common components and interfaces (including APIs, open standards, open data models, user interfaces, and open source tools).
Digital health ecosystem: high level view
At a high level, the digital health ecosystem is based around a patient-centred healthcare approach. Stemming out from this core principle, a range of stakeholder groups all contribute to creating a functioning, trustworthy digital health ecosystem.
Stakeholders in any of these groups can decide to play a leadership or participatory role in a digital ecosystem. For example, regardless of where an organisation is situated in these three groupings, they can be an orchestrator (encouraging ecosystem maturity for all stakeholders), a facilitator (working with their own members and partners to encourage full participation in an ecosystem), or a participant (focusing on one's own organisational role in actively participating in an existing or emerging open digital ecosystem).
Context-setters tend to be governments and regulators that establish regulatory and legislative requirements that all ecosystem participants must follow. But funders can sometimes influence the ecosystem context or encourage prioritisation of certain activities. In a digital health ecosystem, healthcare providers, medical devices (even wearables), government departments, health tech software, and others may be collecting health data that is then provided to others (becoming API or data providers) either as primary use data (to assist in managing an episode of care) or as secondary data (often aggregated) to solve a particular question.
API and data consumers are those that then use this data. This can b healthcare providers (where data is shared for healthcare management of a patient) or for those secondary use of data purposes to government (for planning and resource allocation), to researchers, or into digital products and services providers and analytics consultants who consume the data to create new digital health products and services.
Sometimes consumers are using the data themselves to make decisions, and in other cases, the consumers are creating tools, services, reports, and so on that end users then access to receive a benefit from the availability of data and digital service flows. For example, a healthcare provider could enter data into an electronic healthcare record (as a data and API provider), which is then read by a medical device (data consumer) to adjust settings or alert the patient (end user) when something needs to happen for their chronic disease management.
These stakeholders and the relationships and data flows between them are supported through a range of ecosystem components, including digital public infrastructure aimed at supporting stakeholders across the digital health ecosystem to collaborate, co-create, coordinate and, at times, compete.
When working effectively, a digital health ecosystem leads to 6 key benefits:
Benefit
Better health outcomes
Description
Increased coordination to support high-quality care throughout the patient journey
Example
Data is used to seamlessly provide care across a range of healthcare providers where needed, reduces risks of adverse reactions and contraindications from prescribed therapies, and enables personalised medicine advancements.
Benefit
Reduced Inequality
Description
Using data to better target services and disaggregate data to understand the impacts on vulnerable populations
Example
Data allows insight into differential health outcomes by gender and socioeconomic status.
Benefit
Optimised health system
Description
Achieving efficiencies in care delivery and resource allocation, decreasing the cost of care while maintaining high quality and satisfaction
Example
Data is used to reduce inefficiencies and ensure care is provided through early diagnosis when health care delivery costs are cheaper. Data can also be used to set prevention policies to reduce future strain on healthcare systems.
Benefit
Greater patient-public participation
Description
Understanding of connections and collaborations, and a sense of engagement and involvement in health decision-making by communities and all stakeholders
Example
Access to data enables deeper conversations between patients and health providers, and allows the public to participate in discussions on health research, building trust and supporting local industry growth.
Benefit
Expanded innovation
Description
New industry opportunities and deeper insights into existing systems
Example
Reuse of population health data and research data accelerates innovation, identifying high-potential opportunities for healthcare product development.
Benefit
Professional recognition & Private profits
Description
Support for researchers and other stakeholders that collect, use, and share data
Example
Academics can build careers through data reuse and recognition. For-profit businesses can leverage health data to innovate, remain profitable, and drive economic growth.
Digital health ecosystem: detailed view
Our model identifies all of the stakeholders and components that operate in a digital health ecosystem, but not all may be relevant or readily identifiable in each map you create. For example, in our model, between API and data providers and API and data consumers, we have included Health Data Access Bodies. In Europe, under the European Health Data Space legislation, this new type of body is emerging as part of regulatory data governance to review requests for the use of data. They facilitate between the provider and consumer and may even provide the secure data environment or platform where the data can be accessed, and facilitate the payments (direct to them for processing the decision an d perhaps directly to the provider for use of the data). Even in Europe, as our Global Digital Health Policy Maturity Dashboard shows, not all member states have set up this body as yet. In other countries, this body might not exist. But the roles the body undertakes might be played by other stakeholder entities.
Drawing on some of our previous research into how AI is used across the digital health ecosystem, we have also highlighted on our ecosystem model where AI may be intersecting with ecosystem components and stakeholders.
Digital Health ecosystem stakeholders
Here is our current working definition of each of the stakeholders shown in the model:
Stakeholder
Standards bodies
Type
Context-setters
Description
Standards organisations (and market-driven initiatives) that define specific health data standards and data models or that seek to establish norms for industry interoperability and data sharing.
Stakeholder
Regulators
Type
Context-setters
Description
Defined bodies responsible for establishing regulatory compliance processes and for using and assessing data.
Stakeholder
Government departments
Type
Context-setters API & Data providers API & Data consumers End users
Description
Policy making government bodies that draft and implement legislation, policies, guidelines, and strategies that set the ecosystem context. Government departments also generate and share data, consume data, and are end users of data products and services.
Stakeholder
Funders, investors and incubators
Type
Context-setters Capacity builders
Description
Bodies that provide funding and investment can be both capacity builders and context-setters. As context-setters, they are stimulating market entry and also setting what priorities should be focused on by ecosystem actors. As capacity builders, they are providing financial resources to enable ecosystem growth.
Stakeholder
Healthcare industry
Type
API & Data providers End users
Description
Stakeholders that generate and at times make data and services available digitally and in machine-readable formats to others. Also often end users of data digital tools and services to aid in their role as healthcare providers.
Stakeholder
Healthtech
Type
API & Data providers API & Data consumers End users
Description
Stakeholders that at times generate data through their digital products, services, medical devices and so on. They then can share this data with other tools or stakeholders. They are also consumers of data and APIs to create apps and other digital products and services. They can also be end users, making use of data from their own and others collection to develop new markets and services.
Stakeholder
Multilateral organisations, industry associations, patient representatives, civil society & health equity advocates
Type
Capacity builders
Description
Capacity-building organisations create tools and resources to support ecosystem activities. Industry associations, patient representative organisations, and other bodies also participate in shaping the ecosystem and supporting their members and constituents to build capacity and to be able to participate actively.
Stakeholder
Data, API and AI tools, user agent & infrastructure providers and consultants
Type
Capacity builders API & Data consumers
Description
Stakeholders that assist other actors to participate in open digital ecosystems by providing datasets and/or digital tools to meet regulatory requirements, by providing underlying infrastructure to enable product development and ecosystem participation. These tools providers may also consume data and APIs in order to provide features in their own products and services. Includes open source project maintainers and managers of digital public infrastructure.
Stakeholder
Health data access bodies
Type
Context-setters
Description
These new types of stakeholder bodies are similar to a regulator, where they assess requests for access to health data according to the local data governance legislation. They often act as the platform to connect potential users with providers once assessment and permission has been granted and may offer secure data environment technologies where data consumers can analyse data made available by data providers. They may charge for processing data requests and facilitate payments to data providers.
Stakeholder
API & Data consumers
Type
API & Data consumers
Description
Stakeholders that integrate data and APIs into their products and services. These can include B2B tools providers, device manufacturers and health apps, or some end user stakeholders who also consume data and APIs directly, such as researchers and government departments.
Stakeholder
Researchers and academia
Type
API & Data providers API & Data consumers End users
Description
Stakeholders that generate research in the health sector. They may also make their data available to others. They may consume data and APIs to conduct their research or analysis or may be end users of other data analysis and outputs.
Stakeholder
Media
Type
API & Data consumers End users
Description
Stakeholders that may consume data and provide in more accessible formats for a wider audience of end users, or may be end users themselves of data.
Stakeholder
Non-government organisations
Type
API & Data providers API & Data consumers End users
Description
May generate and collect data if they provide community-based health or other services, they may consume data directly from other sources to provide better products and services to their target audiences, or may be end users of data when making decisions or undertaking advocacy and other activities.
Stakeholder
Community / People
Type
End users
Description
We often think of people in terms of patients, but in reality all of us in our communities are end users of health data and digital health outputs. This can include as patients but also as caregivers, health sector workforce members, and advocates.
Digital Health ecosystem components
Components tend to include:
Component
Regulations & Standards
Description
The regulations and standards themselves and any government policies and strategies that define how digital health is being organised.
Component
Standards & Data Governance
Description
Standards and data governance, including internal standards and style guides and best practices and tools, including in data, AI and API governance frameworks such as consent processes that ensure that data subjects maintain control over how their data is used throughout the ecosystem, and trust frameworks that can include tooling to enable responsible data sharing at scale.
Component
Developer Experience
Description
Developer Experience refers to the resources made available to API and data consumers to assist them to onboard and build successfully with data or APIs.
Component
Security & Privacy
Description
Security and Privacy refers to the level of security and privacy robustness of data and APIs, and ease in enabling data protection regulatory compliance and use of security best practices. These impact on the overall trustworthiness of an open digital health ecosystem.
Component
Digital Readiness
Description
Digital readiness refers to the level of skills and expertise amongst potential API and data consumers, and the digital readiness of end consumers to make use of digital health products and services.
Component
Industry Velocity
Description
Industry Velocity refers to the overall subsector or industry's willingness and capabilities to move to data- and API-enabled digital approaches.
Component
Data, AI, API, and Digital Tools
Description
The data, AI, API, and digital tools including user agents and infrastructure that support open digital health ecosystem growth. This can include open source tooling and other digital public goods that are shared or can be used by any ecosystem stakeholder, as well as proprietary offerings that must be purchased or are only available to specific actors. This can also include the hardware level and the cloud infrastructure that digital is built on.
How to build your own digital health ecosystem map
Using this model, you can map a digital health ecosystem at any of the following levels:
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Geographic level: This can be done at the community, municipal, state/province, national, regional or global levels.
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Burden of disease/preventative area of focus: You could create an ecosystem map to define all stakeholders and relevant necessary to deal with a specific burden of disease or health promotion/prevention area.
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Therapeutic intervention: You could map all ecosystem stakeholders and components relevant to a particular intervention, for example, a pharmaceutical drug, therapeutic modality like aged care, medical device, health app, or anti-tobacco or gun control approaches.
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Hybrid ecosystem models: Often you will want to combine a geographic level with a burden of disease and/or therapeutic intervention area. For example, you might look at all diagnostic services (therapeutic) for cancer (burden of disease) at the province level. This is also a much more manageable level of ecosystem analysis than a whole country. At a whole country, perhaps you only want to name organisations that are taking key leadership roles, and then group secondary and tertiary actors. Or start with the key leaders and over time keep working to build out your ecosystem model to a more comprehensive overview if you have longer term ambitions for how you want to participate in the digital health ecosystem.
We are releasing a health data governance series in September 2025, including some downloadable, interactive templates you can us to map your ecosystem and to dig deeper into each stakeholder and component.
We will be mapping the digital health ecosystems we participate in and measuring how an ecosystem analysis helps us grow. For example, we have resources in health data governance and digital health policy assessment. We will show how analysing the ecosystems around these two activities helps us build new market opportunities. We'd love to work with you if you want to test using the ecosystem model and analysis approach to do the same for your area of interest.
We will continue to build out our ecosystem support resources focused on digital health. Feel free to book a time with me in the Calendly below to discuss what you think and to dig further into digital health ecosystem mapping and analysis.
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based in Barcelona
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