Why platform model in digital health, and why is Tiger Health Technology on the right track?

March 20, 2024
MIT Sloan Management Review recently released a special report titled "New Markets, New Opportunities: Identifying Where and How to Make Your Play," focusing on strategies for emerging technologies. One of the articles, "Health Care Platforms Need a Strategy Overhaul," directly relates to Tiger Health Technology’s approach. It clearly explains the concept behind Health BRIDGE - our software platform for lifecycle management of unstructured medical data to support cloud and AI adoption. From the beginning, we have embraced the platform strategy, and the research from MIT Sloan Management Review validates our approach. We have focused on a narrow and well-defined scope, such as digital pathology; we are developing the platform with the aim of using statistical data to enhance operations and business models; and we are establishing trust and legitimacy not only among costumers but also among key stakeholders in healthcare.

The latest analysis by Emergen Research reveals that the global digital health market was valued at USD 175.20 Billion in 2021. It is projected to register a Compound Annual Growth Rate (CAGR) of 27.2% during the forecast period, with the market size expected to reach USD 1,518.64 Billion by 2030 The increasing demand for remote patient monitoring solutions, the growing adoption of artificial intelligence and machine learning, and the increasing focus on patient-centric healthcare are expected to drive the growth of the digital health market in the coming years.1

According to the U.S. Food and Drug Administration, digital health platforms can help address some of the most important challenges in healthcare.2 The platform business model, described in the book “Organizing for Sustainability. A Guide to Developing New Business Models” written by Jan Jonker, Niels Faber is one of the three main business model archetypes. “The platform business model archetype aims to make better and more efficient use of what we have through asset or performance management enabled by datafication and digitalization. At its essence, this archetype is about better functional utilization…”3

Platform strategy seeks to fit a platform with its environment, but the characteristics of healthcare make such a fit challenging to achieve. Although countries differ significantly in how they fund, organize, and deliver healthcare, multiple factors are consistent across nations and make the context for digital health platforms distinct from other platform businesses, no matter where they are deployed.4

In a recent publication by MIT Sloan Management Review, a three-part approach for making such platforms grow and succeed was outlined. Deploying a platform strategy successfully in the complex healthcare sector requires an understanding of its unique conditions and demands. To avoid costly mistakes, organizations must shift their mainstream assumptions about platform strategy and make different decisions about three key domains – how to enter the market, how to scale the business, and how to govern the ecosystem – to align with a digital health perspective.5

Decision 1: How to enter the market

In healthcare, digital platforms typically extend rather than replace the established ecosystem, where existing actors remain important providers of complementary services. Digital health platforms must find ways to integrate with incumbent offerings when entering the market. Interviews with digital health platform leaders made clear that the intention is not primarily to disrupt and substitute, although substitutions might occur in specific areas; instead, the goal is, first and foremost, to complement a large set of existing offerings.

Decision 2: How to scale the business

Both direct and indirect network effects are limited for digital health platforms relative to many other types of platforms. Learning matters in all types of platform development. In digital healthcare, learning effects are the primary way to benefit from user adoption and increase user retention on the platform so managers must approach business scaling differently. They can use the insights gained in two important ways: to develop operational excellence and to enable business model development.

Decision 3: How to govern the ecosystem

In sharp contrast with the mainstream view, rather than central orchestration, there is distributed orchestration, leaving digital health platforms with the possibility to influence orchestration from a peripheral rather than central position. It’s a question of influence rather than orchestration. To build trust and legitimacy not only among customers but also among physicians, regulators, insurers, and associations as well, platforms need to be transparent and generous in sharing data and evidence about the appropriateness, effectiveness, and safety of their services.

Another important means of influencing the ecosystem is to proactively participate in regulation development. Successful digital health platforms monitor and explain the consequences of existing regulations, not only for their own operations but also for third-party providers and patients. That information serves as input to further regulatory development.

In conclusion, digital health platforms hold promising solutions to address key challenges in healthcare systems worldwide, particularly regarding costs, productivity, and accessibility. These platforms could also serve as valuable components of existing healthcare services and solutions. Health BRIDGE, the data lifecycle management platform developed by Tiger Health Technology, also holds these promises. It is being built with the vision to support cloud and AI adoption in healthcare – two major advancements that are poised to deliver significant value at scale.

What can we expect for digital pathology in 2024?

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