Platform Shift: From EHRs to UDHPs (Unified Digital Health Platforms) – – Section 2

Apr 2, 2025

By VINCE KURAITIS, GIRISH MURALIDHARAN & JODY RANCK

This entry is Section 2 of part 3 of 3 in the series Platforming Healthcare — The Long View. This essay is the next in the series entitled “Platforming Healthcare — the Long View”. The series presents a 30-Year Framework for Platforming Healthcare. An updated v2.0 of a graphic depicting this 30-Year Framework is shown above.

Today’s post is section 2 and will continue to describe and discuss a potential successor to the EHR era — Unified Digital Health Platforms (UDHPs). Here’s an overview:

Mayo Clinic Platform
Business and Strategic Implications of UDHPs
APPENDIX: Additional Readings on UDHPs

Mayo Clinic Platform: Healthcare platforms and AI

The Mayo Clinic Platform (MCP)was launched several years ago with the goal of building the future Mayo Clinic business model that could move beyond the bricks-and-mortar approach to traditional healthcare and open up new avenues for products and services. The adoption of a platform business model was considered essential to serving patients beyond the traditional Mayo Clinic geography as well as a way to incentivize innovation in AI and decentralized care in the home.

A large longitudinal database with both structured and unstructured data provides a foundation for the MCP, particularly in respect to catalyzing innovation in clinical applications of AI. The database called Mayo Clinic Platform Discover has over 7.3 million de-identified patient records that can be used for training AI models as well as in research and discovery for early-stage startups in particular who wish to join the MCP ecosystem. The dataset is referred to as “Data behind glass” for the privacy and security standards that are needed to create the bedrock for a collaborative ecosystem.

Source: Mayo Clinic Platform Playbook

MCP is a three-sided market that has solution developers, data providers, and clinicians composing the three sides. MCP acts as the orchestrator of the ecosystem and additional partners such as Mercy have joined as data contributors in the MCP component called Mayo Clinic Platform Connect. These are the primary components of the platform.

The Mayo Clinic Platform Playbook identifies six key success factors:

A privacy-protecting, secure collaborative environment with de-identified data from global sources. Longitudinal databases of patient records are vital to clinical research and the development of new clinical decision-support tools, therapeutics, and digital health solutions. Privacy and security need to be maintained to protect the trust of Mayo Clinic’s patients.
Breadth and depth of patient data must be sufficient to generate insights for both rare and common diseases.
Seamless capabilities to both ingest diverse data sources (e.g. -omic (genome, metabolome, etc.), EHR, wearables, social determinants of health (SDoH)) and to deliver actionable insights at the point of care.
Cutting-edge data science analytic tools, robust computing power, and uniform data standards.
Strong governance to assume security, scientific validity, interoperability and validation of technologies fit for purpose.
Pathways for commercialization of effective, validated solutions.

MCP vets startups and more mature technology vendors through a process that can begin with providing access to the longitudinal database for developing and training models (early-stage startups) to scaling solutions across MCP and affiliated hospitals with Mayo Clinic. The robust governance structure and integration with MCP makes scaling into other systems much more feasible.

AI governance is a core component of the MCP and why they were one of the original sponsors of the Coalition for Health AI (CHAI) to bring together leading industry players to create the standards for responsible AI across validation, explainability, and transparency. Ensuring that AI tools have been rigorously validated is necessary for clinician adoption of AI as well as maintaining the trust of patients. These standards act as a kind of “rules of the road” for technology solution providers on the MCP.

Platform Shift: From EHRs to UDHPs (Unified Digital Health Platforms)- Section 1

Mar 31, 2025

By VINCE KURAITIS, GIRISH MURALIDHARAN & JODY RANCK

This entry is part 3 of 3 in the series Platforming Healthcare — The Long View. This essay is the next in the series entitled “Platforming Healthcare — the Long View”. The series presents a 30-Year Framework for Platforming Healthcare. An updated v2.0 of a graphic depicting this 30-Year Framework is shown below.

Today’s post will describe and discuss a potential successor to the EHR era — Unified Digital Health Platforms (UDHPs). Here’s an overview:

Background and Environmental Trends
Gartner’s Key Role in Characterizing the UDHP Movement
UDHP Value Propositions
Examples of UDHPs
- ServiceNow

Later this week THCB will run the second section which will include analysis of the Mayo Clinic Platform.

Background and Environmental Trends

Healthcare is fragmented. Data is not standardized and has existed in silos. Patients and clinicians have disjointed experiences. Payment structures create conflicting incentives.

Electronic Health Records (EHRs) were once touted as the key solution for transforming healthcare to a modern, digitally-enabled industry. Yet, they continue to frustrate clinicians with poor UI/UX and largely fulfill a primary role as a system of record to document claims submissions.

Recent technological and business trends have begun transforming healthcare into a more unified and integrated experience:

HITECH (in the U.S.) drove the adoption of electronic health records across the industry
Standards-compliant data models and APIs across various solutions are allowing third-party integrations to add new functionality
Value-based care (VBC) and value-based payment (VBP) models incentivize improving quality rather than maximizing fee-for-service volumes
AI’s emergence and adoption in healthcare fuels the need for more – and better – data and data liquidity.
New competitors in healthcare (Big Tech, Big Retail, digital health ventures) compete based on improving patient experience, advancing VBC and VBP models, and integrated data and analytics
Accessible cloud computing infrastructure is enabling a plethora of **-as-a-Service business models

Healthcare organizations want integrated solutions, not more point solutions. See the previous blog post in this series — “Beyond Awareness: Understanding the Magnitude of Point Solution Fatigue in Healthcare”.

Gartner’s Key Role in Characterizing the UDHP Movement

The trends and forces listed above open the door and create the need for a new category of enterprise software – Unified Digital Health Platforms (UDHPs).

A December 2022 Gartner Market Guide report characterized the long-term potential:

The DHP shift will emerge as the most cost-effective and technically efficient way to scale new digital capabilities within and across health ecosystems and will, over time, replace the dominant era of the monolithic electronic health record (EHR).

While Gartner uses the term “Digital Health Platform (DHP), we use the term “Unified Digital Health Platform” because 1) it’s more descriptive of the architecture and its capabilities, and 2) it distinguishes UDHPs from the thousands of other digital health platforms that vary highly in function.

The DHP Reference Architecture is illustrated in a blog post by Better. Note that UDHPs are depicted as “sitting on top” of EHRs and other siloed sources of health data:

Gartner continues to update its market reports on UDHPs. An April 2024 update is entitled: “Innovation Insight: Digital Health Platforms Accelerate Transformation”. As of the date of publishing this blog post, Altera is offering a complimentary copy of Gartner’s 2024 report on UDHPs.

This blog post is intended to focus more on the business and strategy implications of UDHPs. We strongly recommend reading Gartner’s April 2024 report on UDHPs to gain a more technical perspective.