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Healthcare Blockchain Consortia Initiatives

Healthcare Companies are Ramping Up Involvement in Blockchain / DLT Projects in 2019

Part 3: Three Primary Design Patterns

This is the third in a series of posts on lessons learned from the various healthcare blockchain consortia announced over the last year.



con·sor·tium | \ kən-ˈsȯr-sh(ē-)əm

plural consortia \ kən-ˈsȯr-sh(ē-)ə

1: an agreement, combination, or group (as of companies) formed to undertake an enterprise beyond the resources of any one member

The initial post introduced the history and detailed the trend of these enterprise consortia in healthcare. The second focused on the companies behind the consortia, and how these efforts enable utility solutions aimed at shared problems across the network of participants.  The whole series references the master list of 7 Major consortia announcements over the last year.

Table 1: Enterprise Consortia announced in 2018 and 2019.

Table 1: Enterprise Consortia announced in 2018 and 2019. Updated 10/10/19.

In this newsletter we will discuss the primary business patterns and use cases we see in these announcements. These include:

  • Data Synchronization- The use of a blockchain as an industry utility for accuracy and completeness of data files. The Synaptic Health Alliance’s provider directory data sharing initiative is an example of this design pattern.
  • Asset Exchanges- The use of a two-sided market for the exchange of digital assets that have value for buyers and sellers / curators. The Professional Credentials Exchange’s digital marketplace for exchanging verified credentials is an example of this design pattern.
  • Multi-Party Business Process Automation- The foundational use of a shared source of truth between transacting parties in a business process for the purpose of automation, operational intelligence, and model innovation. Consortia initiatives that focus on shared business processes (ex. Coalesce, MediLedger, RemediChain) are examples of this design pattern.

Meaningful Innovation

Meaningful work in the healthcare space is riddled with technical and non-technical challenges. Life in the space feels like a game of 3-D chess where new pieces are frequently added to the board.

Innovators are regularly challenged with answering a series of interconnected questions including:

  • Do you need a blockchain or Distributed Ledger to solve a specific business problem? Are you storing state transitions? Do you have multi-system / multi-stakeholder contributions? Do these contributors know / trust each other?
  • What business problems are you solving for? What business model characteristics are first-order problems? Are you aiming for an open, border-less, neutral, publicly verifiable system? Or are you solving for more local issues trust and transparency issues?
  • What are the source systems you need to interface with and what are the characteristics of these systems?
  • By using a blockchain or a digital asset, are you enabling a new business model that is significantly better than what exists today?
  • Is there the necessary network of customers excited to bring it to life?
  • Are these companies willing to get over the potential political challenges associated with joining a network with their competitors?
  • What is the value proposition for network participants?
  • Can it clear the procurement / legal process and each of the network parties? Will they all agree?
  • What regulatory challenges should be considered?

The answers to these questions are not always easy and the answers don’t remain constant. The answers help us understand how close we are to the “sweet spot” where there is a clear need to use a DLT; there is a valuable business model innovation that is enabled by the use of a shared ledger to track a digital asset; and there exists at least the minimally viable network of entities required for meaningful use of the solution.

Over the past three years, the team at Hashed Health has had a front row seat to the evolution of technical models, business models and network structures in healthcare. Our team has built on many protocols and analyzed many business models with many enterprise partners in an attempt to understand the pros and cons of a variety of projects.

This work at Hashed Health and the work of other non-Hashed consortia demonstrate three primary design patterns that have emerged as viable constructs for what we consider meaningful work in the near term. These three design patterns are 1) Data Synchronization; 2) Asset Exchanges; and 3) Multi-Party Business Process Automation.

Figure 1: Finding the "sweet spot" where 1) there is a need for the technology; 2) the use of the technology enables an innovative and valuable business model; and 3) there is a motivated network of companies who have or will enter a shared agreement.

Pattern 1: Data Synchronization

The simplest and often best use cases are those that focus on multi-party data synchronization efforts. This design pattern seeks to create a shared source of information to which any member of the consortium can submit data. In doing so, each member learns from the master data set. The ledger acts as an industry utility where each member can more effectively manage information by participating in a group versus acting on its own.

Generally, in these data synchronization efforts, the consortium members are fairly equal in their role. Often members pay their own way to participate in the utility. Fully replicated blockchain protocols (all data is shared on every node in the network) are acceptable because the data is meant to be shared fully across the network. Privacy and confidentiality of transactions are not a concern.

An example of a consortium using this design pattern is the Synaptic Health Alliance. The Synaptic Health Alliance is focusing on using the blockchain as a shared source of truth for provider directory data. Each member of the alliance (which includes Humana, Optum, Multiplan, Quest Diagnostics and others) contributes their directory data to the network and can learn about directory completeness by comparing their data to that of the rest of the network. Their goal is to prove the system in the provider directory area before looking at the sharing of additional types of data.

This type of use case lends itself to fully-replicated blockchains where all data is shared on every node on the network (ex. Fabric, Quorum, etc). Transaction confidentiality is not a concern, so there is no real need for private channels and heavy controls within the environment. It’s these privacy and confidentiality “bolt-ons” that cause many fully replicated blockchains to struggle in today’s world.

Design Pattern: Data Synchronization

Protocol: Blockchain

Governance complexity: High

Business model complexity: Simple

Challenges: Incentive structures; scalable business model; governance

First-order problems: Data sharing amongst participants

Examples: Synaptic Health Alliance (directory)

Pattern 2: Digital Asset Exchange / Digital Asset Marketplaces
© Cgm22 | Stock Free Images

This design pattern employs an asset exchange model derived from the Bitcoin. In this model a piece of data is treated as a digital asset and that asset is be made available on an exchange for trading. The ledger tracks asset ownership, exchange, utilization and forms a basis for asset reputation. The governor and operator of the exchange need not take ownership of the assets themselves, but may have some control over the infrastructure through which assets are traded. The consortium is primarily interested in the value created through the buying and selling process. Buyers of the information finance the platform. Curators of data assets are paid for their contributions, as are partners who help facilitate the use of the solution.

Such two-sided marketplaces have a challenging go-to-market, since they need critical mass of assets in order to attract buyers and sellers. This model expands on the utility concept with an exciting business model that can be applied to a range of problems in healthcare and life sciences.

Hashed Health is a fan of asset exchanges and has several asset exchange projects underway (Professional Credentials Exchange and Bramble are two). While challenging in many regards, we believe this model has a strong incentive structure for both sides of these marketplace. We believe these blockchain / DLT-based “market networks” could have a dramatic effect on certain data management use cases over the next ten years.

Perhaps the best known asset exchange in healthcare is the Professional Credentials Exchange (“ProCredEx” or “PCX”). The digital assets offered in PCX represent verified practitioner credentials, which health systems are required to assemble in order for a physician to treat a patient. In today’s world this complex work of verifying credentials is being completed offline by a health system or some other curator in a many-to-many transaction pattern. The data, once collected, sits idle as a cost center. Enterprises currently do not trade this information primarily because of trust issues. In the PCX model, the verification of a physician’s identity can be offered to another organization who needs to do that same work. The buyer can acquire this information from the ecosystem much faster and cheaper than attempting to do that work alone.

PCX is a clear example of a use case where there is a need for the technology (trust in the verified digital artifact), there is a valuable new business model enabled by the technology (an asset exchange), and there is a network of enterprises (Spectrum Health, Wellcare, Anthem NGS, MEDNAX, and others) who have signed up to use and support the platform.

Design Pattern: Asset Exchange

Protocol: Blockchain or DLT

Governance complexity: Low

Business model: Two-sided marketplace

Challenges: Go to market / critical mass of assets

First-order problems: data access; transactional privacy; data asset ownership

Examples: Professional Credentials Exchange

Pattern 3: Multi-party Process Automation

Traditional business process automation stops at the edge of an organization. Healthcare is inherently a team sport and the future of healthcare business process automation rests in enabling networks to organize data from many sources and improve shared processes. That means improved care coordination, contract adjudication, clinical trials processes, consent management, benefits management, incentivization structures, etc.

This third design pattern we see emerging is potentially simpler from a non-technical perspective since it does not necessarily require a large consortium to stand up and demonstrate value.

These use cases are often solving for “local trust” between two or more counterparties instead of more “global,” network-minded trust as you would find in a true blockchain (ex. Bitcoin) which is optimized to be decentralized, borderless, publicly verifiable, censorship resistant and neutral. In my experience, fully replicated ledgers are not currently built with these healthcare B2B cases in mind and attempts to use a fully replicated ledger in 2019 for this design pattern will likely lead to frustration.

It is these cases where we employ DLT solutions and other technical structures that are starting to look a lot like cloud. These are the systems that allow you to optimize for the local trust issues inherent to these use cases.

Protocol: DLT

Governance complexity: Low

Business model: Local / Counterparty

Challenges: Philosophical (ex. not a true blockchain)

First-order problems: Confidentiality, Privacy, Throughput, Transactional Templates

Examples: Signal Stream, HUN

In future newsletters in this series, we will explore thoughts on selected use cases, protocols, and dive in to other lessons learned through these early consortia projects.

In future newsletters in this series, we will explore protocols and lessons learned.

(I’d like to express my thanks to Stephen Allen, Hashed Health computer science team member / intern all-star for his help researching this series.)


Hashed Health


Signal Stream


John Bass

Anthony Begando

Les Wilkinson

Giles Ward






Hashed Health

901 Woodland Street, Nashville, TN
United States

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