Exploring tokenomics for electronic health records

There are a number of projects trying to build a blockchain based electronic health record (EHR) right now. Here are some of the reasons:

• Multiple disparate parties with equally diverse incentives need access to the same data
• Having a single network with interoperable data is a dream
• The integrity of that data is of the utmost importance
• Control of patient data should be distributed to the edges, into the hands of patients, who the data really is about
• The open architecture associated with blockchains would be a welcome development in a world dominated by the walled gardens of Epic and Cerner

The Center for Biomedical Blockchain Research documents 28 companies tackling personal health records alone. Most, if not all of these platforms, are trying to enable some form of data monetization and selling data is the primary transaction that takes place on them.

Moreover, the majority of these 28 have had an initial coin offering (ICO), otherwise known as a token sale. The reality is that these tokens are primarily used as a fundraising mechanism and their functional purpose is treated as an afterthought, if thought of at all. Their tokens have suffered accordingly.

The reality today is that these tokens are primarily used as a fundraising mechanism and their functional purpose is treated as an afterthought, if thought of at all.

There are a wide array of token models, but particularly popular within the current generation of blockchain enabled EHRs is the “medium of exchange” token model, where a token is used as the native payment within an ecosystem. This suffers from the well documented “velocity” problem, which has significantly contributed to healthcare ICOs’ poor performance to date.

Token economics

This is unfortunate and a disservice to everyone. If designed right, tokens can be an extremely powerful tool. Token economics or tokenomics is a burgeoning field for the study of how to design tokens. The objective of token economics is to use economic incentives to achieve a desired objective. Restated another way, token economics tries to design a system to achieve a desired objective and make money for token holders.

For a blockchain based EHR you could have several objectives, but I think the principle objective should be to maximize the sharing of data. This is for two reasons: the first is that incumbent systems lack the business incentives to share data today, and the second is that the future of healthcare lies in AI, and data will be the fuel for that AI.

Moreover, getting token economics right in a blockchain based EHR could yield a number of further benefits:

• Driving network effects
• Effective and decentralized network governance
• Fundamentally new business models
• The leveraging of cryptoeconomic primitives like token curated registries
• Allowing regular people to gain from the increased value of the network that is created
• Encouraging more adoption as a result of an appreciating native token

How do we design a system that achieves this? Well, token economics isn’t an exact science yet, but we do have a few tools in our metaphorical token toolbox. There are a few token mechanisms we can introduce that could move us towards our goal of data sharing and accrue value to the token holders.

Token mechanisms for a blockchain based EHR

Our blockchain based EHR in this example will need its own native token and I’m going to label this new token the Blockchain Enabled EHR Token, or BEET.

Token burning

A simple token burn could be executed like this:

• A percentage of the value of all data sales denominated in BEET are sent to a burn address and forever removed for the supply
• The above percentage parameter could be agreed upon by on-chain protocol governance

The goal of burning tokens is to reduce the available supply, which, with all else held equal, should cause an appreciation in price.

In theory, this should encourage more data sales in aggregate, as more sales results in a further reduced supply and further appreciation in price.

Staking

Staking is the process of “setting aside” tokens for a period of time.

• A percentage of the value of all data sales denominated in BEET could go towards a pool used to pay node hosters/miners of this network
• If a participant agrees to stake a certain amount of tokens, say, $25,000, then the fee they pay is reduced
• Different amounts staked and duration of staking could merit different levels of fee reduction

By staking your tokens you are reducing the available supply, if only temporarily, as well as contributing to an overall lower velocity for the token. Both of these should add upwards pressure to the token and hopefully cause appreciation in price.

Governance

Governance refers to a broad set of processes enshrined by code, formal or informal processes, and norms that govern how a blockchain changes over time. Fred Ehrsam lays out a great case for why governance is important here.

I think governance in a blockchain enabled EHR is interesting because it distributes control between the many different parties that use an EHR. In particular, it gives a way for patients to exercise real influence over decisions they wouldn’t otherwise have.

An example where governance could be important is in the deciding underlying data standards:

• There will need to be a shared data standard all participants agree upon. Occasionally this will need changes as the underlying standard is upgraded. Those changes could be proposed and ratified using an on-chain governance mechanism.
• Any participant could propose a data standard change with and conduct a simple yes/no poll.
• Network users, whether providers, pharma companies, universities, patients, patient advocacy groups, payers, etc could vote for yes/no with and the weight would be proportional to their tokens.
• The side with more tokens behind it would win and the proposed change is either adopted or rejected.
• There are many variants of this, a popular one including quadratic voting.

By governing the network this way you resolve disputes between parties, let anyone participate in that resolution, and create a shared data standard.

Parties will have preferences on which data standards are used. Perhaps your companies’ engineers are used to working with one particular standard and would have to spend time learning a new standard and updating current systems. Obviously, you would be willing to spend some money to prevent this from from happening.

Cryptoeconomic primitives

Cryptoeconomic primitives are the “well established, generic building blocks” of the crypto world. Jacob Horne has a stellar introduction you can read here Some of these like token curated registries (TCRs) and curated proof markets, need a native currency to work. MedCredits is using a TCR to curate a decentralized registry of physicians as an example.

Here are three potential applications of cryptoeconomic primitives that could use BEET:

• A TCR in this system could be used to curate a list of healthcare providers and their associated wallet addresses
• Curated proof markets could be used to price different data sets
• Having ownership of the data from a clinical trial on the same ledger as ownership of IP that results from that clinical trail poses some interesting possibilities. Patients could be given the opportunity to buy into that IP via bonded curves.

At the end of the day primitives are simply tools that can be combined and interchanged to achieve particular goals. There are an infinite number of potential applications and there will be more cryptoeconomic primitives to come. The trick is to find one or a combination that will help a network achieve a goal (i.e more flow of data) as well as create value for token holders.

Concluding thoughts

I want to be clear that I don’t know what the right model for success is. No one does. But, the above mechanisms are levers we can use to try and nudge a network towards our goals while creating value for token holders. Implementing them is simply that, a nudge in the right direction.

People behave in odd ways, often contrary to how you would expect, and without trying these systems out in real life we won’t know what works or what doesn’t work. The first generation of token economics was homogeneous and disappointing, the next should be experimental and full of bold pioneers. And, when someone does get it right, it will achieve a lot of good and be amazing to watch in action.

Onwards!

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