Democratizing healthcare through decentralized consensus

The concept of cryptocurrency, and more broadly, of decentralized consensus, represents a shift away from the old-world paradigm of centralized authority. My parents’ generation (and their parents’ generation) grew up accustomed to confiding their trust in infallible governments, fail-safe banks, and reputable degree-granting academic institutions to which they paid decades’ worth of savings so that their children would have a better chance in society. Although decentralized consensus is silently changing the economic underpinnings of our society, I regard cryptocurrency and decentralized consensus as safeguards of the democratic ideals espoused by our constitution. The reality is that cryptocurrency is here to stay. Paradigm shifts are a constant in human history, and I believe that the emergence of decentralized consensus will mark one of the most momentous paradigm shifts in human history.

My friends and I went to hear Andreas Antonopolous, a cryptography and cryptocurrency guru, answer Bitcoin questions yesterday. If I were to summarize the 2-hour meetup in one sentence, it would be the following: the details of how cryptocurrencies are traded are still maturing, but the concept of decentralized consensus is here to stay. Decentralized consensus holds the promise of democracy 2.0, something that’s remained a Utopian dream except in the tiny country of Switzerland. Decentralized consensus holds the promise of a better world where governments and organizations don’t steal from politically weak, defenseless individuals. As Antonopolous points out, we’re fortunate enough to have a benevolent government in the United States, but the majority of the world is not so fortunate. Decentralized consensus holds the promise of empowering people to exercise the power of their vote to truly make healthcare a human right. Before I expound on this latter point, I want to outline some technical underpinnings for the uninitiated, so bear with me.

Satoshi Nakamoto’s most remarkable achievement with Bitcoin is the cryptocurrency’s success in solving the problem of a decentralized public ledger. In the case of the US Dollar or any other currency backed by a governmental body or bank, there exists a central authority that acts as the ledger. Bitcoin’s brilliance lies in the fact that the ledger is public, encompassing potentially everyone and anyone. The blockchain ledger is the communal ledger that lends cryptocurrencies their value. It’s characterized by the following 2 criteria [4]:

  • Blocks are very difficult to discover (Difficulty Factor * 2^32 hashes)
  • Blocks are easy to validate

A Bitcoin comes into existence when a “miner” uses her/his machine (and therefore computing resources, disk space, and electrical energy) to generate new blocks that record cryptocurrency transactions. The block chain with the most cumulative computational work is accepted by consensus as the valid block. In other words,  physical energy (electricity) is converted into Bitcoins. Keep that in mind if you ever find yourself wondering whether or not cryptocurrency is “a thing.” The reward for mining Bitcoins diminishes with time, as the horizontal asymptote of ~21 million BTC is approached (around 2024).

This setup has a few interesting results with regard to game theory. While mathematicians reading this will quickly pick up on the fact that wielding >50% of mining power holds the theoretical potential to manipulate the currency, game theorists should also note that this system strongly incentivizes cooperation and veracity [2] (I won’t get into the details here, but I’ll refer you to a suggested reading list at the end of the post).

The Bitcoin protocol is not Turing-complete. Enter Ethereum, a Turing-complete protocol for scripting contracts in the blockchain. Ethereum is big. If you’re not a believer yet in Vitalik Buterin and his work, I encourage you to check out the whitepaper for an interesting read. Ethereum uses a Python-like scripting language (Serpent) to convert contracts into cryptographic building blocks. For the first time in history, parties entering into agreements are not at the mercy of inherently biased third parties. Ethereum marks an era in which algorithms — not banks, governments, or individuals — hold the power to validate and execute contracts.

One interesting result of this decentralization is the so-called Decentralized Autonomous Organization (DAO), in which each member is represented as a cryptographic public key [1]. A contract that exists as lines of code in a Turing-complete language means that we can go beyond simple two-party agreements, like this prenuptial agreement written in Ethereum, to a corporate-like structure that automates redistribution of internal capital among participants in exchange for services provided, assets, or computational power. Transactions can contain information like votes, changes in the contract (such as amendments), or adding/removing members [1]. Most importantly, this is all automated without reliance on an escrow or central authority.

The U.S. healthcare crisis has demonstrated how lawmakers, insurance companies, and healthcare systems are struggling to figure out a way to fairly distribute access to healthcare. The U.S. healthcare system was hurt by an incentive system that rewards procedures rather than quality of care and health outcomes. Recent changes in CMS reimbursement are starting to change this, prompting the emergence of Accountable Care Organizations that receive payment in exchange for providing healthcare to a fixed population, rather than on a fee-for-service basis. The healthcare system failed for the same reason the financial industry lost its credibility in the 2008 financial crisis: third parties succeed in manipulating an easily manipulable system in their favor. People were robbed blind.

I’ll give a simple example of what I’ll call Decentralized Autonomous Health Insurance. Let’s say individuals A through J enter an agreement with physicians X and Y, in which X and Y agree to provide healthcare to individuals A-J. Let’s say in this simplified example that X and Y are not reimbursed for their services, but by A-J’s health outcomes (in ancient China, physicians were paid when their patients were healthy, not when they were sick). Let’s also say that X & Y have a practice that accepts cryptocurrency as payment. Then, A-J and X&Y can pen a virtual contract with the following stipulations:

  1. A-J pay 20 Bitcoins per year to receive care from X & Y’s practice.
  2. The cost to X & Y of providing healthcare to A-J is deducted from the pool of Bitcoins in (1)
  3. X & Y will receive a minimum reimbursement of 10 Bitcoins per patient per year.
  4. If the cost of providing healthcare is less than 10 Bitcoins per person per year, the surplus is shared evenly between providers (X & Y) and patients A – J. This incentivizes patients A – J to take care of their health so they get a bonus at the end of the year, and it incentivizes X & Y to adhere to primary/preventative medicine best practices (including taking time to counsel patients).
  5. A-J can vote annually on which providers they want to provide them with healthcare.
  6. A-J can vote annually on important decisions that affect the distribution of healthcare services.

We might even imagine a scenario in which each patient’s medical record is encoded and distributed in a decentralized manner such that it exists as undecipherable bytes among millions of computers around the world, rather than behind the walls of a single healthcare system. For example, a chip could keep track of our health habits and automatically append these data to our blockchain-based medical records. These data (such as smoking and exercise habits) could then be integrated into the communal contract, so that sedentary smokers have to pay more Bitcoins per year than active non-smokers in order to receive care from X & Y. In this model, individuals’ health (not access to healthcare!) is the internal capital. Everyone is both a payer and consumer of healthcare, and everyone has the power to vote on the bounds and conditions of care provided. This type of Ethereum-based Decentralized Autonomous Health Insurance would have no administrative overhead, no bureaucracy, and no board of directors to decide who is healthy enough to be insured.

I’m less interested in the exact economics of the hypothetical example above than in the broader concept of decentralized consensus and the self-fulfilling social contract. It’s time to decentralize health insurance the same way cryptocurrency is decentralizing currency.

Cryptocurrency and Ethereum are a new social and technological frontier, which haven’t really reached mainstream yet. These young protocols still have to pass several important tests (such as reliable security mechanisms) and prove their scalability before they become widely used, but I’m optimistic. The future will be one shaped by knowledge, and less so by historical inertia. Decentralized Autonomous Organizations hold the promise of just distribution of scarce resources, including the most vital one of all: access to healthcare.


  1. Ethereum Whitepaper
  2. Vitalik Buterin’s blog
  3. Bitcoin: Open source P2P money
  4. Brian Warner’s technical introduction to Bitcoin


[First published on my Quora blog on May 7th 2014]

Brave New Wearable World

From Google Glass to Misfit Shine, wearables refer to any hardware that can be worn around, hardware with which we interact in ways beyond the traditional keyboard and mouse/touchpad. Wearables are our daily companions, collecting information about our bodies and environments, adapting their behavior to our movements. Most of them sync via Bluetooth (or BLE) to our mobile phones. A related but different category of devices under the larger umbrella of the Internet of Things are so-called “there-ables” (a nice term used by Naveen Salvadurai).

But the reality is that wearables are still in their infancy. The term still means little to people in non-tech industries.

I started writing software in 1997 when my parents bought Sony’s PlayStation developer kit for my 12th birthday, the so-called Net Yaroze. Everything was written in the C programming back then. There was no Stackoverflow and no Googling around for sample code. When I couldn’t figure something out, I had to flip through a stack of reference manuals that shipped with the device until I eventually figured things out.

Nowadays languages like Python and Ruby are all the rage. I give credit to the open source community to the modularity of these languages, allowing people to write and contribute to libraries and frameworks that make writing software far easier than it was in the days of C. Developers can now focus on building things and rapidly prototyping rather than figuring out how to accomplish relatively low-level tasks like rendering graphics.

A similar phenomenon is emerging in the hardware world. The open source hardware community is vibrantly blossoming. Hardware hackers are sharing schematics of their creations online, and tools like Arduino, Raspberry Pi, and BeagleBone are helping engineers and non-engineers alike prototype their ideas and build devices that are turning the “Internet of Things” from a buzzword into a reality. Even Google announced a new modular phone, challenging consumers to rethink the lay “blackbox” view of hardware.

Hardware prototyping has become remarkably analogous to software development, thanks to the rise of open source hardware communities and modular prototyping platforms. This is a tremendous driving force behind the explosion of wearables. You need a team of skilled electrical, industrial, and software engineers, a good amount of capital, and a factory to manufacture a new line of activity trackers. But even the most popular wearable devices nowadays are increasingly being born as Kickstarter-funded prototypes on breadboards. The big challenge isn’t conceiving or manufacturing these wearables; the big challenge is identifying a compelling use case, and a hungry market.

Prototyping smart watches
Prototyping smart watches

One group working heroically to make hardware accessible to all is iRoboticist. I spent the past weekend in an awesome 2-day workshop run by Saurabh Palan and his team expanding my knowledge about wearable hardware and getting inspired by smart, passionate hardware hackers from all walks of life. In a few hours, I built a smartwatch prototype that can display the wearer’s heart rate, temperature, and distance walked via a 3-axis accelerometer. Oh, and it also tells time.

The greatest act of rebellion is propagating knowledge. For the sake of knowledge.

Wearables are cool, but as iRoboticist founder Saurabh Palan points out, the greatest hardware of all is the human body, which continues to inspire engineers on a daily basis. No robot is as agile as a human. No app can recognize voices or images like the human mind. I’ve yet to see a robot that can repair itself when damaged.

I’ve come to believe that designers have the most important role in product development. My experience of co-founding PulseBeat and going through the Blueprint Health incubator have convinced me of this beyond a doubt. By designer, I mean someone who works to understand users and systematically studies how they interact with hardware and software. Someone who engineers not just graphical interface or the physical form of a device, but also its functionality. I hope that someday the position of a hospital’s Chief Informatics Officer won’t be filled by (semi-)retired physicians climbing the organizational ladder, but by true designers passionate about the interaction between patients, physicians, nurses, software, and hardware.

I’ll wrap up this post with a final thought on the most important of questions in tech entrepreneurship, the so-what question. From venture capitalists to physicians to journalists, people frequently ask me what I think about wearable technology and where it’s going. Technology is like the restless child running laps around our wizened, slow-moving society of bureaucrats and reactionary institutions. The majority of new technologies, regardless of how much Silicon Valley hypes them and infuses them with venture funds, never find a place in the real world. They either fizzle out or become sustenance for bigger fish. But that doesn’t matter — it’s part of the process of innovation. That’s why I chose tech over academia. Throw a lot of spaghetti against the wall until a strand sticks.

Building software and hardware is my passion. The Valley is filled with very talented engineers and hackers. It’s burgeoning with bullish investors eager to invest in new ideas and wide-eyed founders. But the most valuable thing I learned from my time at Blueprint Health was the fact that the biggest challenge any startup faces is not an engineering or funding question; it’s the so-what question.

We’ll eventually have miniature, implantable, and edible hardware with dozens of sensors onboard. But collecting data is not enough. Even doing analytics on these data is not enough. There’s a huge mismatch between sensors and actuators in health tech. It’s not enough to know that a patient’s health has changed for the worst. The trillion dollar question is, what will your app or hardware do to turn a patient’s health around, whether it’s delivering healthcare workers (what my startup does), delivering therapeutics, or changing people’s behavior.

So you built a cool app or a beautiful new wearable device. But what problem is it solving? Whose pain is it alleviating? To paraphrase Sam Altman, are you selling a painkiller or a vitamin?

We need to get patients, engineers, and healthcare professionals to sit down at the same table more often. The process of product development is radically different in health tech than in other industries. I think the reason so few people have really figured out health tech lies in the fact that it’s hard to get these 3 parties, who have disparate pain points, to participate equally in the development of consumer health apps and wearables. I’m working hard to change this.

[First published on my Quora blog on April 21st 2014]

The Holy Grail: automating documentation of patient encounters

Ask any healthcare professional to make one wish, and more often than not it’ll be something along the lines of, “I wish I had an app to write my notes for me.” Documenting patient encounters is time-consuming, annoying, and takes away time/attention that could be better spent communicating face-to-face with patients. This past weekend, I peeled myself away from PulseBeat-related work to spend the weekend in Boston participating in MIT’s healthcare hackathon. I went with Google Glass developer extraordinaire, John Rodley (TwiAge, a fellow Blueprint startup), and met several other talented people there. After 2 days of hacking, we walked away with a functional prototype of a Glass app that does just that — and won First Place. More importantly, I learned a lot and walked away feeling even hungrier to change healthcare as we knew it.

[First published on my Quora blog on March 18th 2014]

The Winning Team
The Winning Team at MIT’s Hacking Medicine Hackathon (March 2014)