This post elaborates on a 6/19/2014 presentation I gave at the BitTorrent HQ on decentralized autonomous health insurance, and on a prior blog post. My goals here are:
- To quantify and qualify the problems with the US healthcare system, especially as they pertain to the payer system
- To introduce my vision for decentralized autonomous health insurance
- To outline key components of successful health insurance systems
- To start laying the groundwork for applying these concepts in practice
1. The U.S. spends more on healthcare than any other country — for subpar health outcomes
1.1 The U.S. spends 17.7% of its GDP on health-related expenditures, with the Netherlands (11.9%), France (11.6%), and Germany (11.3%) landing a distant second, third, and fourth place, respectively (OECD Health Data 2013). 52.2% of U.S. healthcare spending is private rather than public. The United States, Chile, and Mexico are the only OECD countries whose health expenditures are less than 50% public (OECD Health Data 2013). Despite our country’s disproportionately high healthcare spending, life expectancy among Americans has fallen to about 81 years (as of 2011), comparable to Chile and the Czech Republic and lagging behind most other OECD countries.
1.2 To change individuals’ behavior, change their incentives. To create a sustainable system, align individuals’ incentives. I’ve identified below several flaws in US healthcare’s payer systems, all of which relate directly or indirectly to financial incentives, and discuss potential solutions later in this post.
(i) Large uninsured population. According to the US Census Bureau, the number of Americans without health insurance exceeded 48 million (15.7% of the population) in 2010.
(ii) In the US, 2.5 physicians serve 1,000 people on average, compared to the OECD average of 3.2 physicians per 1,000 people. The American Medical Association projects a shortage of 124,000 physicians (46,000 primary care physicians) by 2015.
(iii) Physicians have traditionally been incentivized financially to perform procedures, not optimize health outcomes. A surgeon is reimbursed tens of thousands of dollars for resecting tumors resulting from lifelong smoking, while general practitioners are hardly reimbursed for taking time to counsel patients on smoking cessation.
(iv) Tort laws keep physicians on the defensive and incentivize them to err on the side of excessive testing.
(v) Uneven distribution of healthcare resources
(vi) Burdensome administrative overhead to perform tasks such as preadmission certification, utilization review, membership management, collection of funds and claims, and quality assurance. Operational hurdles are a common reason for health insurance systems to fail, according to the World Bank.
(vii) Discrimination based on medical diagnoses (“pre-existing conditions”)
(viii) Disparate attitudes toward end-of-life care. Healthcare spending in the last year of life is 6 times greater on average among Medicare patients: $39,975 versus $5,993.
2. Building a smarter healthcare system
An optimal health insurance system has yet to emerge in response to the Affordable Care Act. Social and national payer systems like those in Scandinavia, Germany, and Switzerland are good working solutions, but they’re imperfect systems. Smart contracts don’t promise a utopian solution; however they allow us to iterate toward an optimal set of parameters within a dynamic actuarial system.
2.1 An insurance system in the era of smart contracts will admit its shortcomings in terms of knowledge and financial resources and instead focus on establishing malleable rules than can be updated iteratively based on outputs such as health and financial outcomes.
2.2 Each decentralized autonomous health insurance system will be constructed in a modular fashion with a uniform parameter set, such that each system represents an actuarial experiment based on community-generated contracts.
2.3 The parameters in 2.2 and aggregate financial/health outcomes will be available publicly to facilitate iterative refinement of these smart contracts governing decentralized autonomous health insurance.
2.4 Decentralized autonomous health insurance (DAHI) will shift influence away from private insurers and toward individuals. DAHI systems hold the potential to provide just and universal access to healthcare. These smart contract-based systems will not be burdened by administrative overhead and will not be victims of political consensus or lack thereof.
2.5 Decentralized autonomous health insurance will protect the socioeconomically disadvantaged. “Unless designed to be pro-poor, health insurance can widen inequity as higher income groups are more likely to be insured and use health care services,” warn Wong et al (World Bank Health Insurance Handbook). Existing health insurance tends to draw resources away from the poor. The World Bank identifies 3 mechanisms to protect vulnerable groups, including rural communities, self-employed individuals, informal workers (“black market”), small businesses, the homeless, and orphans:
(i) Compulsory universal coverage to prevent the rich opting out of the pool
(ii) Require redistribution among multiple fund pools
(iii) Financially incentivize providers to serve poor areas
The implementation of these mechanisms, however, has proven challenging because the rules governing private health insurance favor the affluent, both in their scope and execution. DAHI governed by smart contracts will enable the formation, and more importantly the automated enforcement of, fair rules ensuring the inclusion of socioeconomically disadvantaged groups.
2.6 The World Bank identifies several key considerations in designing a sustainable health insurance system:
(i) Political feasibility and political mapping
(ii) Sociocultural norms
These can strongly influence the ultimate success or failure of health insurance programs (boxes 2.2 and 2.3). In some societies, for instance, people believe that planning for inauspicious events can harbinger bad luck. A more germane example of the importance of sociocultural norms is the debate surrounding the end-of-life care in the United States.
(iii) Financial capacity
In the context of traditional government-funded health insurance, financial capacity is determined by the number of people who buy in, the size of the formal sector of the economy that is taxable, and per capital GDP (Wong et al). The World Bank also identifies the capacity to collect, pool, and spend funds efficiently and effectively as determinants of feasible and sustainable health insurance systems.
(iv) Provider capacity
The number of healthcare professionals available to provide healthcare services
3. Guiding principles
Early adoption of DAHI will rely to a large extent on a group’s social cohesiveness. As Wang and colleagues point out, social cohesiveness generally tends to correlate positively with the success of community-based microinsurance. Individuals may be more likely to buy-in if they know that risk is being shared among individuals in their communities, to whom they can relate on a personal level. Initially, smaller insured groups will mean fewer ways for the system to fail as well as greater agility in creating and modifying rules ad libitum. Associated with smaller groups however is greater financial risk. As these groups grow larger, they also become more financially insulated. Therefore, the gradual growth in the size of an insured pool translates into an opportunity to refine gradually the mechanisms governing DAHI, which are outlined below.
3.1 Health insurance based on smart contracts provides an opportunity for societies to engineer redistribution mechanisms that preserve socioeconomically disadvantaged individuals’ access to healthcare resources. The goal here is to establish rules that promote the amalgamation of insured groups, such that wealth and resources flow from the wealthy to the poor, from the healthy to the unhealthy. Each member pays according to how much she or he can afford to pay. These rules will also promote diversification of insured pools to further strengthen the group’s financial insulation. Without such rules, smart contract-based health insurance would only recreate the same inequities in access to healthcare that traditional insurance creates, namely the formation of wealthy insured groups with the exclusion of the poor. One example of a redistribution mechanism is a quota for the sponsorship of disenfranchised individuals, in which an insured group agrees to provide X% of its funds to cover for low-income individuals who could not otherwise afford health insurance.
3.2 The decentralized nature of smart contract-powered, community-based microinsurance bypasses the political roadblocks and administrative challenges that continue to hinder the implementation of the Affordable Care Act. It’s also central to the essence of DAHI as a series of actuarial experiments that allow societies to iteratively approach an optimal set of financial parameters that maximize the just distribution of healthcare resources. One question that arises, however, is the following: what will be the role of federal and state governments? Will they hinder its implementation? If DAHI does in fact become widespread, will it constitute health insurance in the eyes of the law? I believe that governments will play the important role of “the stick” by continuing to incentivize or even mandating membership in a health insurance group, akin the the Affordable Care Act. The mechanics of health insurance, however, are best left to algorithms.
3.3 Medical practice focused on health outcomes, rather than procedures, will require a corresponding shift in reimbursement. Accountable Care Organizations reflect this tendency, which is borne from the federal government’s recent reforms. Analogously, smart contract-based DAHI will be instrumental in incentivizing providers to practice health outcomes-based medicine.
3.4 This was already stated in 1.2, but because of its centrality to the concept of smart contract-based DAHI, I repeat it here. DAHI is based on the admission that no optimal solution to the current payer problem exists. There are numerous potential solutions. Each insured group in DAHI represents a controlled experiment in health economics and policy. Therefore, DAHI must be designed modularly with replicable components, a consistent set of parameters, and transparency of both inputs and outputs to allow iteration toward optimal parameter sets.
3.5 Buy-in from providers will rely foremost on their perceived value of cryptocurrency. This is a matter of time, in my opinion, as cryptocurrencies gradually become more accessible to the general public and more prevalent in commerce. Furthermore, the rate at which DAHI grows will depend to a large extent on legislators’ reaction to smart contract-based DAHI.
4. Proposed mechanisms
Sample Serpent code is available on my Github repository:
Each DAHI system will include a set of parameters including, but not limited to, the following;
(i) Maximum/minimum number of members
(ii) Percentage of member votes necessary for approval of an insurance contract in order to become active
(iii) Enrollment period start and end
(iv) Coverage period
(v) Cancelation penalty
(vi) Premium (either a range or a fixed amount)
(vii) Adjustment formula: this allows adjusting premiums based on individuals’ relative cost to a healthcare system – without ever excluding anyone. One possibility is creating an actuarial score, for example a ratio of benefits received to premiums paid over an individual’s lifetime, which can then be transferred from one contract to the next.
(viii) Maximum plan dollar limit
(ix) Terms of care provided, including access to specialists and physician reimbursement
(xi) Number of mid-level providers and physicians from each specialty, including a voting mechanisms to allow members to vote providers into or out of a group.
(xii) Reward pool to promote good health outcomes
4.1 Both beneficiaries and providers will be subject to a peer-based application process. This will be predefined in the contract’s rules, for instance as a minimum percentage of the vote, to safeguard against discrimination.
4.2 All financial and health outcomes (in anonymous aggregate) will be publically available to allow assessment of a group’s financial feasibility/sustainability, allow quality control of providers’ practices, and promote iterative refinement of the parameter set in subsequent groups. Quality control may also take the form of reputation systems for healthcare providers.
4.3 Both patients and providers will be rewarded for good health outcomes in the form of a bonus at the end of the coverage period.
5. From theory to practice
Smart contract-based decentralized autonomous health insurance, executed correctly, can provide citizens of developed and developing countries alike equitable access to healthcare resources. It has the potential to do what traditional health insurance has frequently failed to do, namely protect the interests of the most socioeconomically vulnerable, and politically weakest, individuals. While adoption of DAHI likely will be a slow process that depends upon the rate at which cryptocurrency becomes mainstream, implementation need not be an all-or-nothing process. First steps will include running simulations and eventually using DAHI in the context of coinsurance, or health insurance for specific contexts such as outpatient visits. A few interesting open questions include how existing health insurers will react to smart contract-based health insurance, and to what extent, if any, DAHI will be truly decentralized. Ultimately, federal and state legislation governing cryptocurrency and smart contracts will shape how smart contract-based insurance is implemented.
8. Actuarial anatomy
8.1 Risk pooling := collection of funds from members of a group to finance the cost of a catastrophic event (Wang et al, 11). This allows a group, rather than an individual, to bear the financial risk of paying for catastrophic costs. The larger and more diverse the group, demographically and economically, the more effectively the risk is spread (WHO 11). The concept of risk pooling is closely tied to moral hazard (see below): how can financial risk be distributed without corrupting individuals’ incentives to exercise precautions?
8.2 Risk aversion := converting a low-probability of a catastrophic event into a certain, low-burden event. Let’s say for instance that a dentist pays $40,000 to insure his hands over the course of 20 years. He has a 1% chance of losing one or both hands, but this would cost him $2 million in lost income. He can convert a 99% chance of making $2 million and keeping his hands (and a 1% chance of losing his hands and $2 million in income) into a 100% chance of losing $40,000.
8.3 Moral hazard : = when the behavior of an insured person changes – usually to become less risk averse – because they no longer bear the full cost of their behavior (Wang et al, 25). For example, let’s say that Larry has a family history of heart disease, and that the cost of treating a heart attack is $100,000. Given his family history, smoking habit, and sedentary lifestyle, his risk of a heart attack in the coming 10 years is 15%. Quitting smoking, losing weight, exercising, and regular checkups would reduce his risk of a heart attack to 7%. But what’s the point of going through all the hassle, Larry thinks, if his insurance will pay for it anyway? Possible solutions to the problem of moral hazard include:
(i) Coinsurance: the insured person still bears some of the costs and therefore retains incentive to adopt and maintain healthy behaviors
(ii) Preconditions to insurance: for instance, Larry’s health insurance requires him to get regular checkups and do an annual urine test to prove non-smoking status
8.4 Adverse selection := tendency of higher-risk individuals to be more likely to enroll in insurance. Unhealthy patients with worrisome family histories or concerning health findings buy health insurance, driving up the cost, whereas healthy individuals become less likely to purchase insurance as it becomes uneconomical.
9. Anatomy of health insurance
The following is an overview of actuarial terminology and common forms of health insurance.
9.1.1 Coinsurance := health insurance plan in which the insured person pays a given percentage of medical expenses after the deductible amount, if any, is paid
9.1.2 Deductible := fixed dollar amount during the benefit period (usually one year) that an insured person pays before the insurer starts to make payments for covered medical services
9.1.3 Premium := fees paid for coverage of medical benefits per unit time
9.1.4 Copayment := health insurance plan requires insured person to pay a fixed dollar amount when a medical service is received; the insurer pays the rest
9.1.5 Gatekeeper: individual who coordinates and authorizes medical services, laboratory studies, specialist referrals, and hospitalizations. This is often the primary care provider.
9.2 Types of health insurance plans
9.2.1 Preferred provider organization (PPO)
Patients receive care from healthcare providers in a given network. Patients are incentivized to remain within the network by being charged premiums for heathcare services received from providers outside the network.
9.2.2 Health maintenance organization (HMO) is both insurer and healthcare system. This includes organizations such as Kaiser Permanente.
9.2.3 Accountable care organization (ACO). Federal or state governments pay ACOs a lump sum to provider care for X number of individuals in a given geographic area for Y units of time. This is a new reimbursement model that emerged from increasing pressure by the federal government on healthcare systems and providers to control costs and practice outcomes-focused medicine.
I’m grateful to Vitalik Buterin, Ethereum creator and recent recipient of the Thiel Fellowship, and to Christian Peel, who runs the Silicon Valley Meetup group, for their productive feedback.
- Angrisano C. et al. “Accounting for the Cost of Health Care in the United States.” McKinsey Global Institute, Jan 2007. http://www.mckinsey.com/insights/health_systems_and_services/accounting_for_the_cost_of_health_care_in_the_united_states
- Joris Bontje’s Serpent Code. https://github.com/jorisbontje/cll-sim/blob/master/examples/i_want_half.cll
- Metwally, Omar. Github repository. https://github.com/osmode/healthereum
- OECD Health Data 2013.
- United States 2010 Census.
- Wang H. et al. Health Insurance Handbook: How to make it work. World Bank Working Paper No. 219, 2012.
- Wood, Gavin. “Ethereum: a secure decentralised transaction ledger.”