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How Risk-Based Healthcare Could Make Us Healthier

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It is generally the case that simple concepts in nature produce incredible complexity. This applies to the genome, where simple base pairs have evolved to express complex and multifunctional instructions that would take thousands of lines of code for any human to create. This applies to the economy, where simple ideas such as the price system become infinitely complex at scale. Any free market advocate should be familiar with this proposition—Austrians, for example, often offer simple solutions, because they understand how emergent complexity might best resolve a given problem. The skeptical response is usually a demand to explain and proscribe that complexity, which can only have limited success. Emergent complexity is surprising and hard to predict, and attempting to replicate it through human laws is nearly always problematic. Rather than responsive distributed decision-making, these laws manifest as an unmanageable onslaught of authoritarian decision points only resolved by ineffective and arbitrary edict. I contend that the key to improving healthcare is through risk management and market principles, and not through command.

The concept of risk is so important to human activity that in most industries there exist risk professionals—people who are tasked with profiling threats, measuring risk, and implementing processes and controls to mitigate the risks. A business person will be familiar with this profession as actuarial sciences. As a risk professional, I offer you the most critical principle of my field: risk is a business function. Under this framing risk becomes an investment. If you invest more in risk prevention than you save in mitigation, then the business has lost money and is worse off. This insight also provides a way to quantify risk: money. Depending on how consequential the risk is we may invest in more or less accurate quantification; this spectrum is typically divided into quantitative risk assessment (strictly monetary) and qualitative risk assessment (a more basic understanding).

Modeling Health Insurance

Healthcare can be divided into several categories, which I will describe notionally as research and development (R&D), treatment, and insurance. The purpose of R&D is to better understand threats and to create treatments. The purpose of treatment is to reduce and resolve risks, and in doing so produce better health outcomes. Insurance, which for our purposes may be the most interesting category, facilitates proportional investment toward potential risks.

In the United States, auto insurance exists as a relatively free market and serves as an excellent case study. Drivers are evaluated through various criteria, and subsequently risk is calculated. This risk is quantified by estimating the likelihood and impact of risk, which is aggregated into a six-month loss expectancy. Loss expectancy changes according to driver performance, location, vehicle safety, miles driven (exposure to risk), etc. Premiums result from loss expectancy (with a profit margin of course). Premiums may change as risk posture changes, and drivers may influence premiums in many ways. Avoiding risky behavior, reducing mileage, buying safer technology, or a safer location/commute could all reduce premiums. Insurance will cover damage and injury, but rarely maintenance. All of this is markedly different from how the US healthcare system works.

Healthcare has not operated freely in the US for some time. As a result, health insurance functions more like a subscription. In 1943 the US passed tax reforms which resulted in exemptions for employer-provided health insurance. These tax exemptions incentivized movement to employer-provided health insurance. At the time, the US was engaged in World War II and had implemented sweeping price and wage controls. This made it difficult for employers to offer competitive compensation. Employers jumped at the opportunity to use health insurance as compensation, which has become the norm today. Nineteen fifty-four saw disability included in Social Security, and in 1965 the Medicare and Medicaid Services Act was passed. These programs operate as subsidized care, not contingent or responsive to risk. As a result of these reforms and more, healthcare in the United States has become masked from the consumer and from risk. Wages lost to health insurance cost are difficult to calculate. Inflated charges are difficult to detect. Health insurance has become a subscription service, covering routine maintenance and purchases. What are your health risks and how are they quantified? How is your investment in health going towards reducing these risks, and by how much? Strictly speaking, the system we have now is not traceable, auditable, or justifiable.

Premiums and Risk

In a truly risk-based health insurance market, risk is measured similarly to the way it is for modern auto insurance. Factors include health of the individual, behavior, and externalities such as location and risk posed by others. Individuals who exhibit better natural health (or have adopted measures such as vaccination) require less investment in health. Individuals who smoke or do drugs present greater risk. During times of pandemic, those individuals who are at greatest risk are those who require the greatest investment.

Although different premiums for natural health may seem unfair to some, there are many ways to manage costs. It is worth noting that those in the best health are often young people, particularly those not yet at peak earning potential. Young people prioritize other investments, and lower premiums for them could mean more resource allocation to education and training, housing, and starting families. As people grow older it becomes increasingly important to allocate money towards their health (only as unfair as retirement). If people at higher risk wish to reduce costs, there are a number of options. The market may demand an insurance provider who charges slightly more for healthy people and slightly less for the unhealthy. This system would have charitable appeal and would normalize costs. Insurance pools may also be used to reduce costs; larger pools increasingly normalize costs. A simple example would be families pooling to flatten costs.

Behavior of the individual—for instance smoking, vaping, or doing drugs—would factor into premiums, leading to interesting political ramifications. In order to determine premium impact, R&D must be conducted. This would provide objective data regarding recreational drug risks, data which is often subpar in our current system. No longer could an arbitrary scheduling system be justified, and no longer would policy be based on an authoritarian wind check. Gone is the CDC’s war on vaping. People doing risky drugs face higher premiums or reduced coverage, which would incentivize better health choices but still allow individuals to make their own bodily decisions. Returning drug policy to the health industry eliminates the drug war. Some revenue associated with drug risks would be invested in reducing those risks, allowing society to most efficiently allocate resources towards harm reduction and rehabilitation.

Pandemics and COVID-19

The data associated with COVID-19 is of poor quality. Governments around the world are pushing policies and measures which are impossible to quantify, justify, and audit. Many of these measures seem to have horrifying economic consequences and seem likely to result in less liberty and prosperity. Due to interdependence a weak economy is weaker in all areas. Healthcare is likely to suffer due to fewer resources to allocate towards care, poor supply chains, scarcity, and a suppressed populace making choices which lean towards budget rather than health. Risk-based health insurance could solve all of these problems.

In order to charge appropriately and deliver quality service, quality data must be taken. This means testing and threat profiling upon identification of disease. The clientele will be incentivized to test, as those who do not present unknown risk and warrant greater premiums. Once the disease has been profiled and tested for, those clients with the greatest risk would be identified. Their (or their pool’s) premiums rise. High-risk premiums could be reduced through risk reducing behavior—self-quarantining, reduced social activity, etc. Getting others severely or fatally ill could be treated similarly to a car accident, with claims settled through insurance. This factor further incentivizes caution to avoid transmitting the virus. Individuals who lose more through risk reduction than premium increase are free to choose to remain productive. Finally, insurance will invest in risk reduction, assigning appropriate resources to treatment and vaccination. People are welcome to refuse the vaccination, but may see an increase in premium.


This system is obviously applicable well beyond COVID-19. In order to properly allocate healthcare resources, healthcare must be responsive to risk. This is particularly true with regard to health insurance. If we are ever able to structure the industry in this way, the solutions will become emergent rather than authoritarian. In these times of fear, reduced liberty, and calls for nationalized healthcare the world over, it seems unlikely that we will see these improvements soon. Until the markets are freed we will continue to see high costs, arbitrary controls, and poor decision-making. What emerges from authoritarianism is poorer health outcomes. What emerges from liberty is an industry incentivized to keep you healthy.


Cameron Smith

Cameron Smith is a security and risk professional based out of Baltimore, Maryland. He has worked within the field for nearly 10 years, in various roles including red teaming, network security, physical security, disaster recovery, and enterprise security architecture. His clients are both private and USG.

Note: The views expressed on Mises.org are not necessarily those of the Mises Institute.
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