From a recent NBER paper by Darius Lakdawalla, Anup Malani, and Julian Reif:
[C]onsider a healthy consumer facing the risk of developing Parkinson’s disease in the years before the discovery of treatments that reduced the disease’s impacts on quality of life. Suppose we measure the quality of one year of life as some percentage of a year spent in perfect health. In the absence of a treatment, contracting Parkinson’s might reduce quality of life from, say, 80% of perfect health to 40%. Consider the introduction of a new medical treatment that costs roughly $5,000 per year and increases quality of life for Parkinson’s patients from 40% to 70%. If the value of perfect health for one year is $50,000, this increase in quality of life is worth $15,000 annually but costs only $5,000 annually. The traditional approach in health economics compares these two numbers to arrive at the net value of the treatment, which in this case would be $10,000 annually.
First of all, I want to flag the use of the term “value” or “net value” here. It’s consistent with what Uwe Reinhardt endorses: the difference—not ratio—of benefit and price. (Click through to the full text of his remarks.) Cost-benefit ratios (or their reciprocols), for instance, are also called “value” by some, but, as Reinhardt noted, that’s weird and inconsistent with the notion of “value” generally used in economics.
Continuing,
Notice that this calculation neglects the way the medical treatment’s introduction also compresses the variance in the quality of life between the Parkinson’s and non‐Parkinson’s states. Prior to the availability of treatment, Parkinson’s was a gamble that lowered quality of life by 40% of a perfectly healthy year, or a loss of approximately $20,000 per year; the treatment transforms the disease into a new gamble that lowers quality of life by just 10% of a perfectly healthy year, or a loss of just $5,000 per year. This compression in quality of life outcomes generates value for consumers who dislike risk.
It is true that the reduction in the variance of health outcomes is mitigated by an increase in the variance of healthcare spending. Before the availability of treatment, the individual may have faced no financial risk from falling ill with Parkinson’s; after its introduction, she faces the risk of a $5,000 per year expenditure. However, if the treatment is priced to generate consumer surplus, the ex post improvement in health outcomes will outweigh its financial cost. Thus, it should come as no surprise that this medical treatment lowers total risk in our example. Prior to the development of treatment, Parkinson’s imposes a risk of losing $20,000 in reduced health. After development, the risk of disease is transformed into a $5,000 financial risk plus a $5,000 health risk. In sum, this medical treatment cut the total risk of Parkinson’s in half. Furthermore, the nascent financial risk associated with purchasing treatment can be mitigated or even eliminated by health insurance.
I’ve put in bold a key assumption (or focus) that the authors apply in their analysis. They are considering only treatments that are priced such that consumer surplus is positive, in the absence of insurance. Given the widespread take-up of insurance, how many treatments are really priced this way? I guess it depends on whose consumer surplus one examines. For many treatments and many patients (but not for all), prices for the uninsured are above that which would generate positive consumer surplus for the uninsured. That fact is the source of moral hazard. Put it this way, at current prices, what’s the market for Sovaldi or proton beam treatments look like without insurance? I think they’re priced precisely to account for insurance. Indeed, I think these products wouldn’t exist without insurance, which is tantamount to saying that there’d be no technology-sustaining consumer surplus positive price.
Am I raising a limitation of the work here? I don’t know. (I will admit to not tracing this through all the math. Think of this as a point I’d raise in a seminar, and then I’d like to hear others who know the work better tell me what’s if what I’ve raised is important. UPDATE: Lead author Darius Lakdawalla responded to this. You’ll find that response below. It’s a good one.)
Continuing,
Even if a consumer has no health insurance, technology can reduce the physical risk she faces. In the Parkinson’s example, she faced a health risk of $20,000 prior to the technology but just a $10,000 risk after it, even if no health insurance is available. Adding health insurance to the analysis would cause the risk to fall even lower, to just $5,000. [… P]roviding consumers with access to better medical technology by encouraging medical innovation may reduce risk more efficiently than providing them with health insurance.
Their conclusion (after analysis),
New medical technologies provide substantial insurance value above and beyond standard consumer surplus. Under plausible assumptions, the insurance value is roughly equal to the conventional value. Accounting for risk thus doubles the value of medical technology over and above conventional calculations.
The ability of medical innovation to function as an insurance device influences not just the level of value, but also the relative value of alternative medical technologies. The conventional framework understates the value of technologies that treat the most severe illnesses, compared to technologies that treat mild ailments. This helps explain why health technology access decisions driven by cost‐effectiveness considerations alone often seem at odds with public opinion. For example, survey evidence suggests that representative respondents evaluating equally “cost‐effective” technologies strictly prefer paying for the one that treats the most severe illness.
I really like this because it aligns how humans tend to feel about the value of medical technologies with economic analysis, explaining why standard cost-effectiveness approaches seem wrong to us. This observation is what gives rise to the rule of rescue.
UPDATE: Here’s Lakdawalla’s response:
In fact, this is not a strong assumption, even for a high-cost drug like your Sovaldi example. To take one example, even the UK’s notoriously stingy health technology assessment agency thinks Sovaldi meets that bar quite easily.
To understand why, it helps to be a bit more literal about the issue. Drugs that generate surplus in the sick state generate a health benefit whose value exceeds the full price of the drug. That is, the gain in quality-adjusted life-years (QALYs) multiplied by the value of a QALY exceeds the full price of the drug. This is the same as saying that the cost-effectiveness ratio of a drug exceeds the value of a QALY. In the case of Sovaldi, the UK concluded that its cost-effectiveness exceeds $50K. Since a QALY is almost surely worth more than that, it follows that Sovaldi generates surplus in the sick state, even when its full price is considered, and even according to the UK.
One caveat is that drugs are priced to hit cost-effectiveness thresholds in markets that perform this analysis — like the UK — but not necessarily in the US. However, most of the time, this ends up being largely a wash. Let’s stick with the Sovaldi example to illustrate. Sovaldi costs $58K in the UK. Large private insurers in the US are probably paying 10-30% more than this, depending on their size and bargaining leverage. This is a pretty typical price differential between UK and US payers. However, the UK’s threshold of $50K/QALY is almost surely much less than 30% below the revealed preference willingness to pay for a QALY in the US. (For example, the labor literature says the value of a statistical life-year is about $200-300K. We have some work showing that metastatic cancer patients are willing to pay about $300K per life year. Etc.) Thus, on balance, Sovaldi is generating surplus in the sick state even at US prices.
Of course, the spirit of your point is still correct, because there are non-trivial numbers of drugs that fail to meet this bar. In addition, if sick people were better insured against the financial risk of illness, more drugs would generate surplus in the sick state, because the willingness to pay for health would go up among the sick. This is the sense in which financial insurance and medical technology are complements.
