Willingness to pay (WTP) in health economics refers to the maximum amount an individual or society would pay for a unit of health improvement (typically a QALY). At the individual level, WTP is elicited through stated preference methods (contingent valuation surveys, discrete choice experiments) to value specific health states or interventions. At the societal level, the WTP threshold is the cost-effectiveness benchmark that determines which interventions are funded — interventions with ICERs below the threshold are considered good value for money. The threshold is sometimes derived empirically (from observed past decisions, displaced spending analysis) or set normatively (reflecting what society should be willing to pay). The appropriate level of the WTP threshold is one of the most consequential and debated parameters in health economics — it determines the boundary between funded and unfunded healthcare.
Every time a health system funds an intervention, it implicitly or explicitly decides how much a unit of health is worth. A system that approves a drug costing $200,000 per QALY is saying "we are willing to pay $200,000 for one year of perfect health." A system that rejects it is saying "we are not." The willingness-to-pay threshold makes this judgment explicit, transforming a vague value statement into a decision rule.
At the individual level, WTP for health improvements can be elicited through surveys. Contingent valuation asks directly: "How much would you pay for X?" Discrete choice experiments present pairs of alternatives with different attributes (cost, effectiveness, side effects, convenience) and ask which they prefer, inferring WTP from the pattern of choices. These methods are used to value health states, inform benefit-package design, and calibrate societal thresholds. However, stated preferences are prone to biases — people say they would pay more than they actually would, and their responses are sensitive to framing, question order, and anchoring.
At the societal level, the WTP threshold determines the boundary of the benefits package. The WHO previously suggested 1-3 times GDP per capita as a threshold, but this approach has been criticized as too permissive — many countries cannot afford to fund all interventions below 3× GDP per capita. More sophisticated approaches estimate the opportunity cost of health spending: the health that would be gained if the money were spent on the next-best alternative. If funding a new cancer drug at $150,000/QALY means withdrawing resources from a prevention program that produces QALYs at $15,000 each, the net effect is a loss of population health. The threshold should equal the cost-effectiveness of the marginal intervention — the last thing currently funded.
The empirical evidence suggests many countries' thresholds are too high relative to their opportunity costs. Claxton and colleagues estimated the marginal productivity of NHS spending at approximately £13,000/QALY — well below the NICE threshold of £20,000-30,000. This implies that some interventions currently funded by NICE are displacing more productive spending elsewhere in the NHS, reducing total population health. Getting the threshold right is not an academic exercise — it determines how hundreds of billions of dollars in health spending are allocated, and small changes affect millions of patients' access to care.
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