Willingness to Pay for Health Risk Reductions: Differences by Type of Illness

BACKGROUND: When it is necessary to conduct a formal benefit-cost analysis for a policy which protects human health or life, government agencies typically aggregate individual physical risk changes and then monetize these benefits using a measure known as the Value of aStatistical Life (VSL). The same VSL is typically used whether the policy leads to a reduction inthe risk of lung cancer, heart disease, or any other illness. OBJECTIVES: To demonstrate within a single study that willingness to pay (WTP) for health risk reductions varies systematically by disease type, prospective illness profile, age, smokingstatus and other factors. METHODS: A representative U.S. sample aged 25+ completed a computerized conjoint-analysis (discrete-choice experiment) survey. Each choice task involved two different health risk reductions for specific health threats described in terms of their future age-at-onset, duration,prognosis, and reduction in life expectancy. The pattern of health state durations—sick-years,recovered-years, and lost life-years—was randomly assigned for each age and gender (subject to basic plausibility exclusions). Illness labels included cancers of the breast, prostate, lung,colon, or skin, plus heart disease, heart attack, respiratory disease, stroke, diabetes, orAlzheimer’s disease. Respondents were provided with extensive tutorial material before being asked to choose their most preferred risk reduction program, where each program wasdescribed as a pin-prick diagnostic test that would provide their physician with information thatwould permit medication or other measures to reduce the health risk in question—at a specifiedannual cost. Respondents could also choose the status quo. A utility-theoretic choice model is specified in terms of discounted expected time in each of three health states (sickness, a post-illness recovered state, or lost life-years). An adaptation of a flexible translog functional form permits a second-order approximation to the underlying preference function, with heterogeneity in preferences according to the randomly assigned illness labels. RESULTS: 1,631 subjects participated, providing 6,848 choices for analysis. Results from our study differ from other VSL estimates in the literature because there is autonomous variation inWTP solely as a result of the illness label applied to a future illness profile, as well as systematic variation in marginal WTP for an avoided sick-year or an avoided lost life-year. We illustrate thecapabilities of our model by demonstrating WTP for microrisk (10e-6) reductions in the chanceof sudden death in the current period, or an illness profile that involves ten years of latency, followed by five years of illness, and then death. We show the degree of variation across age groups and by disease label, with (for example) striking differences between smokers andnonsmokers for lung cancer and respiratory disease. CONCLUSIONS: Our estimated model permits the simulation of WTP estimates for arbitrarily specified patterns of future health states, for a wide variety of major health threats. Unlike wage-risk VSL estimates, our model also spans a wide range of illness profiles (including illnesses which merely reduce life expectancy by a year or two, with only a few months of prior illness).