Background: Cost-effectiveness analysis is an important tool for informing treatment coverage and pricing decisions, yet no consensus exists about what threshold for the incremental cost-effectiveness ratio (ICER) in dollars per quality-adjusted life-year (QALY) gained indicates whether treatments are likely to be cost-effective in the United States.
Objective: To estimate a U.S. cost-effectiveness threshold based on health opportunity costs.
Design: Simulation of short-term mortality and morbidity attributable to persons dropping health insurance due to increased health care expenditures passed though as premium increases. Model inputs came from demographic data and the literature; 95% uncertainty intervals (UIs) were constructed.
Setting: Population-based.
Participants: Simulated cohort of 100 000 individuals from the U.S. population with direct-purchase private health insurance.
Measurements: Number of persons dropping insurance coverage, number of additional deaths, and QALYs lost from increased mortality and morbidity, all per increase of $10 000 000 (2019 U.S. dollars) in population treatment cost.
Results: Per $10 000 000 increase in health care expenditures, 1860 persons (95% UI, 1080 to 2840 persons) were simulated to become uninsured, causing 5 deaths (UI, 3 to 11 deaths), 81 QALYs (UI, 40 to 170 QALYs) lost due to death, and 15 QALYs (UI, 6 to 32 QALYs) lost due to illness; this implies a cost-effectiveness threshold of $104 000 per QALY (UI, $51 000 to $209 000 per QALY) in 2019 U.S. dollars. Given available evidence, there is about 14% probability that the threshold exceeds $150 000 per QALY and about 48% probability that it lies below $100 000 per QALY.
Limitations: Estimates were sensitive to inputs, most notably the effects of losing insurance on mortality and of premium increases on becoming uninsured. Health opportunity costs may vary by population. Nonhealth opportunity costs were excluded.
Conclusion: Given current evidence, treatments with ICERs above the range $100 000 to $150 000 per QALY are unlikely to be cost-effective in the United States.
Primary funding source: None.