Access and economics
Explore transparent cost, QALY, budget and access-delay scenarios for psilocybin research, with explicit assumptions and links to health assessment methods.
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Explore assumptions before drawing conclusions
This transparent, one-period scenario calculator supports research planning. All inputs are user assumptions. It is not an estimate of observed psilocybin effectiveness, an investment forecast, a reimbursement recommendation or a validated health-economic model. It has no clinical effect defaults.
Enter every assumption to calculate. No trial outcome is converted automatically into QALYs.
Formulas and sensitivity
Incremental cost ΔC = intervention cost − comparator cost. Incremental cost-effectiveness ratio = ΔC / ΔQALY, reported only when incremental QALYs are positive. Net monetary benefit = scenario value × ΔQALY − ΔC. Incremental cohort budget = patients × ΔC. Access date is the user-supplied authorisation date plus assumed delay; a delay assumption alone cannot establish when approval will occur.
A QALY is a quality-adjusted life-year: time weighted by a health-related quality-of-life value. The calculator varies incremental QALYs by ±25% and intervention cost by ±25%, changing one assumption at a time. These are deterministic scenario comparisons, not confidence intervals or probabilities. The inputs apply to the same one-period horizon; no discounting, relapse, mortality, adverse-event cost, workforce constraint or retreatment is modelled.
German assessment context and evidence needs
G-BA's AMNOG explanation describes comparative added-benefit assessment and pricing. An illustrative willingness-to-pay value in this calculator is not a German statutory reimbursement threshold. For access context, consult the Germany report.
A defensible economic evaluation needs a relevant comparator, patient-reported quality of life, durability and retreatment data, resource use, adverse events, uncertainty and a stated perspective. Symptom scales alone cannot supply validated QALY gains. Study designs and populations differ; read the selected evidence comparisons before setting assumptions.