A METHOD FOR CALCULATING THE TOTAL QALY OUTPUT AND THE MEAN COST/QALY ATTRIBUTABLE TO THE HEALTH SECTOR; THE CASE OF THE UK
Author(s)
Kim Rand, PhD;
Maths In Health, Principal, Klimmen, Netherlands
Maths In Health, Principal, Klimmen, Netherlands
OBJECTIVES: To develop and demonstrate a transparent method for estimating the total annual QALY output attributable to the health sector in a country, and the implied mean cost per QALY, in order to inform debates on opportunity cost, allocative efficiency, and appropriate willingness-to-pay (WTP) thresholds. The United Kingdom is used as a worked example.
METHODS: We propose a counterfactual accounting framework that attributes QALY output to the health sector as the difference between (i) total QALY accrual in the observed population in a given year and (ii) QALY accrual in a counterfactual population absent the health sector. Observed QALYs are estimated by multiplying age-sex-specific person-year data by corresponding health-related quality of life (HRQoL) norms. The counterfactual population is constructed using historical life tables predating the modern health sector, scaled to the current population structure to avoid cohort and migration effects. Attribution parameters govern the share of observed longevity gains (pL) and HRQoL gains (pH) credited to the health sector. Resulting age-sex specific QALY accrual and their counterfactuals can be combined with total health-sector expenditure to estimate a mean cost per QALY. The approach is illustrated for the UK, using 1948 as the baseline year.
RESULTS: Under illustrative assumptions, with pL=pH=0.5, and average age-sex-specific HRQoL in 1948 being set to 0.2 lower than in 2022, the estimated annual QALY output attributable to the UK health sector is approximately 9.95 million. Total health-sector expenditure of approximately £317 billion imply a mean cost of £31,850 per QALY.
CONCLUSIONS: Results are highly sensitive to baseline HRQoL and attribution assumptions: the illustrative HRQoL gap and attribution shares are at the upper end of plausibility, implying that true attributable QALY output is likely lower and mean cost per QALY higher. The method provides a structured basis for sensitivity analysis and for grounding WTP thresholds in system-wide opportunity costs.
METHODS: We propose a counterfactual accounting framework that attributes QALY output to the health sector as the difference between (i) total QALY accrual in the observed population in a given year and (ii) QALY accrual in a counterfactual population absent the health sector. Observed QALYs are estimated by multiplying age-sex-specific person-year data by corresponding health-related quality of life (HRQoL) norms. The counterfactual population is constructed using historical life tables predating the modern health sector, scaled to the current population structure to avoid cohort and migration effects. Attribution parameters govern the share of observed longevity gains (pL) and HRQoL gains (pH) credited to the health sector. Resulting age-sex specific QALY accrual and their counterfactuals can be combined with total health-sector expenditure to estimate a mean cost per QALY. The approach is illustrated for the UK, using 1948 as the baseline year.
RESULTS: Under illustrative assumptions, with pL=pH=0.5, and average age-sex-specific HRQoL in 1948 being set to 0.2 lower than in 2022, the estimated annual QALY output attributable to the UK health sector is approximately 9.95 million. Total health-sector expenditure of approximately £317 billion imply a mean cost of £31,850 per QALY.
CONCLUSIONS: Results are highly sensitive to baseline HRQoL and attribution assumptions: the illustrative HRQoL gap and attribution shares are at the upper end of plausibility, implying that true attributable QALY output is likely lower and mean cost per QALY higher. The method provides a structured basis for sensitivity analysis and for grounding WTP thresholds in system-wide opportunity costs.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
EE309
Topic
Economic Evaluation
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies, Thresholds & Opportunity Cost
Disease
No Additional Disease & Conditions/Specialized Treatment Areas