Bandingkan metode

	Quality-Adjusted Life Years	Healthy Life Expectancy Decomposition
Bidang	Ekonomi Kesehatan	Social Epidemiology
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	1986	2004
Pencetus	George W. Torrance; Milton C. Weinstein	Wilma J. Nusselder & Caspar W. N. Looman; Daniel F. Sullivan
Tipe	Utility-weighted survival metric pipeline	Demographic decomposition pipeline for a health-expectancy difference
Sumber perintis	Weinstein, M. C., Torrance, G., & McGuire, A. (2009). QALYs: The Basics. Value in Health, 12(Suppl 1), S5-S9.	Nusselder, W. J., & Looman, C. W. N. (2004). Decomposition of differences in health expectancy by cause. Demography, 41(2), 315-334.
Alias	QALY Computation, Quality-Adjusted Survival, Utility-Weighted Life Years, QALY Calculation for Cost-Utility Analysis	Health Expectancy Decomposition, Nusselder-Looman Decomposition, Decomposition of Disability-Free Life Expectancy, Mortality and Disability Decomposition of Health Expectancy
Terkait	3	4
Ringkasan	The quality-adjusted life year, or QALY, is the standard outcome measure of cost-utility analysis in health economics. It combines length and quality of life into one number by weighting each year a person lives by a utility value reflecting their health-related quality of life during that year, on a scale where one is full health and zero is death. One year in perfect health is one QALY; two years lived at a utility of one half is also one QALY. Because the metric expresses survival and health-related quality of life in a single unit, it lets analysts compare interventions that extend life, improve quality of life, or do both, and it forms the denominator of the incremental cost-effectiveness ratios that health-technology agencies use to decide what to fund. George Torrance set out the methods for measuring the health-state utilities at the heart of the QALY, and Weinstein, Torrance, and McGuire later distilled the concept and its construction for a broad audience.	Healthy (or disability-free) life expectancy combines how long people live with how much of that life is spent in good health, and differences in it between groups or over time reflect two distinct forces: changes in mortality and changes in the prevalence of disability. Healthy-life-expectancy decomposition separates these forces. Building on the Sullivan method — which weights life-table person-years by the age-specific share of life lived without disability — Wilma Nusselder and Caspar Looman's 2004 method splits the gap in health expectancy between two populations into an additive mortality component and a disability component for each age, and can further attribute each to specific causes. This resolves the central interpretive ambiguity of health expectancy: a population can have higher healthy life expectancy because its people die later, because they are less disabled at each age, or both, and only a decomposition can tell which.