Population norms for quality adjusted life years for the United States of America, China, the United Kingdom and Australia

预期寿命 质量调整寿命年 人口 人口学 医学 中国 人口增长预测 老年学 成本效益 地理 人口增长 环境卫生 风险分析(工程) 社会学 考古
作者
Andrew Palmer,Julie A. Campbell,Barbara de Graaff,Nancy Devlin,Hasnat Ahmad,Philip Clarke,Mingsheng Chen,Lei Si
出处
期刊:Health Economics [Wiley]
卷期号:30 (8): 1950-1977 被引量:13
标识
DOI:10.1002/hec.4281
摘要

Abstract Health economics uses quality adjusted life years (QALYs) to help healthcare decision makers. However, unlike life expectancy for which age‐ and sex‐dependent national life tables are available, no general population norms exist to use as a benchmark against which to compare observed or modeled projections of QALYs in sub‐populations or patients. We developed a 2‐state Markov model to generate QALY population norms for the USA, UK, China and Australia. Annual age‐ and sex‐specific probabilities of all‐cause mortality were taken from life tables combined with general population country‐specific age‐ and sex‐specific health state utilities for the EQ‐5D‐3L (all countries); and SF‐6D (Australia) multi‐attribute utility instruments (MAUI). To validate our QALY benchmark model we found that the model closely predicted population life expectancies. Using EQ‐5D‐3L, undiscounted QALYs for males/females aged 18 years ranged 54.62/58.90 (USA), 55.55/60.21 (China), 57.11/60.16 (Australia), and 58.01/61.43 (UK) years. SF‐6D benchmark QALYs for Australia were consistently lower than those generated from the EQ‐5D‐3L. The gap in undiscounted QALYs between the UK (highest) and the USA (lowest) was 2.53 QALYs in women and 3.39 QALYs in men aged 18 years. Our model's QALY population norms can be used for internal validation of future health economic models for the country‐specific value sets for the instruments that we adopted, and when quantifying burden of disease in terms of QALYs lost due to illness compared to the general population. We have created a publicly available repository to continuously include QALY benchmarks that use country‐specific value sets for other MAUIs and life expectancies.
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