Focusing on the assessment of health utility, the core component ofquality adjusted life years (QALYs) calculation, the author brieflycompares the utility values between the people in China and ChineseSingaporeans, as well as the values between the general populationand the people with diabetes, revealing how and why the valuesdiffer between them. The author also explicitly describes in thisbook how to establish scoring functions to yield utility values; andhow to compare different utility values, with the intention to gener-ate new knowledge on measuring health utility and provide healthservice researchers with useful tools and guidance for obtaining the values.
【作者简介】
: 王沛,复旦大学公共卫生学院副研究员、硕士生导师,Health and Quality of Lire Outcomes副主编,Pharmaco Economics-Onen编委,中国卫生经济学会卫生技术评价专委会委员,入选“2018年度上海市浦江人才计划”。主要从事健康效用评估、健康相关生命质量测量、健康量表的开发与验证、卫生经济学评价等工作。
【目录】
chapter 1 introduction
1.1 how to define health states
1 2 how to measure hsu values
1.2.1 the direct method
1.2.2 the indirect method
1.2.3 mapping health profiles to health-state utilities
1.3 whose health-state utilities should be used
1.3.1 general population health-state utilities
1.3.2 patient health-state utilities
1.4 research objectives
1.5 summary of studies
chapter 2 do chinese have similar health-state preferences? a parison of the people in china and chinese singaporeans
2.1 introduction
2.2 methods
2.2.1 sampling and recruitment
2.2.2 procedures
2.2.3 eq-vt
2.2.4 health states valued
2.2.5 data analysis
2.3 results
2.4 discussion
chapter 3 the impact of diabetes on health-state utilities
3.1 introduction
3.2 methods
3.2.1 study participants
3.2.2 survey procedures
3.2.3 health states valued
3.2.4 data analysis
3.3 results
3.4 discussion
chapter 4 valuation of eq-5d-3l health states in singapore
4.1 introduction
4.2 methods
4.2.1 sampling and recruitment
4.2.2 the valuation interview
4.2.3 the health states
4.3 statistical analysis
4.3.1 calculation of tto values
4.3.2 modeling of tto values
4.3.3 evaluation of model performance
4.4 results
4.4.1 respondents characteristics
4.4.2 distribution of tto values
4.4.3 modeling analysis
4.5 discussion
chapter 5 predicting preference-based sf-6d36 index scores from the sf-8 health survey
5.1 introduction
5.2 methods
5.2.1 sf
5.2.2 sf-6d
5.2.3 data
5.2.4 model construction
5.2.5 model estimation and evaluation
5.3 results
5.3.1 individual-level prediction
5.3.2 group-level prediction
5.4 discussion
chapter 6 preference-based sf-6d scores derived from the sf-36 and sf-12 have different discriminative power in a population health survey
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