Study on cost-utility threshold based on the preference of population in Liaoning province
- VernacularTitle:基于辽宁省人群偏好的成本-效用阈值研究
- Author:
Lihua SUN
1
;
Shiqi LI
1
;
Ziping YE
1
;
Abduhilil RAELA
1
;
Jiaxin HUANG
1
Author Information
1. School of Business Administration，Shenyang Pharmaceutical University，Shenyang 110016，China
- Publication Type:Journal Article
- Keywords:
pharmacoeconomics;
cost-utility threshold;
willingness-to-pay method;
Liaoning province
- From:
China Pharmacy
2023;34(12):1473-1477
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To study the cost-utility threshold （WTP/Q） based on the preference of the population in Liaoning province with willingness-to-pay（WTP） survey method， and to provide reference for decision-making. METHODS Using the method of questionnaire survey， quota sampling combined with snowball sampling were used to conduct telephone interviews with the general population in Liaoning province， collect data and analyze it. Probit regression combined with generalized linear model was used to analyze the relevant factors affecting WTP/Q. RESULTS A total of 755 general people were recruited. The WTP/Q of Liaoning population was 119 175 yuan，the average WTP/Q for improving the quality of life was 84 902 yuan， and the average WTP/Q for extending the survival period was 188 005 yuan. The analysis of influential factors showed that the older the age， the lower the probability of people purchasing medical interventions； the higher the education level and income， the greater the WTP/ Q； at the same time， the physical feelings of the interviewee， such as pain and depression， could also affect the WTP/Q results； compared with the scenario of improving quality of life， the WTP/Q for the extended survival period was higher. CONCLUSIONS The WTP/Q of Liaoning province based on the WTP survey method is about 2.07 times of the per capita gross domestic product of Liaoning province in the same period. The WTP/Q for extending survival period is about 2.21 times that of improving the quality of life. Therefore， interventions to improve quality of life and to extend the survival period need to be treated differently， in measurement or decision-making.
