Institutions, culture, and chronically ill patients’ willingness to pay for medical treatment: a meta-regression analysis
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Aim: The aim of this study is to provide a synthesis of prior research of estimates of the willingness to pay (WTP) for chronic disease treatment and examines the impact of economic and political institutions, cultures, and other importa...
Saved in:
| Main Author: | |
|---|---|
| Format: | Journal |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85088864767&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70900 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Chiang Mai University |
| Summary: | © 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Aim: The aim of this study is to provide a synthesis of prior research of estimates of the willingness to pay (WTP) for chronic disease treatment and examines the impact of economic and political institutions, cultures, and other important factors on WTP. Subject and method: The paper applies meta-regression analysis to 1053 estimates of WTP from 188 medical treatment studies from 40 countries. Results: The results suggest that patients assign higher values for medical treatment in more capitalistic and more democratic countries. Cultural traits also appear to matter, with higher WTP in societies characterized by individualism and indulgence. Further, disease types matter. Compared to cancer, WTP is lower for diabetes, obesity, asthma, and heart disease treatment, but higher for amyotrophic lateral sclerosis therapy. GDP per capita is positively associated with WTP. The higher public health expenditure is in a country, the higher citizens value health benefits. If individuals expect to live longer, then they will spend less on their health. The published studies estimate a lower value than unpublished studies. Conclusion: This paper presents a comprehensive synthesis of estimates of chronically ill patients’ WTP for medical treatment and identifies the key factors determining WTP through a meta-regression analysis. The main finding is that economic and political institutions, cultural traits, the types of disease, socio-economic characteristics, and valuation methods all influence WTP estimates. |
|---|