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PharmacoEconomics
Published in: PharmacoEconomics 12/2020

01-12-2020 | Original Research Article

Informing a Cost-Effectiveness Threshold for Health Technology Assessment in China: A Marginal Productivity Approach

Authors: Jessica Ochalek, Haiyin Wang, Yuanyuan Gu, James Lomas, Henry Cutler, Chunlin Jin

Published in: PharmacoEconomics | Issue 12/2020

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Abstract

Background

Health technology assessment has been increasingly used in China, having been legally mandated in 2019, to inform reimbursement decisions and price negotiations between the National Healthcare Security Administration and pharmaceutical companies around the price of new pharmaceuticals. The criteria currently used to judge cost effectiveness and inform pricing negotiations, 3 × GDP per capita, is based on the rule of thumb previously recommended by the World Health Organization rather than an estimate based on an empirical assessment of health opportunity costs.

Objective

The objective of this study was to inform a cost-effectiveness threshold for health technology assessment in China that accounts for health opportunity cost.

Methods

The elasticity of health outcomes with respect to health expenditure was estimated using variations across 30 provincial-level administrative divisions in 2017 controlling for a range of other factors and using an instrumental variable approach to account for endogeneity to assess robustness of results. The estimated elasticity was then used to calculate the cost per disability-adjusted life-year (DALY) averted by variations in Chinese health expenditure at the margin.

Results

The range estimated from this study, 27,923–52,247 (2017 RMB) (central estimate 37,446) per DALY averted or 47–88% of GDP per capita (central estimate 63%), shows that a cost per DALY averted cost-effectiveness threshold that reflects health opportunity costs is below 1 × GDP per capita.

Conclusion

Our results suggest that the current cost-effectiveness threshold used in China is too high; continuing to use it risks decisions that reduce overall population health.
Appendix
Available only for authorised users
Footnotes
1
Most variables considered in the study are available only up to 2017.
 
2
Our data exclude Tibet due to missing data. This leaves us with a sample size of 30.
 
3
The first two are only used when the health outcome is DALY rate since the other two are already age specific.
 
4
We consider 0.7 as the threshold for a too high correlation.
 
5
It would be ideal to control for provincial fixed effects. Unfortunately, there is insufficient within-province variation in the expenditure variable for this approach to be viable. We therefore chose to estimate pooled OLS, which is the same type of panel analysis that is undertaken in Siverskog and Henriksson [17].
 
6
Corresponding pooled OLS analysis looking at 2011–2017 for the mortality rate outcomes finds similar coefficient estimates. These results are presented in Table S2, Electronic Supplementary Material.
 
7
The statistical insignificance may be caused by the relatively small sample size; for example, large effect and large standard error at the same time.
 
8
Corresponding pooled OLS IV estimates for the mortality rate outcome models are found in Tables S3 and S4, Electronic Supplementary Material, which provide very similar coefficient estimates. Again, in each case, the IVs pass all three identification tests. The endogeneity tests suggest the exogeneity of health expenditure cannot be rejected based on the data.
 
9
Calculating using an exchange rate of 0.148 for 2017 from the World Bank https://​data.​worldbank.​org/​indicator/​PA.​NUS.​FCRF.
 
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Metadata
Title
Informing a Cost-Effectiveness Threshold for Health Technology Assessment in China: A Marginal Productivity Approach
Authors
Jessica Ochalek
Haiyin Wang
Yuanyuan Gu
James Lomas
Henry Cutler
Chunlin Jin
Publication date
01-12-2020
Publisher
Springer International Publishing
Published in
PharmacoEconomics / Issue 12/2020
Print ISSN: 1170-7690
Electronic ISSN: 1179-2027
DOI
https://doi.org/10.1007/s40273-020-00954-y

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