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PharmacoEconomics

, Volume 32, Issue 3, pp 293–303 | Cite as

Pharmaceutical Pricing: An Empirical Study of Market Competition in Chinese Hospitals

  • Jing WuEmail author
  • Judy Xu
  • Gordon Liu
  • Jiuhong Wu
Original Research Article

Abstract

Background

High pharmaceutical prices and over-prescribing of high-priced pharmaceuticals in Chinese hospitals has long been criticized. Although policy makers have tried to address these issues, they have not yet found an effective balance between government regulation and market forces.

Objective

Our objective was to explore the impact of market competition on pharmaceutical pricing under Chinese government regulation.

Methods

Data from 11 public tertiary hospitals in three cities in China from 2002 to 2005 were used to explore the effect of generic and therapeutic competition on prices of antibiotics and cardiovascular products. A quasi-hedonic regression model was employed to estimate the impact of competition. The inputs to our model were specific attributes of the products and manufacturers, with the exception of competition variables.

Results

Our results suggest that pharmaceutical prices are inversely related to the number of generic and therapeutic competitors, but positively related to the number of therapeutic classes. In addition, the product prices of leading local manufacturers are not only significantly lower than those of global manufacturers, but are also lower than their non-leading counterparts when other product attributes are controlled for.

Conclusion

Under the highly price-regulated market in China, competition from generic and therapeutic competitors did decrease pharmaceutical prices. Further research is needed to explore whether this competition increases consumer welfare in China’s healthcare setting.

Keywords

Anatomical Therapeutic Chemical Bidding Price Generic Molecule Therapeutic Category Pharmaceutical Price 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This study is funded by the National Natural Science Foundation of China (Grant Number 71203155) and Humane Social Science Fund Project of Ministry of Education China (Grant Number 13YJAZH108). All authors contributed to all aspects of the paper. J. Wu is the guarantor for the overall content of this paper. The authors have no conflicts of interest that are directly relevant to the contents of this study.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.School of Pharmaceutical Science and TechnologyTianjin UniversityTianjinChina
  2. 2.School of Public AdministrationSouthwestern University of Finance and EconomicsChengduChina
  3. 3.National School of DevelopmentPeking UniversityBeijingChina
  4. 4.Department of Pharmacy306 Hospital of PLABeijingChina

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