Effects of Volume-Price Contracts on Pharmaceutical Prices: A Retrospective Comparative Study of Public Hospitals in Hubei of China

Abstract

Background: Pharmaceutical expenditure has been increasing worldwide. Many countries have attempted to contain the increase through collective bargaining, including in China. In 2015, the Chinese government introduced a new policy to empower regional governments to reduce pharmaceutical prices through its existing tendering system which enables a lower price for products with higher procurement volumes. Xiangyang municipality in Hubei province took a lead in piloting this initiative.Objectives: This study aimed to evaluate the effects of the volume-price contract initiative on pharmaceutical price procured by the public hospitals in Xiangyang.Methods: A retrospective comparative design was adopted. The price of cardiovascular medicines (349 products under 164 International Nonproprietary Names) procured by the public hospitals in Xiangyang was compared with those procured in Yichang municipality in Hubei. A total of 15,921 procurement records over the period from January 2017 to December 2018 were examined (Xiangyang started the volume-price contract initiative in January 2018). Generalized linear regression models with a difference-in-differences approach which could reflect the differences between the two cities between January 2018 and December 2018 were established to test the effects of the volume-price contract initiative on pharmaceutical prices.Results: On average, the procurement price for cardiovascular medicines adjusted by defined daily dosage in Xiangyang dropped by 41.51%, compared with a 0.22% decrease in Yichang. The difference-in-differences results showed that the volume-price contract initiative resulted in a 36.24% drop (p = 0.006) in the price (30.23% for the original brands, p = 0.008), in addition to the therapeutic competition effect (31.61% reduction in the price, p = 0.002). The top 100 domestic suppliers were highly responsive to the initiative (82.80% drop in the price, p = 0.001).Conclusion: The volume-price contract initiative has the potential to bring down the price of pharmaceutical supplies. Higher responses from the domestic suppliers are evident.

The change of drug utilization in China’s public healthcare institutions under the “4 + 7” centralized drug procurement policy: Evidence from a natural experiment in China

“…As shown in Table 1 , DID analysis revealed that the monthly volume of bid-winning drugs increased significantly ( β = 1.62, p < 0.001) after policy intervention, with a 405.31% increment when some transformations of the coefficients were made ( Kim and Skordis-Worrall, 2017 ; Zhang et al, 2017 ; Li et al, 2021 ). The volume of non-winning drugs was associated with a 62.28% reduction ( β = −0.98, p < 0.001).…”

“…The usage of generic drugs has become more dominant, increasing from 59% to 78%; the increment was the largest in tertiary hospitals, followed in order by secondary hospitals and PHCs. In China, the high reliance of use in original drugs has long existed, especially in large hospitals; also, an increasing use of original drugs is found year by year ( Li et al, 2013 ; Zeng, 2013 ; Tang, 2016 ; Li et al, 2021 ; Huang et al, 2022 ), which appears to be contradicted to the situation in the United State where the generic drugs reached 90% of the prescriptions ( FDA, 2019 ). Next, the low utilization rate of the generic drugs in China could be attributed to a number of factors, including the lack of sufficient understanding in the trust to the quality and efficacy of domestic generic drugs among the physicians, pharmacists, and patients ( Oncu et al, 2020 ; Li et al, 2021 ), as well as the incentives for markups or rebates of high-priced drugs (such as the imported original drugs) ( Zeng et al, 2014 ).…”

“…Considering China’s regional variation in drug use habits, pharmaceutical industry distribution, economic level, and health resources ( Li et al, 2013 ; Zhang and Zhang, 2015 ; Yan and Yan, 2019 ), we first stratify the observation area samples by geographical regions, and then, we determine comparable control area samples within each geographical region. According to Li et al (2021) and Tang (2016) ’s method, the unweighted TOPSIS (technique for order performance by similarity to ideal solution) method was adopted to identify control samples with the highest matching degree (the closest TOPSIS score) among the provinces that did not implement “4 + 7” pilot as the control group. Nine matching variables were considered, including per capita gross domestic product (GDP), population size, number of health institutions, number of hospital beds, number of skilled health workers, number of licensed (assistant) doctors, per capital health expenditure, annual average clinical visits, and annual hospitalization rate.…”

Antibiotic Use in China’s Public Healthcare Institutions During the COVID-19 Pandemic: An Analysis of Nationwide Procurement Data, 2018–2020

“…Modified Park tests and Box-Cox tests were used to estimate family distribution and link function of each outcome indicator ( Zhang et al, 2017 ; Li et al, 2021 ). Based on the results ( Supplementary Table S3 ), we used gamma distribution and log link for most of the outcome variables; in addition, gamma distribution and identity link, Gaussian distribution and identity link, and Gaussian distribution and log link were also applied for other dependent variables.…”

Changing Characteristics of Pharmaceutical Prices in China Under Centralized Procurement Policy: A Multi-Intervention Interrupted Time Series

“…Several factors might influence bidding price, findings derived from cross-country studies reported that more potential competitors, decentralized market, and older generation drugs were generally associated with lower centralized bidding prices (Dubois et al, 2021;Wang and Zahur, 2022). Evidence from China indicated that originators are likely to gain lower prices than generics in centralized bidding (Li et al, 2021;Sun et al, 2022). These to some extent explained the difference in price changes among centralized procured INNs in this study.…”