An Analysis Of The Utilization Of Cephalosporins From 2007 To 2011 In Guangdong Province Of China

Han, Shasha; Guan, Xiaodong; Wang, Tao; Shi, Luwen; Li, H.; Xin, Xiao-Xiong; Huang, Tian

doi:10.1016/j.jval.2014.08.532

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method divided drug cost changes into three parts: quantity factor, price factor, and structural factor, in which the structural factor represents the concept of "price structure" and refers to the combined structure of drugs at different prices. Based on the classical A.M. index system method, previous scholars constructed a drug structure index system, and has been applied in relevant studies [27,28]. The DSI represents the changes in the combination of drugs with different De ned Daily Drug cost (DDDc) in the same drug group, showing the transfer of use from drugs with lower (higher) prices to drugs with higher (lower) prices [29].…”

Section: Sample Selectionmentioning

confidence: 99%

Impact of Volume-Based Drug Procurement Policy on Drug Use Structure of Chinese Public Medical Institutions: A Difference-in-Difference Analysis of Nine Pilot Cities and Twelve Non-pilot Provinces

Lu¹,

Yang²,

Long³

et al. 2021

Preprint

View full text Add to dashboard Cite

Background In 2019, the Chinese government implemented the first round pilot of volume-based drug procurement in 4 municipalities and 7 sub-provincial cities, i.e. “4+7” policy. This study evaluated the impact of “4+7” policy on the use structure of policy-related drugs. Methods Data of China Drug Supply Information Platform (CDSIP) database was used, covering 18,636 public medical institutions from 9 pilot cities and 12 non-pilot provinces in mainland China. “4+7” policy-related drugs were selected as study samples, including 25 drugs in the “4+7” procurement List and 83 alternative drugs that have an alternative relationship with “4+7” List drugs. “4+7” List drugs were divided into bid-winning and bid-non-winning products. Drug Structure Index (DSI) was employed as the outcome variable, and higher DSI refers to the use proportion of higher-DDDc (Defined Daily Drug cost) drugs increased. Difference-in-difference (DID) method was employed to estimate the net effect of “4+7” policy. Results After policy intervention, the DSI of bid-winning drugs significantly decreased (β=-0.233, p<0.0001), while non-winning drugs (β = 0.177, p<0.001) and “4+7” List drugs (β = 0.050, p<0.01) increased. No significant change was found for the overall DSI of alternative drugs (β = 0.013, p>0.05), while a remarkable increase was found in primary healthcare settings (β = 0.033, p<0.05). In three post-“4+7” periods, the increments of DSI for non-winning products were 17.54% (period 1), 18.35% (period 2), and 19.66% (period 3). The DSI of “4+7” List drugs significantly increased in post-“4+7” period 2 and 3 (all p-values<0.05). Conclusions The use proportion of higher-DDDc bid-winning drugs significantly decreased after policy intervention. However, among drugs not involved by NCDP policy, the use proportion of higher-DDDc drugs significantly increased after policy intervention, moreover, the increment was more pronounced at the later periods of policy implementation. The clinical use monitoring and the physician’s prescription behavior supervision should be strengthened.

show abstract

Section: Sample Selectionmentioning

confidence: 99%