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基本药物不良反应数量与就诊人次关系的研究:基于向量自回归模型
Authors Tang W , Chen H, Zhang Z, Wu G, Lin Y
Received 6 June 2023
Accepted for publication 5 December 2023
Published 14 December 2023 Volume 2023:16 Pages 2771—2778
DOI https://doi.org/10.2147/RMHP.S420407
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Jongwha Chang
Objective: To analyse the relationship between the adverse drug reactions (ADRs) of essential drugs and visits, based on the recorded annual increase in ADRs associated with essential medicines in China, to provide a reliable theoretical basis for further analysis and optimization of the safety of essential drugs.
Methods: The data of adverse reactions of essential drugs in China from 2011 to 2020, time series analysis was conducted, and vector autoregressive (VAR) model was established. The relationship between the number of ADRs and visits was explored empirically through Granger causality test, impulse response function and variance decomposition.
Results: There was a long-term cointegration relationship and one-way causality between the number of visits and ADRs caused by essential medicines. In the initial stage, the ADR response to the number of visits increased sharply, but with an increase in the number of lag periods, the impact remained basically stable, even showing a slight decreasing trend.
Conclusion: The number of visits impacts ADRs caused by essential medicines, but this impact remains basically stable after reaching a certain level.
Keywords: essential medicines, adverse drug reactions, vector autoregressive model, time-series analysis