Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
Int J Health Policy Manag. 2023;12:7343. doi: 10.34172/ijhpm.2023.7343. Epub 2023 Jun 20.
A prescribing monitoring policy (PMP) was implemented in November 2015 in Anhui province, China, the first province to pilot this policy to manage the use and costs of select drugs based on their large prescription volumes and/ or costs in hospitals. This study evaluated the impact of PMP on the use and expenditures of different drugs in three tertiary hospitals in Anhui.
We obtained monthly drug use and expenditures data from three tertiary hospitals in Anhui (November 2014 through September 2017). An interrupted time series (ITS) design was used to estimate changes in defined daily doses (DDDs per month) and drug expenditures (dollars per month) of policy-targeted and non-targeted drugs after PMP implementation. Drugs were grouped based on whether they were recommended (recommended drugs) by any clinical guidelines or not (non-recommended drugs), or if they were potentially over-used (proton pump inhibitors, PPIs).
After PMP, DDDs and costs of the targeted PPIs (omeprazole) declined while use of non-targeted PPIs increased correspondingly with overall sustained declines in total PPIs. The policy impact on recommended drugs varied based on whether the targeted drugs have appropriate alternatives. The DDDs and costs of recommended drugs that have readily accessible appropriate alternatives (atorvastatin) declined, which offset increases in its alternative non-target drugs (rosuvastatin), while there was no significant change in those recommended drugs that did not have appropriate alternative drugs (clopidogrel and ticagrelor). Finally, the DDDs and costs of non-recommended drugs decreased significantly.
PMP policy impact was not the same across different drug groups. PMP did help contain the use and costs of potentially over-used drugs and non-recommended drugs. PMP did not seem to reduce the use of first-line therapeutic drugs recommended by clinical treatment guidelines, especially those lacking alternatives; such drugs are unlikely appropriate candidates for PMP.
2015 年 11 月,中国安徽省实施了一项处方监测政策(PMP),这是第一个试点该政策的省份,旨在根据医院的大处方量和/或药品成本来管理特定药品的使用和费用。本研究评估了 PMP 对安徽省三家三级医院中不同药品使用和支出的影响。
我们从安徽省的三家三级医院(2014 年 11 月至 2017 年 9 月)获得了每月的药品使用和支出数据。采用中断时间序列(ITS)设计来估计 PMP 实施后,政策靶向和非靶向药品的定义日剂量(每月 DDD)和药品支出(每月美元)的变化。根据是否有任何临床指南推荐(推荐药物)和是否有潜在过度使用(质子泵抑制剂,PPIs)将药品分为两组。
PMP 后,靶向 PPI(奥美拉唑)的 DDD 和费用下降,而非靶向 PPI 的使用相应增加,总 PPI 持续下降。政策对推荐药物的影响取决于靶向药物是否有合适的替代品。有现成易得的合适替代品(阿托伐他汀)的推荐药物的 DDD 和费用下降,抵消了其替代非靶向药物(瑞舒伐他汀)的增加,而没有合适替代品的推荐药物(氯吡格雷和替格瑞洛)则没有显著变化。最后,非推荐药物的 DDD 和费用显著下降。
PMP 政策的影响在不同的药物群体中并不相同。PMP 确实有助于控制潜在过度使用和非推荐药物的使用和成本。PMP 似乎并没有减少临床治疗指南推荐的一线治疗药物的使用,特别是那些缺乏替代品的药物;这些药物不太可能是 PMP 的合适候选药物。