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作 者:张婧[1] 黄元楷 席晓宇[1] ZHANG Jing;HUANG Yuankai;XI Xiaoyu(Research Center of National Drug Policy&Ecosystem,China Pharmaceutical University,Nanjing 211198,China)
机构地区:[1]中国药科大学国家药物政策与医药产业经济研究中心,南京211198
出 处:《中国药房》2021年第22期2790-2793,共4页China Pharmacy
基 金:国家自然科学基金(青年科学基金)资助项目(No.72004230)。
摘 要:目的:为药物经济学预算影响分析研究的开展和相关决策提供参考。方法:以使用新干预措施的增量人数为切入点,设计新的计算方法,并分析新算法相较于常见算法的优势及潜在应用范围。结果与结论:新算法直接使用来源于真实世界的销售数据推算各干预方案的使用人数及其增量。相较于常见算法,新算法不考虑各干预方案使用人数的不变部分,转而重点关注使用人数的变化部分,回避了目标人群和某些干预方案使用人数的估算,能够在一定程度上解决常见算法对目标人群和市场份额预测不合理或不准确的问题,而且可以进行灵活调整以适应不同的市场情形和支付准入情形。但也存在关键参数(如抢占率等)来源主观性较强或数据来源不准确等不足,从而导致使用人数计算过程中不确定性因素较多。OBJECTIVE:To provide reference for the development of pharmacoeconomic budget impact analysis and related decision-making.METHODS:Taking the incremental number of people using new intervention measures as the starting point,a new algorithm was designed,and the advantages and potential application scope of the new algorithm were compared with those of common algorithms.RESULTS&CONCLUSIONS:The new algorithm directly used the sales data from the real world to calculate the number of users and their increment of each intervention scheme.Compared with common algorithms,the new algorithm did not consider the unchanged part of the number of users of each intervention scheme,but focused on the changing part of the number of users,avoided the estimation of the number of the target population and the users of some intervention schemes,and could solve the problem of unreasonable or inaccurate prediction of the target population and market share by common algorithms to a certain extent;moreover,it could be flexibly adjusted to adapt to different market conditions and medical insurance access conditions.However,due to the strong subjectivity of key parameters(such as preemption rate)or inaccurate data sources,the calculation results of the new algorithm are still uncertain.
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