在美国追踪阿片类药物:一个高分辨率的制药分销数据集
Ambra Amico1, Luca Verginer2, Frank Schweitzer2
1Chair of Systems Design, ETH Zurich, Weinbergstrasse 56/58, 8092, Zurich, Switzerland. ambra.amico@smart.mit.edu.
Scientific data
|July 13, 2024
概括
研究人员创建了一个高分辨率的药品分销途径数据集在美国各地. 这一新的数据集重建了3.75亿个药物包装旅程,为供应网络提供了前所未有的视角.
科学领域:
- 制药供应链分析 制药供应链分析
- 医疗信息学 医疗信息学
- 网络科学 网络科学
背景情况:
- 缺乏全面的历史数据阻碍了制药供应链研究.
- 现有的数据集,如ARCOS (自动化报告和收集受控物质) 提供二次性运输记录,但不完全包裹的旅程.
- 对推进药品分销领域研究的重大障碍.
研究的目的:
- 为了解决制药供应链中的数据缺口.
- 介绍美国各地药品包装分销路径的高分辨率数据集.
- 为了使供应和分销网络的调查.
主要方法:
- 使用新的算法重建了3.75亿条分布路径.
- 使用了DEA维护的ARCOS数据库 (2006-2014年,有50亿条运输记录).
- 算法从二次性运输记录中重建完整的包裹旅程.
主要成果:
- 开发了药品分销的高分辨率数据集.
- 数据集涵盖了分发给约30万美国药房,医院和从业人员的药物包.
- 重建的路径提供了前所未有的时间和空间分辨率.
结论:
- 重建的数据集是制药供应链研究的宝贵资源.
- 提供了前所未有的美国制药分销的观点.
- 方便对复杂的供应和分销网络进行调查.
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