Multifile probabilistic record linkage for drug overdose surveillance and public health action

记录链接是指通过标识数据内和数据之间的唯一个人来集成数据的过程 消息来源。在管理数据库中，通常具有有限数量的个人部分 识别符，如姓名或出生日期，加上排版错误和丢失的数据，构成 记录联动任务难度大，容易出错。已经展示了概率记录链接方法 与基于规则的确定性技术相比具有更好的性能，如概率法 方法更好地适应数据文件中不同和增加的错误级别。现有概率 然而，方法受到不同的限制。在实践中，遇到数据是很常见的 需要使用同时合并和重复数据消除的多个数据源的集成方案 不完整的信息，如姓名、日期或地址。这些方案超出了 已经开发了哪些常用的记录链接和重复数据删除方法。因此，我们 建议将目前可用的表现最佳的记录链接方法扩展到同时 集成多个数据文件并检测其中的重复记录。我们将开发这一方法，包括 与公共卫生-西雅图和金县合作的关联软件和图形用户界面 以确保这些项目对现实世界的需求和挑战作出反应。我们还将进行一项初步研究 实施金县行政数据系统用于过量用药监测和 对过量用药预防方案的评估。

Record linkage refers to the process of integrating data by identifying unique individuals within and across data sources. In administrative databases, it is common to have a limited amount of the individuals' partial identifiers, such as names or dates of birth, which together with typographical errors and missing data, makes the record linkage task difficult and prone to errors. Probabilistic record linkage approaches have been shown to have superior performance when compared with ruled-based deterministic techniques, as probabilistic approaches adapt better to different and increased levels of error in the datafiles. Existing probabilistic approaches are nevertheless subject to different limitations. In practice, it is common to encounter data integration scenarios where multiple data sources need to be simultaneously merged and deduplicated using imperfect information such as names, dates or addresses. These scenarios go beyond the specifications for which commonly used record linkage and deduplication methodologies have been developed. We therefore propose to extend the currently-available best-performing record linkage methodologies to simultaneously integrate multiple datafiles and detect duplicated records within them. We will develop this methodology, with an associated software and graphical user interface, in partnership with Public Health – Seattle & King County to ensure that these are responsive to real world needs and challenges. We will also conduct a pilot study implementing the techniques on King County administrative data systems used for overdose surveillance and evaluation of overdose prevention programs.