在电子健康记录系统之间转换时进行遗留数据验证的合理方法。
A rational approach to legacy data validation when transitioning between electronic health record systems.
作者信息
Pageler Natalie M, Grazier G'Sell Max Jacob, Chandler Warren, Mailes Emily, Yang Christine, Longhurst Christopher A
机构信息
Division of Critical Care Medicine Department of Pediatrics, Stanford University School of Medicine Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA Information Services Department, Stanford Children's Health, CA
Department of Statistics, Carnegie Mellon University, Pittsburgh, PA.
出版信息
J Am Med Inform Assoc. 2016 Sep;23(5):991-4. doi: 10.1093/jamia/ocv173. Epub 2016 Mar 14.
OBJECTIVE
The objective of this project was to use statistical techniques to determine the completeness and accuracy of data migrated during electronic health record conversion.
METHODS
Data validation during migration consists of mapped record testing and validation of a sample of the data for completeness and accuracy. We statistically determined a randomized sample size for each data type based on the desired confidence level and error limits.
RESULTS
The only error identified in the post go-live period was a failure to migrate some clinical notes, which was unrelated to the validation process. No errors in the migrated data were found during the 12- month post-implementation period.
CONCLUSIONS
Compared to the typical industry approach, we have demonstrated that a statistical approach to sampling size for data validation can ensure consistent confidence levels while maximizing efficiency of the validation process during a major electronic health record conversion.
目的
本项目的目的是使用统计技术来确定电子健康记录转换过程中迁移数据的完整性和准确性。
方法
迁移过程中的数据验证包括映射记录测试以及对数据样本的完整性和准确性进行验证。我们根据所需的置信水平和误差限度，通过统计方法确定了每种数据类型的随机样本量。
结果
上线后发现的唯一错误是一些临床记录未能迁移，这与验证过程无关。在实施后的12个月期间，未发现迁移数据中的错误。
结论
与典型的行业方法相比，我们已经证明，在大型电子健康记录转换过程中，采用统计方法确定数据验证的样本量可以确保一致的置信水平，同时最大限度地提高验证过程的效率。
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