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.
Keywords: Data migration; applied clinical informatics; data validation; electronic health record; electronic medical record; implementation.
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