Validating electronis databases to ensure accuracy and integrity of data

Any unintended changes to data as the result of a storage, retrieval or processing operation, including malicious intent, unexpected hardware failure, and human error, is failure of data integrity.

If the changes are the result of unauthorized access, it may also be a failure of data security.

Therefore, data validation should start with business process definition and set of business rules within this process.There are a number of regulations and guidances requiring validation of electronic health records systems, which include clinical databases – see below for a list of the more important ones.The underlying reason for the regulations is that clinical databases affect clinical data, which affect treatment decisions, which affect patient health.Data integrity is the opposite of data corruption, which is a form of data loss.The overall intent of any data integrity technique is the same: ensure data is recorded exactly as intended (such as a database correctly rejecting mutually exclusive possibilities,) and upon later retrieval, ensure the data is the same as it was when it was originally recorded.

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In short, data integrity aims to prevent unintentional changes to information.

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