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Background:

Electronic health information routinely collected during health care delivery and reimbursement can help address the need for evidence about the real-world effectiveness, safety, and quality of medical care. Often, distributed networks that combine information from multiple sources are needed to generate this real-world evidence.

Objective:

We provide a set of field-tested best practices and a set of recommendations for data quality checking for comparative effectiveness research (CER) in distributed data networks.

Methods:

Explore the requirements for data quality checking and describe data quality approaches undertaken by several existing multi-site networks.

Results:

There are no established standards regarding how to evaluate the quality of electronic health data for CER within distributed networks. Data checks of increasing complexity are often used, ranging from consistency with syntactic rules to …