Payers, consumer coalitions, and federal and state agencies are increasingly seeking to use registry data for efforts like pay-for-performance, direct-to-consumer reporting and post-market surveillance. These efforts often have implicit or explicit consequences for patients, providers and manufacturers, thus highlighting a critical need for data accuracy, according to a new paper published Sept. 20 in the Journal of the American College of Cardiology.

The paper focuses on the need for enhanced data validation as the use of registry data expands, and specifically looks at the Data Quality Program developed by the ACC's National Cardiovascular Data Registry (NCDR®) as a model for success. Under the program, which was created to ensure the completeness, consistency, and accuracy of data submitted to NCDR registries, data are filtered through a data quality report using registry-specific algorithms that require predetermined levels of completeness and consistency before being included in a registry. Next, internal quality assurance protocols enforce data standards before reporting. Finally, 300 to 625 records per registry are audited annually within 25 randomly identified sites.

Additional Resources Full Paper NCDR® Website Risk Adjusted Outcomes in the NCDR® (Cardiology)

Based on 2010 audits, the participant average raw accuracy of data abstraction for the CathPCI Registry, ICD Registry, and ACTION Registry-GWTG were 93.1 percent, 91.2 percent and 89.7 percent, respectively. According to the authors, these results serve as evidence that many fields in the NCDR accurately represent the data from the medical charts.

Moving forward, "the objective of the next generation of quality assurance is to ensure quality through a rapid learning system that combines mutually supporting components within the NCDR," the authors note. They highlight the fact that in addition to external stakeholder demands, internal uses of data in appropriate use criteria and risk-adjusted models, will also require more precise data in order to ensure valid conclusions. According to the authors, increasing the sophistication of the Data Quality Program will ensure the College is monitoring, evaluating and improving data quality in a timely and accurate manner.

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