The National Cardiovascular Data Registry (NCDR) Data Quality Brief: the NCDR Data Quality Program in 2012

J Am Coll Cardiol. 2012 Oct 16;60(16):1484-8. doi: 10.1016/j.jacc.2012.07.020. Epub 2012 Sep 19.


Objectives: The National Cardiovascular Data Registry (NCDR) developed the Data Quality Program to meet the objectives of ensuring the completeness, consistency, and accuracy of data submitted to the observational clinical registries. The Data Quality Program consists of 3 main components: 1) a data quality report; 2) a set of internal quality assurance protocols; and 3) a yearly data audit program.

Background: Since its inception in 1997, the NCDR has been the basis for the development of performance and quality metrics, site-level quality improvement programs, and peer-reviewed health outcomes research.

Methods: Before inclusion in the registry, data are filtered through the registry-specific algorithms that require predetermined levels of completeness and consistency for submitted data fields as part of the data quality report. Internal quality assurance protocols enforce data standards before reporting. Within each registry, 300 to 625 records are audited annually in 25 randomly identified sites (i.e., 12 to 25 records per audited site).

Results: In the 2010 audits, the participant average raw accuracy of data abstraction for the CathPCI Registry, ICD Registry, and ACTION Registry-GWTG were, respectively, 93.1% (range, 89.4% minimum, 97.4% maximum), 91.2% (range, 83.7% minimum, 95.7% maximum), and 89.7.% (range, 85% minimum, 95% maximum).

Conclusions: The 2010 audits provided evidence that many fields in the NCDR accurately represent the data from the medical charts. The American College of Cardiology Foundation is undertaking a series of initiatives aimed at creating a quality assurance rapid learning system, which, when complete, will monitor, evaluate, and improve data quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cardiovascular Diseases*
  • Humans
  • Medical Audit
  • Registries*
  • Research Design