Comparing clinical automated, medical record, and hybrid data sources for diabetes quality measures

Abstract

Background: Little is known about the relative reliability of medical record and clinical automated data, sources commonly used to assess diabetes quality of care. The agreement between diabetes quality measures constructed from clinical automated versus medical record data sources was compared, and the performance of hybrid measures derived from a combination of the two data sources was examined.

Methods: Medical records were abstracted for 1,032 patients with diabetes who received care from 21 facilities in 4 Veterans Integrated Service Networks. Automated data were obtained from a central Veterans Health Administration diabetes registry containing information on laboratory tests and medication use.

Results: Success rates were higher for process measures derived from medical record data than from automated data, but no substantial differences among data sources were found for the intermediate outcome measures. Agreement for measures derived from the medical record compared with automated data was moderate for process measures but high for intermediate outcome measures. Hybrid measures yielded success rates similar to those of medical record-based measures but would have required about 50% fewer chart reviews.

Conclusions: Agreement between medical record and automated data was generally high. Yet even in an integrated health care system with sophisticated information technology, automated data tended to underestimate the success rate in technical process measures for diabetes care and yielded different quartile performance rankings for facilities. Applying hybrid methodology yielded results consistent with the medical record but required less data to come from medical record reviews.