Registry data quality improvement by identifying discrepancies between assigned codes and text descriptions of birth

Insights

This study enhanced birth defect data accuracy in the New York State Congenital Malformations Registry (CMR) by improving British Pediatric Association (BPA) code assignments. The quality improvement process successfully identified and corrected data discrepancies, leading to more reliable surveillance for public health initiatives.

Area of Science:

  • Public Health Surveillance
  • Medical Informatics
  • Epidemiology

Background:

  • Birth defects surveillance programs are crucial for population health initiatives.
  • The New York State (NYS) Department of Health (DOH) Congenital Malformations Registry (CMR) has monitored birth defects for 30 years.
  • Accurate coding of birth defects is essential for effective surveillance and prevention efforts.

Purpose of the Study:

  • To enhance the accuracy of British Pediatric Association (BPA) codes assigned to birth defect case reports within the NYS CMR.
  • To improve the specificity and reliability of birth defect data for public health research and policy.

Main Methods:

  • Utilized computer programming to identify potential mismatches between International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes/text descriptions and BPA codes for birth years 1998-2010.
  • Flagged records with discrepancies for manual review by registry staff.
  • Implemented data correction procedures to resolve identified inaccuracies.

Main Results:

  • Scanned 164,726 records, identifying discrepancies in approximately 10% of cases, with about 8% requiring correction.
  • For targeted birth defects, 24.8% of records were reviewed, and 19% were corrected.
  • Manual review corrected 76.8% of the flagged records, indicating significant data quality improvement.

Conclusions:

  • The implemented data quality improvement approach was effective in identifying and resolving inaccuracies in the NYS CMR.
  • High-quality surveillance data supports trend monitoring, interstate comparisons, and birth defect research.
  • Improved data accuracy better informs public health policy and prevention strategies.
Abstract

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