KEYWORDS:
data quality
BACKGROUND:
Data quality is a focus area in the CDC/NIP Immunization Registry Support Branch five year strategic plan and has data quality measurements for accuracy, completeness, timeliness, and data quality improvement methodologies.
OBJECTIVE:
Describe the current status of immunization registry data quality and examine key components of data quality improvement plans
METHOD:
56 of 64 CDC immunization grantees responded to data quality-related questions in self-reported immunization registry progress reports for CY2002. Descriptive statistics for data quality-related questions were calculated using Microsoft Excel. A CDC review panel evaluated data quality improvement plans from seven CDC immunization registry sentinel sites.
RESULT:
Timeliness indicators measured that 64% of grantees establish a registry record within six weeks of patient birth and 89% of grantees receive and process vaccination records within 30 days of vaccine administration. Of the 89% (50), only 78% (39) could query their databases to validate timeliness. Of the grantees that said that they could receive and process records within 30 days, only 58% (29) could actually do that to a majority of their doses administered. Accuracy indicators measured that 88% of grantees had a data quality protocol. 59% of grantees monitored their registry’s automated de-duplication process and 42% of these grantees had a manual resolution threshold of no more than 5%. Only 16% of grantees had used the CDC’s de-duplication test cases to measure the sensitivity and specificity of their registry’s de-duplication process. For data completeness indicators, 29% of grantees had assessed the proportion of missing or nonsense data in their registry’s database. Data quality improvement plans focused on the data timeliness, completeness, and accuracy measures of the Technical Working Group’s Immunization Registry Functional Standards for the Certification of Registries.
CONCLUSION:
The majority of CDC immunization grantees are using data quality indicators to measure progress. Grantees used their current progress towards data quality indicators to base their goals and objectives for their data quality improvement plans.
LEARNING OBJECTIVES:
Identify data quality measurement indicators and examine key components of data quality improvement plans
Back to Designing Multi-Faceted Data Quality Initiatives
Back to The 2003 Immunization Registry Conference (October 27-29, 2003)