Background:
The Region V Infertility Prevention Project (RVIPP) aims to reduce the prevalence of chlamydia infection by screening and treating at-risk individuals. High quality and complete IPP data are essential to determine what populations to screen, for program evaluation, and for resource allocation. Analysis of RVIPP data during 2002 to 2006 demonstrated a significant improvement in the rate of missing/unknown key data elements.

Objective:
To identify strategies that will improve IPP data quality and completeness in order to target screening and resources more effectively.

Method:
RVIPP data from 2002 to 2006 were analyzed by state and key demographic element to determine the percent of missing/unknown data and the percent change of missing/unknown data over time. States with the lowest percent of missing/unknown demographic data were contacted to determine best practices.

Result:
An analysis of RVIPP screening and demographic data from 2002 to 2006 showed that while annual screening tests increased 1.6% (532,033 to 540,769), missing/unknown key data elements decreased by 37% (215,051 to 135,541): sex (-59.7%), age (-41.6%), race (-49.2%), and ethnicity (-28.7%). Upon further analysis, two states, Illinois (0.6%) and Ohio (0.1%), were identified as having the lowest percent of missing/unknown data elements. These two states used active follow-up as a quality assurance tool to identify and decrease missing/unknown data elements.

Conclusion:
Conducting periodic QA review and implementing active follow-up of missing/unknown key data elements can improve data quality and completeness enabling screening and resources to be targeted more effectively.

Implications:
During times of limited funding, it is imperative that resources are directed toward screening those individuals at greatest risk for chlamydia infection. By collecting accurate and complete data, decisions regarding how to best use these limited resources can be made more precisely and have a greater impact.