Estimating chlamydia screening coverage: a comparison of self-report and health care effectiveness data and information set measures.

BACKGROUND: Population-based surveys (self-report) and health insurance administrative data (Healthcare Effectiveness Data and Information Set [HEDIS]) are used to estimate chlamydia screening coverage in the United States. Estimates from these methods differ, but few studies have compared these 2 indices in the same population. METHODS: In 2010, we surveyed a random sample of women aged 18 to 25 years enrolled in a Washington State-managed care organization. Respondents were asked if they were sexually active in last year and if they tested for chlamydia in that time. We linked survey responses to administrative records of chlamydia testing and reproductive/testing services used, which comprise the HEDIS definition of the screened population and the sexually active population, respectively. We compared self-report and HEDIS using 3 outcomes: (1) sexual activity (gold standard = self-report), (2) any chlamydia screening (no gold standard), and (3) within-plan chlamydia screening (gold standard = HEDIS). RESULTS: Of 954 eligible respondents, 377 (40%) completed the survey and consented to administrative record linkage. Chlamydia screening estimates for HEDIS and self-report were 47% and 53%, respectively. The sensitivity and specificity of HEDIS to define sexually active women were 84.8% (95% confidence interval [CI], 79.6%-89.1%) and 63.5% (95% CI, 52.4%-73.7%), respectively. Forty percent of women had a chlamydia test in their administrative record, but 53% self-reported being tested for chlamydia (κ = 0.35); 19% reported out-of-plan chlamydia testing. The sensitivity of self-reported within-plan chlamydia testing was 71.3% (95% CI, 61.0%-80.1%); the specificity was 80.6% (95% CI, 72.6%-87.2%). CONCLUSIONS: The Healthcare Effectiveness Data and Information Set does not accurately identify sexually active women and may underestimate chlamydia testing coverage. Self-reported testing may not be an accurate measure of true chlamydial testing coverage.

Chlamydia screening coverage estimates derived using healthcare effectiveness data and information system procedures and indirect estimation vary substantially.

BACKGROUND: Screening coverage is an important determinant of chlamydial control program success. OBJECTIVES: The aim of this study was to compare chlamydial screening coverage estimates. METHODS: We compared 9 estimates among women aged 15 to 25 years in Washington State, 2009. Four used Healthcare Effectiveness Data and Information System (HEDIS) procedures among Group Health enrollees. Separate HEDIS estimates assessed all enrollees and the subset of women who used services; for each group, separate estimates defined the sexually active population using HEDIS methods or National Survey of Family Growth (NSFG) data. Three indirect screening estimates used census and NSFG data to define the population's size and derived the number of tests performed by dividing the number of reported cases by test positivity defined using data from different laboratories, adjusted for repeat testing. A fourth indirect estimate was adjusted for reason for testing. A direct-indirect estimate combined data on the number of tests performed in reporting laboratories and an indirect estimate of tests performed elsewhere. RESULTS: Healthcare Effectiveness Data and Information System procedures and NSFG data yielded similar estimates of the percentage of women who were sexually active (60% vs. 61%). Screening coverage estimated by HEDIS was higher among Group Health users (43.6%) than among all enrollees (34.2%). Indirect screening coverage estimates varied from 46.4% to 68.7%. The direct-indirect estimate, which included a direct measure of the number of tests performed to identify 52% of reported cases, was 57.6%. CONCLUSIONS: Most sexually active women aged 15 to 25 years in Washington State were screened for chlamydia in 2009. Healthcare Effectiveness Data and Information System methods may underestimate screening coverage. Health departments can derive population-based coverage estimates using data from large laboratories.