Literature DB >> 24179260

A systematic evaluation of different methods for calculating adolescent vaccination levels using immunization information system data.

Charitha Gowda1, Shiming Dong, Rachel C Potter, Kevin J Dombkowski, Shannon Stokley, Amanda F Dempsey.   

Abstract

OBJECTIVE: Immunization information systems (IISs) are valuable surveillance tools; however, population relocation may introduce bias when determining immunization coverage. We explored alternative methods for estimating the vaccine-eligible population when calculating adolescent immunization levels using a statewide IIS.
METHODS: We performed a retrospective analysis of the Michigan State Care Improvement Registry (MCIR) for all adolescents aged 11-18 years registered in the MCIR as of October 2010. We explored four methods for determining denominators: (1) including all adolescents with MCIR records, (2) excluding adolescents with out-of-state residence, (3) further excluding those without MCIR activity ≥ 10 years prior to the evaluation date, and (4) using a denominator based on U.S. Census data. We estimated state- and county-specific coverage levels for four adolescent vaccines.
RESULTS: We found a 20% difference in estimated vaccination coverage between the most inclusive and restrictive denominator populations. Although there was some variability among the four methods in vaccination at the state level (2%-11%), greater variation occurred at the county level (up to 21%). This variation was substantial enough to potentially impact public health assessments of immunization programs. Generally, vaccines with higher coverage levels had greater absolute variation, as did counties with smaller populations.
CONCLUSION: At the county level, using the four denominator calculation methods resulted in substantial differences in estimated adolescent immunization rates that were less apparent when aggregated at the state level. Further research is needed to ascertain the most appropriate method for estimating vaccine coverage levels using IIS data.

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Year:  2013        PMID: 24179260      PMCID: PMC3804092          DOI: 10.1177/003335491312800608

Source DB:  PubMed          Journal:  Public Health Rep        ISSN: 0033-3549            Impact factor:   2.792


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