Literature DB >> 22811492

Using administrative medical claims data to supplement state disease registry systems for reporting zoonotic infections.

Stephen G Jones1, Steven Coulter, William Conner.   

Abstract

OBJECTIVE: To determine what, if any, opportunity exists in using administrative medical claims data for supplemental reporting to the state infectious disease registry system.
MATERIALS AND METHODS: Cases of five tick-borne (Lyme disease (LD), babesiosis, ehrlichiosis, Rocky Mountain spotted fever (RMSF), tularemia) and two mosquito-borne diseases (West Nile virus, La Crosse viral encephalitis) reported to the Tennessee Department of Health during 2000-2009 were selected for study. Similarly, medically diagnosed cases from a Tennessee-based managed care organization (MCO) claims data warehouse were extracted for the same time period. MCO and Tennessee Department of Health incidence rates were compared using a complete randomized block design within a general linear mixed model to measure potential supplemental reporting opportunity.
RESULTS: MCO LD incidence was 7.7 times higher (p<0.001) than that reported to the state, possibly indicating significant under-reporting (∼196 unreported cases per year). MCO data also suggest about 33 cases of RMSF go unreported each year in Tennessee (p<0.001). Three cases of babesiosis were discovered using claims data, a significant finding as this disease was only recently confirmed in Tennessee. DISCUSSION: Data sharing between MCOs and health departments for vaccine information already exists (eg, the Vaccine Safety Datalink Rapid Cycle Analysis project). There may be a significant opportunity in Tennessee to supplement the current passive infectious disease reporting system with administrative claims data, particularly for LD and RMSF.
CONCLUSIONS: There are limitations with administrative claims data, but health plans may help bridge data gaps and support the federal administration's vision of combining public and private data into one source.

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Mesh:

Year:  2012        PMID: 22811492      PMCID: PMC3555318          DOI: 10.1136/amiajnl-2012-000948

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


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