Literature DB >> 22749206

Comparing spatio-temporal clusters of arthropod-borne infections using administrative medical claims and state reported surveillance data.

Stephen G Jones1, William Conner, Bo Song, David Gordon, Anand Jayakaran.   

Abstract

Considered separately, notifiable disease registries and medical claims data have certain advantages (e.g., consistent case definitions and electronic records, respectively) and limitations (e.g., incomplete reporting and coding errors, respectively) within disease outbreak research. Combined however, these data could provide a more complete source of information. Using a retrospective space-time permutation scan statistic, zoonotic case information from a state registry system (TDH) was compared with administrative medical claims information from a managed care organization (MCO) to examine how data sources differ. Study observations included case information for four tick-borne (Lyme disease, ehrlichiosis, Rocky Mountain spotted fever, tularemia) and two mosquito-borne diseases (West Nile virus, La Crosse viral encephalitis) occurring in Tennessee. One hundred and three clusters were detected, of which nine were significant (P<0.05). Considering only significant clusters, no spatial or temporal overlapping between data sources occurred. In conclusion, data integration efforts and data limitations should be considered to provide more comprehensive case information.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22749206     DOI: 10.1016/j.sste.2012.01.001

Source DB:  PubMed          Journal:  Spat Spatiotemporal Epidemiol        ISSN: 1877-5845


  3 in total

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

Authors:  Stephen G Jones; Steven Coulter; William Conner
Journal:  J Am Med Inform Assoc       Date:  2012-07-18       Impact factor: 4.497

2.  Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004-2014: flexibly shaped scan statistics.

Authors:  Xianyan Tang; Alan Geater; Edward McNeil; Qiuyun Deng; Aihu Dong; Ge Zhong
Journal:  BMC Infect Dis       Date:  2017-04-04       Impact factor: 3.090

3.  Influence of spatial resolution on space-time disease cluster detection.

Authors:  Stephen G Jones; Martin Kulldorff
Journal:  PLoS One       Date:  2012-10-24       Impact factor: 3.240

  3 in total

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