title: Comparing spatio-temporal clusters of arthropod-borne infections using administrative medical claims and state reported surveillance data.
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.
authors: BlueCross BlueShield of Tennessee, Dept. of Medical Informatics, Bldg. 2.1, Chattanooga, TN 37402, USA. stephen_jones@bcbst.com
authors: Stephen G
authors: SG
authors: Jones
authors: William
authors: W
authors: Conner
authors: Bo
authors: B
authors: Song
authors: David
authors: D
authors: Gordon
authors: Anand
authors: A
authors: Jayakaran
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D003625:Data Collection / Q000379:methods* / Q000706:statistics & numerical data; D018563:Disease Notification / Q000706:statistics & numerical data; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D011159:Population Surveillance; D012042:Registries; D012189:Retrospective Studies; D062211:Spatio-Temporal Analysis; D013714:Tennessee; D015047:Zoonoses / Q000453:epidemiology*