title: Using administrative data to understand the geography of case ascertainment.
abstract: We examined the geographic variability of information generated from different case definitions of childhood asthma derived from administrative health data used in Alberta, Canada. Our objective was to determine if analyses based on different case ascertainment algorithms identify geographic clusters in the same region of the study area. Our study group was based on a closed cohort of asthmatic children born in 1988. We used a spatial scan statistic to identify variations in the approximate location of geographic clusters of asthma based on different case definitions. Our results indicate that the geographic patterns are not greatly affected by the case ascertainment algorithm or the source of data. For example, asthmatics identified from medical claims data showed similar clustering to asthmatics defined through hospitalization and emergency department data. However, estimates of prevalence and incidence require careful consideration and validation against other data sources.
authors.affiliation: School of Geography and Earth Sciences, McMaster University, Hamilton, ON. yiannan@mcmaster.ca
authors.forename: N
authors.initials: N
authors.lastname: Yiannakoulias
authors.forename: D P
authors.initials: DP
authors.lastname: Schopflocher
authors.forename: L W
authors.initials: LW
authors.lastname: Svenson
mesh_terms: D000416:Alberta / Q000453:epidemiology; D000465:Algorithms; D001249:Asthma / Q000175:diagnosis / Q000453:epidemiology*; D002648:Child; D003625:Data Collection / Q000379:methods*; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D038801:International Classification of Diseases; D008331:Management Information Systems / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data; D011159:Population Surveillance / Q000379:methods*; D015995:Prevalence; D012111:Residence Characteristics; D012306:Risk; D017062:Small-Area Analysis