Literature DB >> 20031085

Using administrative data to understand the geography of case ascertainment.

N Yiannakoulias1, D P Schopflocher, L W Svenson.   

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.

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Mesh:

Year:  2009        PMID: 20031085

Source DB:  PubMed          Journal:  Chronic Dis Can        ISSN: 0228-8699


  6 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.  Spatiotemporal patterns of childhood asthma hospitalization and utilization in Memphis Metropolitan Area from 2005 to 2015.

Authors:  Tonny J Oyana; Pradeep Podila; Jagila Minso Wesley; Slawo Lomnicki; Stephania Cormier
Journal:  J Asthma       Date:  2017-01-05       Impact factor: 2.515

3.  Developments in asthma incidence and prevalence in Alberta between 1995 and 2015.

Authors:  Ana-Maria Bosonea; Heather Sharpe; Ting Wang; Jeffrey A Bakal; A Dean Befus; Lawrence W Svenson; Harissios Vliagoftis
Journal:  Allergy Asthma Clin Immunol       Date:  2020-10-09       Impact factor: 3.406

4.  An integrated framework for the geographic surveillance of chronic disease.

Authors:  Nikolaos Yiannakoulias; Lawrence W Svenson; Donald P Schopflocher
Journal:  Int J Health Geogr       Date:  2009-11-30       Impact factor: 3.918

Review 5.  A Systematic Review of Network Studies Based on Administrative Health Data.

Authors:  Shakir Karim; Shahadat Uddin; Tasadduq Imam; Mohammad Ali Moni
Journal:  Int J Environ Res Public Health       Date:  2020-04-09       Impact factor: 3.390

6.  Comparing different supervised machine learning algorithms for disease prediction.

Authors:  Shahadat Uddin; Arif Khan; Md Ekramul Hossain; Mohammad Ali Moni
Journal:  BMC Med Inform Decis Mak       Date:  2019-12-21       Impact factor: 2.796

  6 in total

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