Karen E. Lamb , Ximena Camacho , Ping-wen Lee , Digsu N. Koye , Aneta Kotevski , Javier Haurat , Lukar E. Thornton , Maureen Turner , Julie A. Simpson , Luke Burchill
{"title":"Health map for HealthGap: Defining a geographical catchment to examine cardiovascular risk in Victoria, Australia","authors":"Karen E. Lamb , Ximena Camacho , Ping-wen Lee , Digsu N. Koye , Aneta Kotevski , Javier Haurat , Lukar E. Thornton , Maureen Turner , Julie A. Simpson , Luke Burchill","doi":"10.1016/j.healthplace.2024.103318","DOIUrl":null,"url":null,"abstract":"<div><p>The HealthGap study aimed to understand cardiovascular risk among Indigenous Australians in Victoria using linked administrative data. A key challenge was differing spatial coverages of sources: state-level data for risk factors but cardiovascular outcomes for three hospitals. Catchments were defined based on hospital postcodes to estimate denominator populations for risk modelling: first- and second-order neighbours, and spatial distribution of outcomes (‘spatial event distribution’). Catchment coverage was assessed through proportions of patients presenting to study hospitals from catchment postcodes. The spatial event distribution performed best, capturing 82% events overall (first-order:40%; second-order:64%) and 65% Indigenous (27% and 45%). No approach excluded proximal non-study hospitals. Spatial event distributions could help define denominator populations when geographic information on outcome data is available but may not avoid potential misclassification.</p></div>","PeriodicalId":49302,"journal":{"name":"Health & Place","volume":"89 ","pages":"Article 103318"},"PeriodicalIF":3.8000,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health & Place","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1353829224001461","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
The HealthGap study aimed to understand cardiovascular risk among Indigenous Australians in Victoria using linked administrative data. A key challenge was differing spatial coverages of sources: state-level data for risk factors but cardiovascular outcomes for three hospitals. Catchments were defined based on hospital postcodes to estimate denominator populations for risk modelling: first- and second-order neighbours, and spatial distribution of outcomes (‘spatial event distribution’). Catchment coverage was assessed through proportions of patients presenting to study hospitals from catchment postcodes. The spatial event distribution performed best, capturing 82% events overall (first-order:40%; second-order:64%) and 65% Indigenous (27% and 45%). No approach excluded proximal non-study hospitals. Spatial event distributions could help define denominator populations when geographic information on outcome data is available but may not avoid potential misclassification.