Dataset Information

GeoBoundaries: A global database of political administrative boundaries.

ABSTRACT: We present the geoBoundaries Global Administrative Database (geoBoundaries): an online, open license resource of the geographic boundaries of political administrative divisions (i.e., state, county). Contrasted to other resources geoBoundaries (1) provides detailed information on the legal open license for every boundary in the repository, and (2) focuses on provisioning highly precise boundary data to support accurate, replicable scientific inquiry. Further, all data is released in a structured form, allowing for the integration of geoBoundaries with large-scale computational workflows. Our database has records for every country around the world, with up to 5 levels of administrative hierarchy. The database is accessible at http://www.geoboundaries.org, and a static version is archived on the Harvard Dataverse.

SUBMITTER: Runfola D

PROVIDER: S-EPMC7182183 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

geoBoundaries: A global database of political administrative boundaries.

Runfola Daniel D Anderson Austin A Baier Heather H Crittenden Matt M Dowker Elizabeth E Fuhrig Sydney S Goodman Seth S Grimsley Grace G Layko Rachel R Melville Graham G Mulder Maddy M Oberman Rachel R Panganiban Joshua J Peck Andrew A Seitz Leigh L Shea Sylvia S Slevin Hannah H Youngerman Rebecca R Hobbs Lauren L

PloS one 20200424 4

We present the geoBoundaries Global Administrative Database (geoBoundaries): an online, open license resource of the geographic boundaries of political administrative divisions (i.e., state, county). Contrasted to other resources geoBoundaries (1) provides detailed information on the legal open license for every boundary in the repository, and (2) focuses on provisioning highly precise boundary data to support accurate, replicable scientific inquiry. Further, all data is released in a structured ...[more]

PMID: 32330167

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Project description:BackgroundAdministrative data are commonly used to study clinical outcomes in renal disease. Race is an important determinant of renal health delivery and outcomes in Canada but is not validated in most administrative data, and the correlation with census-based definitions of race is unknown.ObjectivesValidation of self-reported race (SRR) in a Canadian provincial renal administrative database (Patient Records and Outcome Management Information System [PROMIS]) and comparison with the Canadian census categories of race.DesignProspective patient survey study to validate SRR in PROMIS.SettingBritish Columbia, Canada.PatientsAdult patients registered in PROMIS.MeasurementsSurvey SRR was used as gold standard to validate SRR in PROMIS. Self-reported race in PROMIS was compared with census race categories.MethodsThis is a cross-sectional telephone survey of a random sample of all adults in PROMIS conducted between February 2016 and November 2016. Responders selected a race category from PROMIS and from the Canadian census. Sensitivity (Sn) and specificity (Sp) were calculated with 95% confidence intervals (CIs).ResultsA total of 21 039 patients met inclusion criteria, 1677 were selected for the survey and 637 participated (38% response rate). There were no differences between the PROMIS, sampled, and responder populations. PROMIS SRR had an accuracy of 95.3% (95% CI: 94.2%-97.0%) when validated against the survey SRR with Sn and Sp ≥90% in all race groups except in Aboriginals (Sn 87.5%). The positive and negative predictive values were ≥95%, except in very low and high-prevalence groups, respectively. The Canadian census had an accuracy of 95.7% (95% CI: 94.4%-97.6%) when validated against PROMIS SRR with Sn and Sp ≥90%. The results did not differ in subgroups based on age, sex, birth outside Canada, or renal group (glomerulonephritis, chronic kidney disease, hemodialysis, peritoneal dialysis, transplant recipients, or live donors).LimitationsAnalysis of minority groups and lower prevalence groups is limited by sample size. Results may not be generalizable to other administrative databases.ConclusionsWe have shown high accuracy of PROMIS SRR that validates its use in the secondary analysis of administrative data for research. There is high correlation between PROMIS and census race categories which allows linkage with other data sources that use census-based definitions of race.

Dataset Information

GeoBoundaries: A global database of political administrative boundaries.

Publications

geoBoundaries: A global database of political administrative boundaries.

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