From Australian Urban Research Infrastructure Network
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PHIDU - Admissions - Principal Diagnosis: Females (LGA) 2017-2018

Created 04/05/2025

Updated 04/05/2025

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This dataset, released June 2020, contains data relating to female hospital admissions during 2017-2018 by a principal diagnosis of Parasitic disease, cancer, Blood-organ disease, metabolic disease, nervous system disease, eye disease, ear disease, circulatory system disease, respiratory system disease, digestive system disease, skin disease, musculoskeletal disease, genitourinary system disease, perinatal condition, congenital deformations and external causes. The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Compiled by PHIDU using data from the Australian Institute of Health and Welfare, supplied on behalf of Stateand Territory health departments for 2017/18; and the average of the ABS Estimated Resident Population, 30 June 2017 and 30 June 2018. AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

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Additional Info

Field Value
Title PHIDU - Admissions - Principal Diagnosis: Females (LGA) 2017-2018
Language English
Licence Not Specified
Landing Page https://devweb.dga.links.com.au/data/dataset/71d99cb3-338e-44de-b481-15990c47ebc1
Remote Last Updated 06/03/2025
Contact Point
Torrens University Australia - Public Health Information Development Unit
test@email.loc
Reference Period 06/03/2025
Geospatial Coverage
Map data © OpenStreetMap contributors
Data Portal Australian Urban Research Infrastructure Network

Data Source

This dataset was originally found on Australian Urban Research Infrastructure Network "PHIDU - Admissions - Principal Diagnosis: Females (LGA) 2017-2018". Please visit the source to access the original metadata of the dataset:
https://data.aurin.org.au/dataset/tua-phidu-phidu-admiss-principal-diag-females-lga-2017-18-lga2016