From Australian Urban Research Infrastructure Network
JSON RDF ISO19115-3 XML

PHIDU - Potentially Preventable Admissions - Chronic Conditions (LGA) 2017-2018

Created 04/05/2025

Updated 04/05/2025

JSON RDF ISO19115-3 XML

This dataset, released June 2020, contains data on the number of Potentially preventable hospitalisations - Chronic conditions, 2017/18. 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available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells.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.

Files and APIs

Tags

Additional Info

Field Value
Title PHIDU - Potentially Preventable Admissions - Chronic Conditions (LGA) 2017-2018
Language English
Licence CC-BY-NC-SA-3.0-AU
Landing Page https://devweb.dga.links.com.au/data/dataset/d0929177-a085-4bde-8a49-7c2a1edabc3e
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 {"type": "Polygon", "coordinates": [[[96.81, -43.75], [159.11, -43.75], [159.11, -9.14], [96.81, -9.14], [96.81, -43.75]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on Australian Urban Research Infrastructure Network "PHIDU - Potentially Preventable Admissions - Chronic Conditions (LGA) 2017-2018". Please visit the source to access the original metadata of the dataset:
https://data.aurin.org.au/dataset/tua-phidu-phidu-admissions-prevent-diag-chronic-lga-2017-18-lga2016

Original dataset
Dataset copies

No duplicate datasets found.