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Please use this identifier to cite or link to this item: http://hdl.handle.net/11054/1543
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dc.contributorAldrich, Rosemaryen_US
dc.contributorBasso, Paulen_US
dc.date.accessioned2020-07-28T10:02:45Z-
dc.date.available2020-07-28T10:02:45Z-
dc.date.issued2020-
dc.identifier.govdoc01500en_US
dc.identifier.urihttp://hdl.handle.net/11054/1543-
dc.description.provenanceSubmitted by Gemma Siemensma (gemmas@bhs.org.au) on 2020-07-28T10:02:26Z No. of bitstreams: 0en
dc.description.provenanceApproved for entry into archive by Gemma Siemensma (gemmas@bhs.org.au) on 2020-07-28T10:02:45Z (GMT) No. of bitstreams: 0en
dc.description.provenanceMade available in DSpace on 2020-07-28T10:02:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2020en
dc.titleUse of big data to derive socio-economic position metrics on admission to better target interventions to prevent hospital acquired complications.en_US
dc.typeConferenceen_US
dc.type.specifiedPaperen_US
dc.bibliographicCitation.conferencedateFebruary 13then_US
dc.bibliographicCitation.conferencenameAustralian Digital Health CRC Forumen_US
dc.bibliographicCitation.conferenceplaceMelbourne, Australiaen_US
dc.subject.healththesaurusBIG DATAen_US
dc.subject.healththesaurusDATAen_US
dc.subject.healththesaurusDATA ANALYSISen_US
dc.subject.healththesaurusHEALTH DATAen_US
dc.subject.healththesaurusHOSPITAL DATAen_US
dc.subject.healththesaurusADMISSIONSen_US
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