Development of a Self-Harm Monitoring System for Victoria

Jo Robinson, Katrina Witt, Michelle Lamblin, Matthew J. Spittal, Greg Carter, Karin Verspoor, Andrew Page, Gowri Rajaram, Vlada Rozova, Nicole T. M. Hill, Jane Pirkis, Caitlin Bleeker, Alex Pleban and Jonathan C. Knott
Additional contact information
Jo Robinson: Orygen, Parkville, VIC 3052, Australia
Katrina Witt: Orygen, Parkville, VIC 3052, Australia
Michelle Lamblin: Orygen, Parkville, VIC 3052, Australia
Matthew J. Spittal: Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010 Australia
Greg Carter: Centre for Brain and Mental Health Research, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
Karin Verspoor: School of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3052, Australia
Andrew Page: Translational Health Research Institute, Western Sydney University, Campbelltown, NSW 2560, Australia
Gowri Rajaram: Orygen, Parkville, VIC 3052, Australia
Vlada Rozova: School of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3052, Australia
Nicole T. M. Hill: Orygen, Parkville, VIC 3052, Australia
Jane Pirkis: Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010 Australia
Caitlin Bleeker: Orygen, Parkville, VIC 3052, Australia
Alex Pleban: Mid-West Area Mental Health Service, Emergency Department, Sunshine Hospital, Sunshine, VIC 3021, Australia
Jonathan C. Knott: Centre for Integrated Critical Care, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia

IJERPH, 2020, vol. 17, issue 24, 1-12

Abstract: The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and internationally. The World Health Organization has recommended that member states develop self-harm surveillance systems as part of their suicide prevention efforts. This is also a priority under Australia’s Fifth National Mental Health and Suicide Prevention Plan. The aim of this paper is to describe the development of a state-based self-harm monitoring system in Victoria, Australia. In this system, data on all self-harm presentations are collected from eight hospital emergency departments in Victoria. A natural language processing classifier that uses machine learning to identify episodes of self-harm is currently being developed. This uses the free-text triage case notes, together with certain structured data fields, contained within the metadata of the incoming records. Post-processing is undertaken to identify primary mechanism of injury, substances consumed (including alcohol, illicit drugs and pharmaceutical preparations) and presence of psychiatric disorders. This system will ultimately leverage routinely collected data in combination with advanced artificial intelligence methods to support robust community-wide monitoring of self-harm. Once fully operational, this system will provide accurate and timely information on all presentations to participating emergency departments for self-harm, thereby providing a useful indicator for Australia’s suicide prevention efforts.

Keywords: self-harm; suicide; monitoring; emergency department; artificial intelligence; natural language processing; Australia (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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