Evidence map›Paper›PMID 33333970›Full record

ArticleInternational journal of environmental research and public health2020

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 and 4 more

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.8field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
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  4. Development and Implementation of National Real-Time Surveillance System for Suicide Attempts in Uruguay.International journal of environmental research and public health · 2025
    Article
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  11. Detection of self-harm and suicidal ideation in emergency department triage notes.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 1 country.

Jo RobinsonOrygen, Parkville, VIC 3052, Australia.ORCID 0000-0001-5652-918X
Katrina WittOrygen, Parkville, VIC 3052, Australia.
Michelle LamblinOrygen, Parkville, VIC 3052, Australia.
Matthew J SpittalCentre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010 Australia.
Greg CarterCentre for Brain and Mental Health Research, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia.
Karin VerspoorSchool of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3052, Australia.ORCID 0000-0002-8661-1544
Andrew PageTranslational Health Research Institute, Western Sydney University, Campbelltown, NSW 2560, Australia.
Gowri RajaramOrygen, Parkville, VIC 3052, Australia.
Vlada RozovaSchool of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3052, Australia.
Nicole T M HillOrygen, Parkville, VIC 3052, Australia.ORCID 0000-0003-1987-5299
Jane PirkisCentre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3010 Australia.ORCID 0000-0002-2538-4472
Caitlin BleekerOrygen, Parkville, VIC 3052, Australia.
Alex PlebanMid-West Area Mental Health Service, Emergency Department, Sunshine Hospital, Sunshine, VIC 3021, Australia.
Jonathan C KnottCentre for Integrated Critical Care, Melbourne Medical School, The University of Melbourne, Parkville, VIC 3010, Australia.
The University of Melbourne · AUCalvary Mater Newcastle Hospital · AUSunshine Hospital · AUTranslational Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceSelf-Injurious BehaviorAdolescentEmergency Service, HospitalHumansSuicide, AttemptedVictoriaartificial intelligenceAustraliaemergency departmentmonitoringnatural language processingself-harmsuicide

Identifiers

PMID33333970
PMCPMC7765445
OpenAlexW3112893300

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.