Evidence map›Paper›PMID 29273670›Full record

ArticleBMJ open2017

Using a retrospective cross-sectional study to analyse unintentional fatal drowning in Australia: ICD-10 coding-based methodologies verses actual deaths.

Amy E Peden, Richard C Franklin, Alison J Mahony, Justin Scarr, Paul D Barnsley

Abstract read
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

42 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Pre-Existing Medical Conditions: A Systematic Literature Review of a Silent Contributor to Adult Drowning.International journal of environmental research and public health · 2022
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  11. First global status report on drowning prevention identifies opportunities to scale up efforts.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2026
    Article
  12. Burden of unintentional drowning in Indonesia: insights from the Global Burden of Disease Study 2019.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2025
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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

5 authors.

Amy E PedenRoyal Life Saving Society - Australia, Broadway, Australia.ORCID 0000-0002-6424-1511
Richard C FranklinRoyal Life Saving Society - Australia, Broadway, Australia.
Alison J MahonyRoyal Life Saving Society - Australia, Broadway, Australia.
Justin ScarrRoyal Life Saving Society - Australia, Broadway, Australia.
Paul D BarnsleyRoyal Life Saving Society - Australia, Broadway, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesFatal drowning estimates using a single underlying cause of death (UCoD) may under-represent the number of drowning deaths. This study explores how data vary by International Classification of Diseases (ICD)-10 coding combinations and the use of multiple underlying causes of death using a national register of drowning deaths.

designAn analysis of ICD-10 external cause codes of unintentional drowning deaths for the period 2007-2011 as extracted from an Australian total population unintentional drowning database developed by Royal Life Saving Society-Australia (the Database). The study analysed results against three reporting methodologies: primary drowning codes (W65-74), drowning-related codes, plus cases where drowning was identified but not the UCoD.

settingAustralia, 2007-2011.

participantsUnintentional fatal drowning cases.

resultsThe Database recorded 1428 drowning deaths. 866 (60.6%) had an UCoD of W65-74 (accidental drowning), 249 (17.2%) cases had an UCoD of either T75.1 (0.2%), V90 (5.5%), V92 (3.5%), X38 (2.4%) or Y21 (5.9%) and 53 (3.7%) lacked ICD coding. Children (aged 0-17 years) were closely aligned (73.9%); however, watercraft (29.2%) and non-aquatic transport (13.0%) were not. When the UCoD and all subsequent causes are used, 67.2% of cases include W65-74 codes. 91.6% of all cases had a drowning code (T75.1, V90, V92, W65-74, X38 and Y21) at any level.

conclusionDefining drowning with the codes W65-74 and using only the UCoD captures 61% of all drowning deaths in Australia. This is unevenly distributed with adults, watercraft and non-aquatic transport-related drowning deaths under-represented. Using a wider inclusion of ICD codes, which are drowning-related and multiple causes of death minimises this under-representation. A narrow approach to counting drowning deaths will negatively impact the design of policy, advocacy and programme planning for prevention.

Indexed as

AdolescentAdultAge DistributionAustraliaCause of DeathChildChild, PreschoolClinical CodingCross-Sectional StudiesDatabases, FactualDrowningFemaleHumansInfantInfant, NewbornInternational Classification of Diseasesdrowningepidemiologyglobal burden of diseaseinjuryinternational classification of diseases (ICD)methodologypublic health

Identifiers

PMID29273670
PMCPMC5778319

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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.