2019
DOI: 10.1111/1742-6723.13266
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Driving change: A partnership study protocol using shared emergency department data to reduce alcohol‐related harm

Abstract: Background: Sharing anonymised ED data with community agencies to reduce alcohol-related injury and assaults has been found effective in the UK. This protocol document outlines the design of an Australian multi-site trial using shared, anonymised ED data to reduce alcoholrelated harm.

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Cited by 9 publications
(17 citation statements)
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References 23 publications
(30 reference statements)
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“…This cross-sectional, multi-centre study is the first of its kind in Australia to systematically document alcohol consumption in the 12 hours prior among those attending an ED, 16 and the first study to document the ICD-…”
Section: Discussionmentioning
confidence: 99%
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“…This cross-sectional, multi-centre study is the first of its kind in Australia to systematically document alcohol consumption in the 12 hours prior among those attending an ED, 16 and the first study to document the ICD-…”
Section: Discussionmentioning
confidence: 99%
“…Data collected included age, sex, clinical manifestations, hospital geographical location, principal diagnosis and ICD-10-AM code, with four additional questions covering drinking in the 12 hours prior to attendance, typical alcohol consumption level in a drinking session, location where most alcohol was purchased and the location of the last drink. 16 Alcohol-related data were collected specifically as a part of the project. Data for the study were extracted from July 2018 to June 2019 (which was the first full 12 months available where all sites collected data).…”
Section: Methodsmentioning
confidence: 99%
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“…Furthermore, our measures relied on coding conducted as part of administrative processes within hospitals not designed for research. Previous analyses have highlighted the weaknesses of alcohol measures in hospital systems [16,35] and we have relied on time and condition-based proxy measures to attempt to capture key trends [17,36]. These challenges exist to varying degrees for all our outcome variables, biasing all of our estimates of policy impact towards the null by increasing the noise in the data and making it harder to detect any specific impact on injuries and other outcomes stemming from licensed premises and entertainment precincts.…”
Section: Limitationsmentioning
confidence: 99%