@article{ref1,
title="How representative is the Victorian Emergency Minimum Dataset (VEMD) for population-based injury surveillance in Victoria? A retrospective observational study of administrative healthcare data",
journal="BMJ open",
year="2022",
author="Rezaei-Darzi, Ehsan and Berecki-Gisolf, Janneke and Fernando, Dasamal Tharanga",
volume="12",
number="12",
pages="e063115-e063115",
abstract="OBJECTIVE: The Victorian Emergency Minimum Dataset (VEMD) is a key data resource for injury surveillance. The VEMD collects emergency department data from 39 public hospitals across Victoria; however, rural emergency care services are not well captured. The aim of this study is to determine the representativeness of the VEMD for injury surveillance. <br><br>DESIGN: A retrospective observational study of administrative healthcare data.   SETTING AND PARTICIPANTS: Injury admissions in 2014/2015-2018/2019 were extracted from the Victorian Admitted Episodes Dataset (VAED) which captures all Victorian hospital admissions; only cases that arrived through a hospital's emergency department (ED) were included. Each admission was categorised as taking place in a VEMD-contributing versus a non-VEMD hospital. <br><br>RESULTS: There were 535 477 incident injury admissions in the study period, of which 517 207 (96.6%) were admitted to a VEMD contributing hospital. Male gender (OR 1.13 (95% CI 1.10 to 1.17)) and young age (age 0-14 vs 45-54 years, OR 4.68 (95% CI 3.52 to 6.21)) were associated with VEMD participating (vs non-VEMD-participating) hospitals. Residing in regional/rural areas was negatively associated with VEMD participating (vs non-VEMD participating) hospitals (OR=0.11 (95% CI 0.10 to 0.11)). Intentional injury (assault and self-harm) was also associated with VEMD participation. <br><br>CONCLUSIONS: VEMD representativeness is largely consistent across the whole of Victoria, but varies vastly by region, with substantial under-representation of some areas of Victoria. By comparison, for injury surveillance, regional rates are more reliable when based on the VAED. For local ED-presentation rates, the bias analysis results can be used to create weights, as a temporary solution until rural emergency services injury data is systematically collected and included in state-wide injury surveillance databases.<p /> <p>Language: en</p>",
language="en",
issn="2044-6055",
doi="10.1136/bmjopen-2022-063115",
url="http://dx.doi.org/10.1136/bmjopen-2022-063115"
}