TY  - JOUR
PY  - 2022//
TI  - Improving injury surveillance data quality: a study based on hospitals contributing to the Victorian Emergency Minimum Dataset
JO  - Australian and New Zealand journal of public health
A1  - Sheppard, Dianne M.
A1  - Hayman, Jane
A1  - Allen, Trevor J.
A1  - Berecki-Gisolf, Janneke
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - OBJECTIVE: In this paper, we describe the design and baseline data of a study aimed at improving injury surveillance data quality of hospitals contributing to the Victorian Emergency Minimum Dataset (VEMD). <br><br>METHODS: The sequential study phases include a baseline analysis of data quality, direct engagement and communication with each of the emergency department (ED) hospital sites, collection of survey and interview data and ongoing monitoring. <br><br>RESULTS: In 2019/20, there were 371,683 injury-related ED presentations recorded in the VEMD. Percentage unspecified, the indicator of (poor) data quality, was lowest for 'body region' (2.7%) and 'injury type' (7.4%), and highest for 'activity when injured' (29.4%). In the latter, contributing hospitals ranged from 3.0-99.9% unspecified. The 'description of event' variable had a mean word count of 10; 16/38 hospitals had a narrative word count of <5. <br><br>CONCLUSIONS: Baseline hospital injury surveillance data vary vastly in data quality, leaving much room for improvement and justifying intervention as described. Implications for public health: Hospital engagement and feedback described in this study is expected to have a marked effect on data quality from 2021 onwards. This will ensure that Victorian injury surveillance data can fulfil their purpose to accurately inform injury prevention policy and practice.<p />  <p>Language: en</p>
LA  - en
SN  - 1326-0200
UR  - http://dx.doi.org/10.1111/1753-6405.13200
ID  - ref1
ER  -