Australian and New Zealand Journal of Public Health (Jun 2022)

Improving injury surveillance data quality: a study based on hospitals contributing to the Victorian Emergency Minimum Dataset

  • Dianne M. Sheppard,
  • Jane Hayman,
  • Trevor J. Allen,
  • Janneke Berecki‐Gisolf

DOI
https://doi.org/10.1111/1753-6405.13200
Journal volume & issue
Vol. 46, no. 3
pp. 401 – 406

Abstract

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Abstract 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). 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. 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. 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.

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