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

Aust N Z J Public Health. 2022 Jun;46(3):401-406. doi: 10.1111/1753-6405.13200. Epub 2022 Mar 3.

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.

Keywords: data quality; emergency department; injury prevention; injury surveillance; protocol.

MeSH terms

  • Data Accuracy
  • Data Collection
  • Emergency Service, Hospital*
  • Hospitals*
  • Humans