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Methodologic issues
Causes of injuries resulting in hospitalisation in Australia: assessing coder agreement on external causes
  1. K McKenzie1,
  2. E L Enraght-Moony1,
  3. G Waller1,
  4. S M Walker1,
  5. J E Harrison2,
  6. R J McClure3
  1. 1
    National Centre for Classification in Health, Queensland University of Technology, Brisbane, Queensland, Australia
  2. 2
    Research Centre for Injury Studies, Flinders University, Adelaide, South Australia, Australia
  3. 3
    Monash University Accident Research Centre, Monash University, Melbourne, Victoria, Australia
  1. Dr K McKenzie, National Centre for Classification in Health, School of Public Health, Queensland University of Technology, Kelvin Grove 4059, Queensland, Australia; k.mckenzie{at}qut.edu.au

Abstract

Objective: To assess extent of coder agreement for external causes of injury using ICD-10-AM for injury-related hospitalisations in Australian public hospitals.

Methods: A random sample of 4850 discharges from 2002 to 2004 was obtained from a stratified random sample of 50 hospitals across four states in Australia. On-site medical record reviews were conducted and external cause codes were assigned blinded to the original coded data. Code agreement levels were grouped into the following agreement categories: block level, 3-character level, 4-character level, 5th-character level, and complete code level.

Results: At a broad block level, code agreement was found in over 90% of cases for most mechanisms (eg, transport, fall). Percentage disagreement was 26.0% at the 3-character level; agreement for the complete external cause code was 67.6%. For activity codes, the percentage of disagreement at the 3-character level was 7.3% and agreement for the complete activity code was 68.0%. For place of occurrence codes, the percentage of disagreement at the 4-character level was 22.0%; agreement for the complete place code was 75.4%.

Conclusions: With 68% agreement for complete codes and 74% agreement for 3-character codes, as well as variability in agreement levels across different code blocks, place and activity codes, researchers need to be aware of the reliability of their specific data of interest when they wish to undertake trend analyses or case selection for specific causes of interest.

https://doi.org/10.1136/ip.2008.020479

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    Footnotes

    • Funding: This research is funded by an Australian Research Council Linkage Project grant, Injury Prevention and Control Australia, the Victorian Department of Human Services, and the Queensland Health Information Centre.

    • Competing interests: None.

    • Contributors: KMcK contributed to the conceptual design of the manuscript, and was responsible for conducting the literature review, writing the first draft of the manuscript, compiling all authors’ responses, and preparing the final version of the manuscript. ELE-M contributed to the conceptual design of the manuscript, assisted with the literature review, and reviewed and commented on each draft of the manuscript. GW contributed to the conceptual design of the manuscript, conducted the majority of the medical record reviews and data collection, provided context to the manuscript in terms of clinical coding processes, and reviewed and commented on each draft of the manuscript. SMW contributed to the conceptual design of the manuscript, provided context to the manuscript in terms of clinical coding processes, and reviewed and commented on each draft of the manuscript. JEH contributed to the conceptual design of the manuscript, and provided context to the manuscript in terms of injury surveillance implications. RJMcC contributed to the conceptual design of the manuscript, provided context to the manuscript in terms of injury prevention implications, and reviewed and commented on each draft of the manuscript.