National Centre for Classification in Health, Queensland University of Technology, Brisbane, Queensland, Australia.
Inj Prev. 2009 Jun;15(3):188-96. doi: 10.1136/ip.2008.020479.
To assess extent of coder agreement for external causes of injury using ICD-10-AM for injury-related hospitalisations in Australian public hospitals.
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.
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%.
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.
评估使用 ICD-10-AM 对澳大利亚公立医院伤害相关住院患者的伤害外部原因编码的一致性程度。
从澳大利亚四个州的 50 家医院中抽取分层随机样本,获取 2002 年至 2004 年的 4850 例出院患者的随机样本。对现场病历进行审查,并对外部原因编码进行分配,编码分配过程中不参考原始编码数据。将代码一致性程度分为以下类别:块级别、3 位字符级别、4 位字符级别、5 位字符级别和完整代码级别。
在大多数机制(如交通、跌倒)中,在广泛的块级别上,超过 90%的病例存在代码一致性。在 3 位字符级别上,不一致率为 26.0%;完整外部原因代码的一致性为 67.6%。对于活动代码,在 3 位字符级别上的不一致率为 7.3%,完整活动代码的一致性为 68.0%。对于发生地点代码,在 4 位字符级别上的不一致率为 22.0%;完整地点代码的一致性为 75.4%。
完整代码的一致性为 68%,3 位字符代码的一致性为 74%,并且不同代码块、地点和活动代码的一致性程度存在差异,因此,当研究人员希望进行特定原因的趋势分析或特定原因的病例选择时,他们需要意识到自己感兴趣的特定数据的可靠性。