评估ICD-10管理数据在合并症编码中的有效性。

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES
Jie Pan, Seungwon Lee, Cheligeer Cheligeer, Bing Li, Guosong Wu, Catherine A Eastwood, Yuan Xu, Hude Quan
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引用次数: 0

摘要

目的:行政数据通常用于了解慢性疾病的流行情况并支持卫生信息研究。本研究评估了国际疾病分类第十版(ICD-10)管理数据中编码合并症的有效性。方法:我们分析了加拿大阿尔伯塔省的三个图表回顾队列(2003年4008例,2015年3045例,2022年9024例)。护士审查员使用一致的方案评估了17种临床状况的存在。这些评价与使用唯一患者标识符的管理数据相关联。我们以图表回顾数据作为参考标准,比较ICD-10编码合并症的准确性。结果:我们的研究结果显示,图表回顾与ICD-10对这17种疾病的患病率的平均差异在2003年为2.1%,2015年为7.6%,2022年为6.3%。一些情况相对稳定,如糖尿病(1.9%,2.1%和1.1%)和转移性癌症(0.3%,1.1%和0.4%)。对于这17种情况,2003年的敏感性为39.6-85.1%,2015年为1.3%-85.2%,2022年为3.0-89.7%。ICD-10使用合并症预测住院死亡率的c统计量在2003年为0.84,2015年为0.81,2022年为0.78。讨论:编码不足可能主要是由于医院病人数量的增加和分配给编码专家的时间有限。有可能开发基于电子健康记录的人工智能方法,以支持编码实践并提高数据质量。结论:20年来,合并症的发生率越来越低。ICD-10的有效性有所下降,但在编码要求的某些条件下保持相对稳定。下编码对住院死亡率预测影响最小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the validity of ICD-10 administrative data in coding comorbidities.

Objectives: Administrative data are commonly used to inform chronic disease prevalence and support health informatic research. This study assessed the validity of coding comorbidities in the International Classification of Diseases, 10th Revision (ICD-10) administrative data.

Methods: We analysed three chart review cohorts (4008 patients in 2003, 3045 in 2015 and 9024 in 2022) in Alberta, Canada. Nurse reviewers assessed the presence of 17 clinical conditions using a consistent protocol. The reviews were linked with administrative data using unique patient identifiers. We compared the accuracy in coding comorbidity by ICD-10, using chart review data as the reference standard.

Results: Our findings showed that the mean difference in prevalence between chart reviews and ICD-10 for these 17 conditions was 2.1% in 2003, 7.6% in 2015 and 6.3% in 2022. Some conditions were relatively stable, such as diabetes (1.9%, 2.1% and 1.1%) and metastatic cancer (0.3%, 1.1% and 0.4%). For these 17 conditions, the sensitivity ranged from 39.6-85.1% in 2003, 1.3%-85.2% in 2015 and 3.0-89.7% in 2022. The C-statistics for predicting in-hospital mortality using comorbidities by ICD-10 were 0.84 in 2003, 0.81 in 2015 and 0.78 in 2022.

Discussion: The undercoding could be primarily due to the increase in hospital patient volumes and the limited time allocated to coding specialists. There is the potential to develop artificial intelligence methods based on electronic health records to support coding practices and improve data quality.

Conclusion: Comorbidities were increasingly undercoded over 20 years. The validity of ICD-10 decreased but remained relatively stable for certain conditions mandated for coding. The undercoding exerted minimal impact on in-hospital mortality prediction.

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来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
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