Kuklik Nils, Stausberg Jürgen, Jöckel Karl-Heinz
Institute of Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Centre for Clinical Trials Essen (ZKSE), Institute of Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
PLoS One. 2017 Nov 2;12(11):e0187510. doi: 10.1371/journal.pone.0187510. eCollection 2017.
Adverse drug events (ADEs) during hospital stays are a significant problem of healthcare systems. Established monitoring systems lack completeness or are cost intensive. Routinely assigned International Statistical Classification of Diseases and Related Health Problems (ICD) codes could complement existing systems for ADE identification. To analyze the potential of using routine data for ADE detection, the validity of a set of ICD codes was determined focusing on hospital-acquired events.
The study utilized routine data from four German hospitals covering the years 2014 and 2015. A set of ICD, 10th Revision, German Modification (ICD-10-GM) diagnoses coded most frequently in the routine data and identified as codes indicating ADEs was analyzed. Data from psychiatric and psychotherapeutic departments were excluded. Retrospective chart review was performed to calculate positive predictive values (PPV) and sensitivity.
Of 807 reviewed ADE codes, 91.2% (95%-confidence interval: 89.0, 93.1) were identified as disease in the medical records and 65.1% (61.7, 68.3) were confirmed as ADE. For code groups being predominantly hospital-acquired, 78.5% (73.7, 82.9) were confirmed as ADE, ranging from 68.5% to 94.4% dependent on the ICD code. However, sensitivity of inpatient ADEs was relatively low. 49.7% (45.2, 54.2) of 495 identified hospital-acquired ADEs were coded as disease in the routine data, from which a subgroup of 12.1% (9.4, 15.3) was coded as drug-associated disease.
ICD codes from routine data can provide an important contribution to the development and improvement of ADE monitoring systems. Documentation quality is crucial to further increase the PPV, and actions against under-reporting of ADEs in routine data need to be taken.
住院期间的药物不良事件（ADEs）是医疗系统的一个重大问题。现有的监测系统缺乏完整性或成本高昂。常规分配的国际疾病和相关健康问题统计分类（ICD）代码可以补充现有的ADE识别系统。为了分析使用常规数据进行ADE检测的潜力，我们确定了一组ICD代码针对医院获得性事件的有效性。
本研究利用了四家德国医院2014年和2015年的常规数据。分析了一组在常规数据中编码最频繁且被确定为指示ADEs的第10版国际疾病分类德国修订版（ICD-10-GM）诊断。排除了精神科和心理治疗科的数据。进行回顾性病历审查以计算阳性预测值（PPV）和敏感性。
在807个审查的ADE代码中，91.2%（95%置信区间：89.0，93.1）在病历中被确定为疾病，65.1%（61.7，68.3）被确认为ADE。对于主要为医院获得性的代码组，78.5%（73.7，82.9）被确认为ADE，根据ICD代码的不同，范围在68.5%至94.4%之间。然而，住院患者ADEs的敏感性相对较低。在495例确定的医院获得性ADEs中，49.7%（45.2，54.2）在常规数据中被编码为疾病，其中12.1%（9.4，15.3）的亚组被编码为药物相关疾病。
常规数据中的ICD代码可为ADE监测系统的开发和改进做出重要贡献。文档质量对于进一步提高PPV至关重要，并且需要采取行动应对常规数据中ADEs报告不足的问题。
