Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands; Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam The Netherlands.
Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands.
J Clin Epidemiol. 2014 Aug;67(8):921-31. doi: 10.1016/j.jclinepi.2014.02.020. Epub 2014 May 1.
OBJECTIVE: To evaluate the accuracy of disease codes and free text in identifying upper gastrointestinal bleeding (UGIB) from electronic health-care records (EHRs). STUDY DESIGN AND SETTING: We conducted a validation study in four European electronic health-care record (EHR) databases such as Integrated Primary Care Information (IPCI), Health Search/CSD Patient Database (HSD), ARS, and Aarhus, in which we identified UGIB cases using free text or disease codes: (1) International Classification of Disease (ICD)-9 (HSD, ARS); (2) ICD-10 (Aarhus); and (3) International Classification of Primary Care (ICPC) (IPCI). From each database, we randomly selected and manually reviewed 200 cases to calculate positive predictive values (PPVs). We employed different case definitions to assess the effect of outcome misclassification on estimation of risk of drug-related UGIB. RESULTS: PPV was 22% [95% confidence interval (CI): 16, 28] and 21% (95% CI: 16, 28) in IPCI for free text and ICPC codes, respectively. PPV was 91% (95% CI: 86, 95) for ICD-9 codes and 47% (95% CI: 35, 59) for free text in HSD. PPV for ICD-9 codes in ARS was 72% (95% CI: 65, 78) and 77% (95% CI: 69, 83) for ICD-10 codes (Aarhus). More specific definitions did not have significant impact on risk estimation of drug-related UGIB, except for wider CIs. CONCLUSIONS: ICD-9-CM and ICD-10 disease codes have good PPV in identifying UGIB from EHR; less granular terminology (ICPC) may require additional strategies. Use of more specific UGIB definitions affects precision, but not magnitude, of risk estimates.
目的:评估电子健康记录(EHR)中疾病代码和自由文本在识别上消化道出血(UGIB)中的准确性。
研究设计和设置:我们在四个欧洲电子健康记录(EHR)数据库中进行了一项验证研究,包括综合初级保健信息(IPCI)、健康搜索/CSD 患者数据库(HSD)、ARS 和奥胡斯,我们使用自由文本或疾病代码来识别 UGIB 病例:(1)国际疾病分类(ICD)第 9 版(HSD、ARS);(2)ICD-10(奥胡斯);和(3)国际初级保健分类(ICPC)(IPCI)。从每个数据库中,我们随机选择并手动审查了 200 例病例,以计算阳性预测值(PPV)。我们采用了不同的病例定义来评估结局误诊对药物相关 UGIB 风险估计的影响。
结果:IPCI 中自由文本和 ICPC 代码的 PPV 分别为 22%(95%置信区间[CI]:16,28)和 21%(95% CI:16,28)。HSD 中 ICD-9 代码的 PPV 为 91%(95% CI:86,95),而自由文本的 PPV 为 47%(95% CI:35,59)。ARS 中 ICD-9 代码的 PPV 为 72%(95% CI:65,78),ICD-10 代码(奥胡斯)的 PPV 为 77%(95% CI:69,83)。更具体的定义除了 CIs 更宽之外,对药物相关 UGIB 风险估计没有显著影响。
结论:ICD-9-CM 和 ICD-10 疾病代码在识别 EHR 中的 UGIB 方面具有良好的 PPV;粒度较粗的术语(ICPC)可能需要额外的策略。使用更具体的 UGIB 定义会影响风险估计的精度,但不会影响幅度。
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