用于识别感染性心内膜炎患者的管理数据的准确性。
Accuracy of administrative data for identification of patients with infective endocarditis.
作者信息
Tan Charlie, Hansen Mark, Cohen Gideon, Boyle Karl, Daneman Nick, Adhikari Neill K J
机构信息
Sunnybrook Research Institute, Toronto, Canada.
Division of Cardiology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.
出版信息
Int J Cardiol. 2016 Dec 1;224:162-164. doi: 10.1016/j.ijcard.2016.09.030. Epub 2016 Sep 17.
BACKGROUND
Infective endocarditis is associated with high morbidity and mortality rates that have plateaued over recent decades. Research to improve outcomes for these patients is limited by the rarity of this condition. Therefore, we sought to validate administrative database codes for the diagnosis of infective endocarditis.
METHODS
We conducted a retrospective validation study of International Classification of Diseases (ICD-10-CM) codes for infective endocarditis against clinical Duke criteria (definite and probable) at a large acute care hospital between October 1, 2013 and June 30, 2015. To identify potential cases missed by ICD-10-CM codes, we also screened the hospital's valvular heart surgery database and the microbiology laboratory database (the latter for patients with bacteremia due to organisms commonly causing endocarditis).
RESULTS
Using definite Duke criteria or probable criteria with clinical suspicion as the reference standard, the ICD-10-CM codes had a sensitivity (SN) of 0.90 (95% confidence interval (CI), 0.81-0.95), specificity (SP) of 1 (95% CI, 1-1), positive predictive value (PPV) of 0.78 (95% CI, 0.68-0.85) and negative predictive value (NPV) of 1 (95% CI, 1-1). Restricting the case definition to definite Duke criteria resulted in an increase in SN to 0.95 (95% CI, 0.86-0.99) and a decrease in PPV to 0.6 (95% CI, 0.49-0.69), with no change in specificity.
CONCLUSION
ICD-10-CM codes can accurately identify patients with infective endocarditis, and so administrative databases offer a potential means to study this infection over large jurisdictions, and thereby improve the prediction, diagnosis, treatment and prevention of this rare but serious infection.
背景
感染性心内膜炎的发病率和死亡率较高,近几十年来一直处于平稳状态。由于这种疾病较为罕见,改善这些患者治疗效果的研究受到限制。因此,我们试图验证用于诊断感染性心内膜炎的行政数据库编码。
方法
我们在一家大型急症医院对2013年10月1日至2015年6月30日期间国际疾病分类(ICD-10-CM)中感染性心内膜炎的编码与临床杜克标准(确诊和疑似)进行了一项回顾性验证研究。为了识别ICD-10-CM编码遗漏的潜在病例,我们还筛查了医院的心脏瓣膜手术数据库和微生物实验室数据库(后者针对因常见的心内膜炎病原体导致菌血症的患者)。
结果
以确诊杜克标准或伴有临床怀疑的疑似标准作为参考标准,ICD-10-CM编码的敏感度(SN)为0.90(95%置信区间(CI),0.81 - 0.95),特异度(SP)为1(95%CI,1 - 1),阳性预测值(PPV)为0.78(95%CI,0.68 - 0.85),阴性预测值(NPV)为1(95%CI,1 - 1)。将病例定义限制为确诊杜克标准后,敏感度提高至0.95(95%CI,0.86 - 0.99),阳性预测值降至0.6(95%CI,0.49 - 0.69),特异度无变化。
结论
ICD-10-CM编码能够准确识别感染性心内膜炎患者,因此行政数据库为在大范围内研究这种感染提供了一种潜在手段,从而改善对这种罕见但严重感染的预测、诊断、治疗和预防。