Division of Infectious Diseases, College of Medicine, The Ohio State University, 410 West 10th Ave., Columbus, OH 43210, USA.
Am J Infect Control. 2010 Nov;38(9):701-5. doi: 10.1016/j.ajic.2010.03.015. Epub 2010 Jul 1.
Public reporting and reduced Medicare payments because of health care-associated infections have resulted in the consideration of administrative discharge codes as markers of health care-associated infections. This study aims to determine whether specific secondary ICD-9-CM infection codes linked to cases from a large data set of surgical procedures are predictors of surgical site infections (SSIs).
All patients undergoing 1 of 9 surgical procedures from January 1, 2005, through December 31, 2005, at a large academic medical center and who were assigned a secondary ICD-9-CM infection code at discharge were eligible for study inclusion. All cases were reviewed to determine the presence of SSIs. Logistic regression was used to determine which secondary codes were predictors of SSIs.
Among 75 secondary infection codes applied at discharge to 454 patients, only 1 code (998.59) appeared to be reliably associated with SSIs. Two other general infection codes (996.63 and 996.67) and 1 specific infection code (320.3) may also have utility.
Administrative coding data do not perform well to identify SSIs. Some general secondary infection codes, however, may have the potential to be utilized in screening algorithms of electronic health data to assist in SSI surveillance.
由于与医疗保健相关的感染而导致的公共报告和医疗保险支付减少,使得人们开始考虑将行政出院代码作为与医疗保健相关的感染的标志物。本研究旨在确定与大型手术程序数据集相关的特定次要 ICD-9-CM 感染代码是否可预测手术部位感染 (SSI)。
从 2005 年 1 月 1 日至 2005 年 12 月 31 日,在一家大型学术医疗中心接受 9 种手术之一的所有患者,并且在出院时被分配了次要 ICD-9-CM 感染代码,都有资格进行研究。所有病例均进行了审查,以确定是否存在 SSI。使用逻辑回归确定哪些次要代码是 SSI 的预测因素。
在出院时应用于 454 名患者的 75 种次要感染代码中,只有 1 种代码(998.59)似乎与 SSI 可靠相关。另外两个一般感染代码(996.63 和 996.67)和 1 个特定感染代码(320.3)也可能具有实用性。
行政编码数据在识别 SSI 方面表现不佳。但是,某些一般的次要感染代码可能具有在电子健康数据的筛选算法中使用的潜力,以协助 SSI 监测。