Osler T M, Cohen M, Rogers F B, Camp L, Rutledge R, Shackford S R
Department of Surgery, College of Medicine, University of Vermont, Burlington 05405, USA.
J Trauma. 1997 Aug;43(2):253-6; discussion 256-7. doi: 10.1097/00005373-199708000-00008.
Trauma registries are an essential but expensive tool for monitoring trauma system performance. The time required to catalog patients' injuries is the source of much of this expense. Typically, 15 minutes of chart review per patient are required, which in a busy trauma center may represent 25% of a full-time employee. We hypothesized that International Classification of Disease-Ninth Revision (ICD-9) codes generated by the hospital information system (HI) would be similar to those coded by a dedicated trauma registrar (TR) and would be as accurate as TR ICD-9 codes in predicting outcome.
One thousand eight hundred twelve patients admitted to a Level I trauma center during 2 years had International Classification of Disease Injury Severity Scores (ICISS) calculated based on HI and TR ICD-9 codes. The relative predictive powers of these two ICISSs were then compared for every patient using Receiver Operator Characteristic Curve Area (ROC) and Hosmer Lemeshow Statistics.
Eighty-nine percent of patients (1,608 of 1,812) had identical HI and TR ICISSs. Eleven patients' ICISSs differed by >0.1, and only two patients' scores differed by >0.2. ICISS proved to be a powerful predictor of outcome whether derived from HI (ROC = 0.884; 95% confidence interval (CI) = 0.850-0.917) or TR (ROC = 0.872; 95% CI = 0.837-0.908). Although these predictive powers were not significantly different (p = 0.076), the trend was for HI to perform better than TR. ISS calculated for the same data set using the MacKenzie dictionary proved significantly less predictive of outcome than either ICISS (ROC(MacKenzie) = 0.843; 95% CI = 0.792-0.884; p = 0.034).
We conclude that in our hospital TR data on individual injuries can be replaced by HI data without loss of predictive power. ISS based on the MacKenzie dictionary should be abandoned because it is much less predictive of outcome than ICISS.
创伤登记是监测创伤系统性能的重要但昂贵的工具。对患者损伤进行编目的时间是这项费用的主要来源。通常,每位患者需要15分钟的病历审查时间,在繁忙的创伤中心,这可能占一名全职员工工作量的25%。我们假设医院信息系统(HI)生成的国际疾病分类第九版(ICD - 9)编码将与专门的创伤登记员(TR)编码相似,并且在预测结果方面与TR的ICD - 9编码一样准确。
在两年期间入住一级创伤中心的1812名患者,根据HI和TR的ICD - 9编码计算国际疾病分类损伤严重度评分(ICISS)。然后使用受试者操作特征曲线面积(ROC)和霍斯默 - 莱梅肖统计量比较每位患者这两种ICISS的相对预测能力。
89%的患者(1812例中的1608例)HI和TR的ICISS相同。11例患者的ICISS差异>0.1,只有2例患者的评分差异>0.2。事实证明,无论是从HI得出的ICISS(ROC = 0.884;95%置信区间(CI)= 0.850 - 0.917)还是从TR得出的ICISS(ROC = 0.872;95% CI = 0.837 - 0.908),都是结果的有力预测指标。虽然这些预测能力没有显著差异(p = 0.076),但趋势是HI的表现优于TR。使用麦肯齐字典为同一数据集计算的损伤严重度评分(ISS)在预测结果方面明显不如任何一种ICISS(ROC(麦肯齐)= 0.843;95% CI = 0.792 - 0.884;p = 0.034)。
我们得出结论,在我们医院,关于个体损伤的TR数据可以被HI数据取代,而不会损失预测能力。基于麦肯齐字典的ISS应该被摒弃,因为它在预测结果方面远不如ICISS。