Evans R Scott, Lloyd James F, Aston Valerie T, Woller Scott C, Tripp Jacob S, Elliott C Greg, Stevens Scott M
Medical Informatics, Intermountain Healthcare;
AMIA Annu Symp Proc. 2010 Nov 13;2010:217-21.
Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), may be the number one preventable cause of death associated with hospitalization. Numerous evidence-based guidelines for effective VTE prophylaxis therapy exist. However, underuse is common due to the difficulty in integrating VTE risk assessment into routine patient care. Previous studies utilizing computer decision support to identify high-risk patients report improved use of prophylaxis therapy and reduced VTE. However, those studies did not report the sensitivity, specificity or positive predictive value of their methods to identify patients at high risk. We report an evaluation of a computerized tool to identify patients at high risk for VTE that found a sensitivity of 98% and positive predictive value of 99%. Another computer program used to detect VTE had a sensitivity of 92%, specificity of 99% and a positive predictive value of 97% to identify DVT and a sensitivity of 100%, specificity of 98% and positive predictive value of 89% to identify PE. These tools were found to provide a dependable method to identify patients at high risk for and with VTE.
静脉血栓栓塞症（VTE），包括深静脉血栓形成（DVT）和肺栓塞（PE），可能是与住院相关的头号可预防死亡原因。现有众多基于证据的有效VTE预防治疗指南。然而，由于难以将VTE风险评估纳入常规患者护理，预防措施未得到充分利用的情况很常见。以往利用计算机决策支持来识别高危患者的研究报告称，预防治疗的使用有所增加，VTE发生率降低。然而，这些研究并未报告其识别高危患者方法的敏感性、特异性或阳性预测值。我们报告了一项对用于识别VTE高危患者的计算机化工具的评估，该工具的敏感性为98%，阳性预测值为99%。另一个用于检测VTE的计算机程序在识别DVT方面的敏感性为92%，特异性为99%，阳性预测值为97%；在识别PE方面的敏感性为100%，特异性为98%，阳性预测值为89%。这些工具被发现为识别VTE高危患者和VTE患者提供了一种可靠的方法。
