Lenert L A, Tovar M
Division of Clinical Pharmacology, Stanford University School of Medicine, CA.
Proc Annu Symp Comput Appl Med Care. 1993:274-8.
The process of applying a practice guideline to a patient requires a great deal of clinical data. AAPT (Appropriateness-Assessment Processing from Text) is an experimental computer program that can assess the appropriateness of coronary-artery bypass grafting surgery (CABG) in patients with coronary-artery disease (CAD) and chronic stable angina from the admission summaries of those patients. The AAPT architecture combines natural-language processing (NLP) and probabilistic inference. The NLP module identifies single clinical concepts of interest in the free-text document. The probabilistic inference module, a Bayesian belief network, estimates values for variables not specifically mentioned. AAPT produces a patient's summary of CAD that is similar to a manually generated clinical summary. Work is ongoing to improve AAPT and evaluate it as a tool to assist in the dissemination of guidelines and as a tool to encourage adherence to practice guidelines.
将实践指南应用于患者的过程需要大量临床数据。AAPT（文本适用性评估处理系统）是一个实验性计算机程序，它可以根据冠心病（CAD）和慢性稳定型心绞痛患者的入院摘要，评估这些患者进行冠状动脉旁路移植术（CABG）的适用性。AAPT架构结合了自然语言处理（NLP）和概率推理。NLP模块识别自由文本文件中感兴趣的单个临床概念。概率推理模块，即贝叶斯信念网络，估计未具体提及的变量值。AAPT生成一份与人工生成的临床摘要相似的CAD患者摘要。目前正在进行改进AAPT的工作，并将其作为协助指南传播的工具以及鼓励遵循实践指南的工具进行评估。
