MOMENT (Monitoring for Outpatient Medication Effects and New Toxicities) in TIME

描述（由申请人提供）： TIME项目中的MOMENT（门诊药物效应和新毒性监测）将通过开发复杂的文本挖掘和数据提取工具来扩展正在进行的TIME（使用证据进行住院患者监测的工具）安全和适当的测试补助金#5 R 01 LM 007995 -03，以检查急诊和医院护理患者的药物不良反应。 使用通过自然语言处理增强的基于UML的概念标识符，MOMENT项目将检测：（a）可能与药物相关的个体临床表现（症状和体检结果）;（B）临床综合征（例如，肝毒性、肌病、肾功能不全、葡萄糖耐受不良）;和（c）和临床疾病（如肼苯哒嗪或普鲁卡因胺诱导的系统性狼疮，或与罗非考昔相关的急性心肌梗塞）。拟议工作的创新方面包括使用先进的自然语言处理技术从患者病史和体检记录以及辅助测试报告中抽象出代表潜在药物作用的概念，结合基于证据的模板和诊断算法来检测药物毒性的复杂模式（例如，肝细胞损伤、肺纤维化或急性冠状动脉综合征）、用于确定大人群中药物作用的先进统计方法以及包含超过100，000名患者数据的临床数据库的利用。 公开声明 MOMENT项目（门诊药物效应和新毒性监测）将证明将信息学应用（电子病历系统和护理提供者订单输入（CPOE）系统）结合起来的可行性，这些应用在许多医疗机构中越来越多，以创建一个先进的药物不良反应检测和监测系统。该项目将开发工具和算法，以检测可能表明药物引起的损伤的患者症状，体检体征，测试结果和医学诊断。

DESCRIPTION (provided by applicant): The MOMENT (Monitoring for Outpatient Medication Effects and New Toxicities) in TIME project will extend the in-progress TIME (Tools for Inpatient Monitoring using Evidence) for Safe and Appropriate Testing grant, #5 R01 LM007995-03, by developing sophisticated text-mining and data extraction tools to examine adverse drug effects in patients presenting for emergency and hospital care. Using a UMLS-based concept identifier enhanced with natural language processing, the MOMENT project will detect: (a) individual clinical manifestations (symptoms and physical exam findings) that are potentially drug related; (b) clinical syndromes (e.g., hepatoxicity, myopathy, renal insufficiency, glucose intolerance); and, (c) and clinical diseases (such as systemic lupus induced by hydralazine or procainamide, or acute myocardial infarction associated with rofecoxib). Innovative aspects of the proposed work include use of advanced natural language processing techniques to abstract concepts representing potential drug effects from patient history and physical examination records and ancillary test reports, the combination of evidence based templates and diagnostic algorithms to detect complex patterns of drug toxicity (e.g., hepatocelluar damage, pulmonary fibrosis, or acute coronary syndrome), advanced statistical methods for determining medication effects in large populations, and utilization of a clinical database containing data on more than 100,000 patients. Public Statement The MOMENT project (Monitoring for Outpatient Medication Effects and New Toxicities) will demonstrate the feasibility of combining informatics applications increasingly present in many healthcare institutions - electronic medical record systems and care provider order entry (CPOE) systems - to create an advanced detection and monitoring system for adverse medication effects. The project will develop tools and algorithms to detect the patient symptoms, physical exam signs, test results, and medical diagnoses that may indicate drug-induced injury.