COMPUTER INTERPRETATION OF FREE-TEXT DATA

自由文本数据的计算机解释

• 批准号: 2237957
• 负责人: LESLIE A. LENERT
• 金额: $ 11.33万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-06-01 至 1999-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2237957
• 关键词: abstracting; artificial intelligence; automated medical record system; computer assisted diagnosis; computer assisted medical decision making; computer human interaction; coronary bypass; health care model; health care quality; human data; information retrieval; mammography; method development; statistics /biometry; thoracic radiography; vocabulary development for information system

Efforts to apply computer methods to assess and improve the quality of care in the hospital have been stymied by limited access to clinical data. Free-text data have detailed clinical descriptions of patients that would be useful in computer altering systems and computer reminder systems. However, free-text data cannot be interpreted by most clinical computer systems. In this proposal, we describe research specifically aimed at making free-text data accessible to computer-based applications for assessing and improving the quality of care. In particular the research plan focuses on the development of technologies that would allow free-text data to be used in clinical alert systems for critical test results; in reminder systems to encourage adherence to practice guidelines; and in data collection systems for severity of illness models applied in the assessment of risk adjusted outcomes. The approach described in the research plan emphasizes the development of statistical and probabilistic methods for interpretation of data derived from medical language processing systems. We will test the methods developed for language processing and interpretation developed under this proposal in 3 area: 1) the identification of concepts related to severity from the MedisGroups and the Computerized Severity Index models of patient severity of illness; 2) the identification of chest x ray reports and mammography reports with potentially malignant findings that require radiological follow-up; 3) and the automatic assessment of appropriateness of coronary artery bypass grafting (CABG) surgery from free-text descriptions of patients based on the application of a clinical practice guideline for CABG surgery.

努力应用计算机方法评估和提高质量 由于获得临床服务的机会有限，医院的护理受到阻碍 数据。 自由文本数据有患者的详细临床描述 这对于计算机更改系统和计算机提醒很有用 系统。 然而，大多数临床无法解释自由文本数据 计算机系统。 在这个提案中，我们具体描述了研究 旨在使基于计算机的应用程序可以访问自由文本数据 用于评估和提高护理质量。 特别是 研究计划的重点是开发技术，使 用于关键测试的临床警报系统的自由文本数据 结果;提醒系统鼓励坚持实践 指导方针；以及疾病严重程度模型的数据收集系统 应用于风险调整结果的评估。 方法 研究计划中描述的强调统计的发展 以及解释医学数据的概率方法 语言处理系统。 我们将测试开发的方法 根据该提案开发的语言处理和解释 3 区域：1）识别与严重性相关的概念 MedisGroups 和患者的计算机化严重程度指数模型 疾病的严重程度； 2）胸部X光报告的识别和 乳房X光检查报告有潜在的恶性结果，需要 放射学随访； 3）自动评估 冠状动脉旁路移植术（CABG）手术的适宜性 基于临床应用的患者的自由文本描述 CABG 手术实践指南。