Buchanan B G, Moore J D, Forsythe D E, Carenini G, Ohlsson S, Banks G
Department of Computer Science, University of Pittsburgh, PA 15260, USA.
Artif Intell Med. 1995 Apr;7(2):117-54. doi: 10.1016/0933-3657(94)00029-r.
This paper is a report on the first phase of a long-term, interdisciplinary project whose goal is to increase the overall effectiveness of physicians' time, and thus the quality of health care, by improving the information exchange between physicians and patients in clinical settings. We are focusing on patients with long-term and chronic conditions, initially on migraine patients, who require periodic interaction with their physicians for effective management of their condition. We are using medical informatics to focus on the information needs of patients, as well as of physicians, and to address problems of information exchange. This requires understanding patients' concerns to design an appropriate system, and using state-of-the-art artificial intelligence techniques to build an interactive explanation system. In contrast to many other knowledge-based systems, our system's design is based on empirical data on actual information needs. We used ethnographic techniques to observe explanations actually given in clinic settings, and to conduct interviews with migraine sufferers and physicians. Our system has an extensive knowledge base that contains both general medical terminology and specific knowledge about migraine, such as common trigger factors and symptoms of migraine, the common therapies, and the most common effects and side effects of those therapies. The system consists of two main components: (a) an interactive history-taking module that collects information from patients prior to each visit, builds a patient model, and summarizes the patients' status for their physicians; and (b) an intelligent explanation module that produces an interactive information sheet containing explanations in everyday language that are tailored to individual patients, and responds intelligently to follow-up questions about topics covered in the information sheet.
本文是一项长期跨学科项目第一阶段的报告,该项目的目标是通过改善临床环境中医师与患者之间的信息交流,提高医生时间的整体效率,进而提升医疗保健质量。我们聚焦于患有长期和慢性疾病的患者,最初是偏头痛患者,他们需要定期与医生互动以有效管理病情。我们运用医学信息学关注患者以及医生的信息需求,并解决信息交流问题。这需要了解患者的担忧以设计合适的系统,并使用最先进的人工智能技术构建一个交互式解释系统。与许多其他基于知识的系统不同,我们系统的设计基于关于实际信息需求的实证数据。我们采用人种学技术观察临床环境中实际给出的解释,并对偏头痛患者和医生进行访谈。我们的系统有一个广泛的知识库,其中包含一般医学术语以及关于偏头痛的特定知识,如偏头痛的常见触发因素和症状、常见疗法以及这些疗法最常见的效果和副作用。该系统由两个主要组件组成:(a) 一个交互式病史采集模块,在每次就诊前从患者那里收集信息,构建患者模型,并为医生总结患者的状况;(b) 一个智能解释模块,生成一份包含用日常语言表述的、针对个体患者量身定制的解释的交互式信息表,并对关于信息表中所涵盖主题的后续问题做出智能回应。