Terminological Systems for Representing Patient Status

描述（由申请人提供）： 医疗保健是一个深刻的信息密集型产业，存在于一个 环境中，开发和部署基于计算机的 支持信息处理的技术正在以一种 前所未有的步伐。不幸的是，缺乏一致性和可比性 术语数据仍然是充分实现 这些新技术的潜力。概念术语 系统提供解决方案，强调基于概念的术语方法 而不是基于词汇的方法。 本提案的总体重点是基本概念系统， 的术语数据的机器处理所需的 主题字段为“患者状态”。我们使用患者状态一词来指 身体、社会和认知功能的维度 健康，疾病和一个人生活的环境。的 该项目的具体目标是：1）确定和评估术语， 与患者状态相关的术语系统，2）描述术语 系统具体到患者状态的主题领域进行识别和评估， 以及3）将正式表示患者状态的术语系统与 参考术语和信息模型。为了实现这一目标，我们将 利用马约诊所近十年的工作， 基于术语系统，支持临床 记录，以及大量的试点工作，具体到索引的领域 病人状况 与强调学科和专业的术语发展相反， 在建模活动中，我们采用了"自下而上"的 视角，强调患者状态的学科领域视角 通过丰富的文本语料库的组装。在这项研究的最后，我们 打算为这一领域提供可扩展资源。这项工作并 不重复术语和信息建模工作中的任何现有工作， 相当广泛地建立在现有工作的基础上。

DESCRIPTION (provided by applicant): Health care is a profoundly information intensive industry, existing in an environment where the development and deployment of computer based technologies to support information processing is proceeding at an unprecedented pace. Unfortunately, the lack of consistent and comparable terminological data remains a significant barrier to fully realizing the potential of these new technologies. Concept based terminologies terminology systems offer solutions, emphasizing concept based approaches to terminology rather than lexical based approaches. The overall focus of this proposal is on the underlying concept systems that are required for the machine processing of terminological data related to the subject field of "patient status". We use the term patient status to refer to the dimensions of physical, social, and cognitive functioning within the context of health, disease, and the environment in which one lives. The specific aims of this project are to 1) identify and evaluate terms and terminology systems relevant to patient status, 2) describe a terminology system specific to the subject field of patient status identify and evaluate, and 3) compare a terminology system to formally represent patient status to reference terminology and information models. In accomplishing this, we will leverage nearly a decade of work at the Mayo Clinic that is emphasized concept based terminology systems in support of automated indexing of clinical records, and considerable pilot work specific to indexing the domain of patient status. In contrast to terminology developments that have emphasized disciplinary and business perspectives in modeling initiatives, we are employing a "bottom-up" perspective, emphasizing the subject field perspective of patient status through the assembly of rich textual corpora. At the end of this study, we intend to make available a scalable resource for this field. This work does not duplicate any existing work in terminology and information modeling work, rather extensively builds on existing work.