Controlled Vocabulary Design for Clinical Applications

词汇表的构成机制提供了几乎完全覆盖健康内容的承诺。基于计算机的患者记录研究所、ANSI-HISB、NCVHS和其他机构都提出了这样的声明，即在实现在护理点进行受控可比数据编码的承诺之前，需要对常规医学文本进行充分的覆盖。我们之前的工作表明，与非组成方法相比，医疗问题的组成方法提供了更好的覆盖率(54.0%vs.27.6%，p&lt；0.0001)。SNOMED-CT被美国病理学家学会定位为临床数据编码的标准，在美国，也许在英语世界也是如此。迄今为止，关于其拟议范围和目的的术语质量的独立评价提供的数据很少。我们提出以下具体目标：1)评估SNOMED-CT的临床内容覆盖范围，并测试SNOMED-CT具有足够的表现力来表示临床问题列表条目所需概念的假设，2)确定使用SNOMED-CT创建的组合表达式的可用性，并根据SNOMED-CT作为组合临床术语的临床可用性来测试问题列表管理器应用程序可用且不会成为混淆因素的假设，3)使用问题列表管理器应用程序评估SNOMED-CT在前瞻性临床试验中的满意度和性能，以检验SNOMED-CT在临床上可用且适合在护理点输入临床问题列表的假设。我们将编写一组接口来执行自动术语合成和解析，并设计和测试一台高吞吐量机器，以使用大型临床问题语料库(200,000个临床问题)来评估SNOMED-CT的内容覆盖率。这项拟议的工作将在临床环境中提供SNOMED-CT的独立评估。准确和可比较的患者数据，以我们行医的粒度记录，对医疗实践(例如，指南的实施)、未来临床医生的教育(例如，信息获取技术)和对循证医学实践的研究(例如，结果研究)具有深远的研究意义。

Compositional mechanisms for vocabulary provide the promise of near complete coverage of health content. The Computer-based Patient Record Institute, ANSI-HISB, the NCVHS and others have all proffered statements that adequate coverage of routine medical text is necessary before the promise of controlled comparable data encoding, at the point-of-care, can be realized. Our previous work demonstrated that a compositional approach to point-of-care entry of medical problems provided superior coverage when compared to a non- compositional approach (54.0% vs. 27.6%, p<0.0001). SNOMED-CT is being positioned by the College of American Pathologists as being a standard for clinical data encoding in the United States and perhaps in the English-speaking world. To date, there is little data available from independent evaluations regarding the quality of the terminology for its proposed scope and purpose. We propose the following Specific Aims: 1) to evaluate the clinical content coverage of SNOMED-CT, and to test the hypothesis that SNOMED-CT has adequate expressivity to represent the concepts required for clinical Problem List entry, 2) to determine the Usability of compositional expressions created using SNOMED-CT, and to test the hypothesis that the Problem List Manager Application is usable and will not be a confounding factor, in terms of the clinical Usability of the SNOMED-CT as a compositional clinical terminology, and 3) to evaluate the satisfaction and performance of SNOMED-CT in a Prospective Clinical Trial using a Problem List Manager Application to test the hypothesis that SNOMED-CT is clinically usable and suitable for clinical problem list entry at the point-of-care. We will write a set of interfaces to perform Automated Term Composition and Dissection and design and test a High Throughput machine to evaluate the content coverage of SNOMED-CT using a large corpus of clinical problems (2,000,000 clinical problems). This proposed effort would provide an independent evaluation of SNOMED-CT in a clinical setting. Accurate and comparable patient data, recorded at the granularity at which we practice medicine, has far reaching research implications for medical practice (e.g., implementation of guidelines), education of future clinicians (e.g., information acquisition techniques) and research (e.g., outcomes research) toward the evidence-based practice of medicine.