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Development and Evaluation of Methods for Structured Recording of Heart Murmur Findings Using SNOMED-CT® Post-Coordination

机译:使用SNOMED-CT®协调后心脏杂音发现的结构化记录方法的开发和评估

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摘要

>Objective: This study evaluated an existing SNOMED-CT® model for structured recording of heart murmur findings and compared it to a concept-dependent attributes model using content from SNOMED-CT.>Methods: The authors developed a model for recording heart murmur findings as an alternative to SNOMED-CT's use of Interprets and Has interpretation. A micro-nomenclature was then created to support each model using subset and extension mechanisms described for SNOMED-CT. Each micro-nomenclature included a partonomy of cardiac cycle timing values. A mechanism for handling ranges of values was also devised. One hundred clinical heart murmurs were recorded using purpose-built recording software based on both models.>Results: Each micro-nomenclature was extended through the addition of the same list of concepts. SNOMED role grouping was required in both models. All 100 clinical murmurs were described using each model. The only major differences between the two models were the number of relationship rows required for storage and the hierarchical assignments of concepts within the micro-nomenclatures.>Conclusion: The authors were able to capture 100 clinical heart murmurs with both models. Requirements for implementing the two models were virtually identical. In fact, data stored using these models could be easily interconverted. There is no apparent penalty for implementing either approach.
机译:>目的:该研究评估了现有的SNOMED-CT ®模型,用于心脏杂波发现的结构化记录,并使用SNOMED-CT的内容将其与概念相关的属性模型进行了比较。 >方法:作者开发了一种记录心脏杂音结果的模型,以替代SNOMED-CT使用解释和Has解释。然后使用针对SNOMED-CT所述的子集和扩展机制,创建微命名法以支持每个模型。每个微观术语都包括心动周期定时值的词法。还设计了一种处理值范围的机制。使用基于这两种模型的专用记录软件记录了一百种临床心脏杂音。>结果:通过添加相同的概念列表,扩展了每个微观术语。在两个模型中都需要SNOMED角色分组。使用每种模型描述了所有100种临床杂音。两种模型之间的唯一主要区别是存储所需的关系行数和微观术语中概念的分层分配。>结论:作者能够捕获100种临床心脏杂音楷模。实施这两种模型的要求实际上是相同的。实际上,使用这些模型存储的数据可以轻松地相互转换。实施这两种方法都没有明显的惩罚。

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