Lieberman Michael I, Ricciardi Thomas N, Masarie F E, Spackman Kent A
Oregon Health & Sciences University, Portland, OR, USA.
AMIA Annu Symp Proc. 2003;2003:910.
The usefulness of digital clinical information is limited by difficulty in accessing that information. Information in electronic medical records (EMR) must be entered and stored at the appropriate level of granularity for individual patient care. However, benefits such as outcomes research and decision support require aggregation to clinical data -- "heart disease" as opposed to "S/P MI 1997" for example. The hierarchical relationships in an external reference terminology, such as SNOMED, can facilitate aggregation. This study examines whether by leveraging the knowledge built into SNOMED's hierarchical structure, one can simplify the query process without degrading the query results.
数字临床信息的实用性受到获取信息难度的限制。电子病历（EMR）中的信息必须以适合个体患者护理的适当粒度级别进行输入和存储。然而，诸如结果研究和决策支持等益处需要将数据汇总到临床数据——例如，“心脏病”而非“1997年心肌梗死后状态”。外部参考术语（如SNOMED）中的层次关系有助于汇总。本研究探讨了通过利用SNOMED层次结构中构建的知识，是否可以在不降低查询结果的情况下简化查询过程。
