审核三个大型机构中 LOINC 使用的一致性和有用性——使用版本空间对 LOINC 代码进行分组。
Auditing consistency and usefulness of LOINC use among three large institutions - using version spaces for grouping LOINC codes.
机构信息
The Department of Biomedical Informatics, The University of Utah, Salt Lake City, UT, USA.
出版信息
J Biomed Inform. 2012 Aug;45(4):658-66. doi: 10.1016/j.jbi.2012.01.008. Epub 2012 Jan 28.
OBJECTIVES
We wanted to develop a method for evaluating the consistency and usefulness of LOINC code use across different institutions, and to evaluate the degree of interoperability that can be attained when using LOINC codes for laboratory data exchange. Our specific goals were to: (1) Determine if any contradictory knowledge exists in LOINC. (2) Determine how many LOINC codes were used in a truly interoperable fashion between systems. (3) Provide suggestions for improving the semantic interoperability of LOINC.
METHODS
We collected Extensional Definitions (EDs) of LOINC usage from three institutions. The version space approach was used to divide LOINC codes into small sets, which made auditing of LOINC use across the institutions feasible. We then compared pairings of LOINC codes from the three institutions for consistency and usefulness.
RESULTS
The number of LOINC codes evaluated were 1917, 1267 and 1693 as obtained from ARUP, Intermountain and Regenstrief respectively. There were 2022, 2030, and 2301 version spaces among ARUP and Intermountain, Intermountain and Regenstrief and ARUP and Regenstrief respectively. Using the EDs as the gold standard, there were 104, 109 and 112 pairs containing contradictory knowledge and there were 1165, 765 and 1121 semantically interoperable pairs. The interoperable pairs were classified into three levels: (1) Level I - No loss of meaning, complete information was exchanged by identical codes. (2) Level II - No loss of meaning, but processing of data was needed to make the data completely comparable. (3) Level III - Some loss of meaning. For example, tests with a specific 'method' could be rolled-up with tests that were 'methodless'.
CONCLUSIONS
There are variations in the way LOINC is used for data exchange that result in some data not being truly interoperable across different enterprises. To improve its semantic interoperability, we need to detect and correct any contradictory knowledge within LOINC and add computable relationships that can be used for making reliable inferences about the data. The LOINC committee should also provide detailed guidance on best practices for mapping from local codes to LOINC codes and for using LOINC codes in data exchange.
目的
我们希望开发一种方法来评估不同机构之间 LOINC 代码使用的一致性和有用性，并评估在使用 LOINC 代码进行实验室数据交换时可以实现的互操作性程度。我们的具体目标是：（1）确定 LOINC 中是否存在矛盾的知识。（2）确定在系统之间以真正互操作的方式使用了多少 LOINC 代码。（3）为提高 LOINC 的语义互操作性提供建议。
方法
我们从三个机构收集了 LOINC 使用的扩展定义 (ED)。版本空间方法用于将 LOINC 代码划分为小的集合，这使得在机构之间审核 LOINC 的使用成为可能。然后，我们比较了来自三个机构的 LOINC 代码的配对，以确定其一致性和有用性。
结果
从 ARUP、Intermountain 和 Regenstrief 分别获得的评估 LOINC 代码数量分别为 1917、1267 和 1693。ARUP 和 Intermountain、Intermountain 和 Regenstrief 以及 ARUP 和 Regenstrief 之间的版本空间分别为 2022、2030 和 2301。使用 ED 作为黄金标准，有 104、109 和 112 对包含矛盾知识，有 1165、765 和 1121 对语义上可互操作。互操作对分为三个级别：（1）级别 I - 没有意义的损失，通过相同的代码完全交换了完整的信息。（2）级别 II - 没有意义的损失，但需要处理数据才能使数据完全可比。（3）级别 III - 有些意义的损失。例如，具有特定“方法”的测试可以与没有“方法”的测试汇总在一起。
结论
在用于数据交换的 LOINC 用法方面存在差异，导致一些数据在不同企业之间无法真正互操作。为了提高其语义互操作性，我们需要检测和纠正 LOINC 中的任何矛盾知识，并添加可用于对数据进行可靠推断的可计算关系。LOINC 委员会还应就从本地代码到 LOINC 代码的映射以及在数据交换中使用 LOINC 代码的最佳实践提供详细指导。
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