Using Logical Observation Identifier Names and Codes (LOINC) to exchange laboratory data among three academic hospitals.

D M Baorto, J J Cimino, C A Parvin, M G Kahn
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Abstract

Using a standard set of names and codes to exchange electronic laboratory data would facilitate multiinstitutional research and data pooling. This need has led to the development of the Logical Observation Identifier Names and Codes (LOINC) database and its test naming convention. We conducted a study which required 3 academic hospitals (in 2 separate medical centers) to extract raw laboratory data from their local information system for a defined patient population, translate tests into LOINC, and provide aggregate data which could then be used to compare laboratory utilization. We found that the coding of local tests into LOINC can often be complex, especially the "Kind of Property" field, and apparently trivial differences in choices made by individual institutions can result in nonmatches in electronically pooled data. In our study, 72-86% of the failures of LOINC to match the same tests between different institutions were due to differences in local coding choices. LOINC has tremendous potential to eliminate the needing for detailed human inspection during the pooling of laboratory data from diverse sites, and perhaps even a built-in capability to adjust matching stringency by selecting subsets of LOINC fields required to match. However, a quality, standard coding procedure at all sites is critical.

使用逻辑观察标识名称和代码(LOINC)在三所学术医院之间交换实验室数据。
使用一套标准的名称和代码来交换电子实验室数据将促进多机构研究和数据汇集。这种需求导致了逻辑观察标识符名称和代码(LOINC)数据库及其测试命名约定的发展。我们进行了一项研究,要求3所学术医院(位于2个独立的医疗中心)从其本地信息系统中提取特定患者群体的原始实验室数据,将测试结果转换为LOINC,并提供可用于比较实验室利用率的汇总数据。我们发现,将本地测试编码到LOINC中通常是复杂的,特别是“属性类型”字段,而且各个机构所做选择的明显细微差异可能导致电子汇总数据中的不匹配。在我们的研究中,72-86%的LOINC在不同机构之间匹配相同测试的失败是由于本地编码选择的差异。LOINC具有巨大的潜力,可以在汇集来自不同站点的实验室数据期间消除对详细的人工检查的需要,甚至可以通过选择需要匹配的LOINC字段子集来调整匹配严格性的内置功能。然而,在所有站点上的高质量、标准的编码程序是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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