Baorto D M, Cimino J J, Parvin C A, Kahn M G
Section of Medical Informatics, Washington University, St. Louis, MO, USA.
Proc AMIA Annu Fall Symp. 1997:96-100.
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.
使用一套标准的名称和代码来交换电子实验室数据将有助于多机构研究和数据汇总。这种需求促使了逻辑观察标识符名称和代码(LOINC)数据库及其测试命名规范的开发。我们开展了一项研究,要求3家学术医院(分属2个不同的医疗中心)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,将检测项目转换为LOINC代码,并提供汇总数据,以便用于比较实验室的使用情况。我们发现,将本地检测项目编码为LOINC代码往往很复杂,尤其是“属性类型”字段,而且各机构在选择上的明显细微差异可能导致电子汇总数据不匹配。在我们的研究中,72%至86%的不同机构间LOINC与相同检测项目不匹配的情况是由本地编码选择的差异造成的。LOINC在汇总来自不同地点的实验室数据时,具有巨大潜力消除对详细人工检查的需求,甚至可能具备通过选择匹配所需的LOINC字段子集来调整匹配严格度的内置功能。然而,所有机构都采用高质量的标准编码程序至关重要。