Baorto D M, Cimino J J, Parvin C A, Kahn M G
Department of Pathology, Washington University School of Medicine, Washington University, St. Louis, MO 63110, USA.
Int J Med Inform. 1998 Jul;51(1):29-37. doi: 10.1016/s1386-5056(98)00089-6.
A standard set of names and codes for laboratory test results is critical for any endeavor requiring automated data pooling, including multi-institutional research and cross-facility patient care. This need has led to the development of the logical observation identifier names and codes (LOINC) database and its test-naming convention. This study is an expansion of a pilot study using LOINC to exchange laboratory data between Columbia University Medical Center in New York and Barnes Hospital at Washington University in St. Louis, where we described complexities and ambiguities that arose in the LOINC coding process (D.M. Baorto, J.J. Cimino, C.A. Parvin, M.G. Kahn, Proc. Am. Med. Inf. Assoc. 1997). For the present study, we required the same two medical centers to again 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. Here we examine a larger number of tests from each site which have been recoded using an updated version of the LOINC database. We conclude 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 the present study, 75% of failures to match the same tests between different institutions using LOINC codes were due to differences in local coding choices. LOINC has the potential to eliminate the need 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 is required and examples highlighted in this paper may require special attention while mapping to LOINC.
一套标准的实验室检测结果名称和代码对于任何需要自动数据汇总的工作都至关重要，包括多机构研究和跨机构患者护理。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发展。本研究是一项试点研究的扩展，该试点研究使用LOINC在纽约的哥伦比亚大学医学中心和圣路易斯华盛顿大学的巴恩斯医院之间交换实验室数据，我们在其中描述了LOINC编码过程中出现的复杂性和模糊性（D.M. Baorto、J.J. Cimino、C.A. Parvin、M.G. Kahn，《美国医学信息学会会刊》，1997年）。对于本研究，我们要求同样的两个医学中心再次从其本地信息系统中为特定患者群体提取原始实验室数据，将检测项目转换为LOINC代码，并提供汇总数据，然后可用于比较实验室利用率。在这里，我们检查了来自每个站点的大量使用更新版LOINC数据库重新编码的检测项目。我们得出结论，将本地检测项目编码为LOINC代码通常可能很复杂，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。在本研究中，使用LOINC代码在不同机构之间未能匹配相同检测项目的情况中，75%是由于本地编码选择的差异。LOINC有潜力消除在汇总来自不同站点的实验室数据时进行详细人工检查的必要性，甚至可能具有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，需要一个质量标准编码程序，并且本文中突出显示的示例在映射到LOINC时可能需要特别关注。
Zotero 插件