Gamache Roland E, Dixon Brian E, Grannis Shaun, Vreeman Daniel J
Regenstrief Institute, Inc., Indianapolis, IN, USA.
AMIA Annu Symp Proc. 2012;2012:228-36. Epub 2012 Nov 3.
Automated electronic laboratory reporting (ELR) for public health has many potential advantages, but requires mapping local laboratory test codes to a standard vocabulary such as LOINC. Mapping only the most frequently reported tests provides one way to prioritize the effort and mitigate the resource burden. We evaluated the implications of selective mapping on ELR for public health by comparing reportable conditions from an operational ELR system with the codes in the LOINC Top 2000. Laboratory result codes in the LOINC Top 2000 accounted for 65.3% of the reportable condition volume. However, by also including the 129 most frequent LOINC codes that identified reportable conditions in our system but were not present in the LOINC Top 2000, this set would cover 98% of the reportable condition volume. Our study highlights the ways that our approach to implementing vocabulary standards impacts secondary data uses such as public health reporting.
用于公共卫生的自动化电子实验室报告（ELR）有许多潜在优势，但需要将本地实验室测试代码映射到诸如LOINC之类的标准词汇表。仅映射最常报告的测试是确定工作优先级并减轻资源负担的一种方法。我们通过将一个运行中的ELR系统的可报告病症与LOINC前2000代码进行比较，评估了公共卫生ELR中选择性映射的影响。LOINC前2000中的实验室结果代码占可报告病症总量的65.3%。然而，通过同时纳入在我们系统中识别出可报告病症但不在LOINC前2000中的129个最常用LOINC代码，这组代码将覆盖98%的可报告病症总量。我们的研究突出了我们实施词汇标准的方法对诸如公共卫生报告等二次数据使用产生影响的方式。
