论文标题
用于模拟III临床编码数据集的银标准的实验评估和开发
Experimental Evaluation and Development of a Silver-Standard for the MIMIC-III Clinical Coding Dataset
论文作者
论文摘要
临床编码目前是一个劳动力密集的，容易出错但关键的行政过程，医院的患者发作是由大型，标准化的分类法规层次结构的合格人员手动分配的代码。自动化的临床编码在NLP研究中具有悠久的历史，并且最近看到了新的开发项目，从而树立了新的最新成果。此任务中使用的流行数据集是Mimic-III，这是一个大型重症监护数据库，其中包括临床免费文本注释和相关代码。我们主张重新考虑有效性模仿III的代码，这些代码通常被视为黄金标准，尤其是在模仿III没有接受次要验证时。这项工作提出了一种开源的，可再现的实验方法，用于评估从EHR放电摘要中得出的代码的有效性。我们用模拟于III的排放摘要来体现该方法，并显示模拟III中最常分配的代码的编码不足35％。
Clinical coding is currently a labour-intensive, error-prone, but critical administrative process whereby hospital patient episodes are manually assigned codes by qualified staff from large, standardised taxonomic hierarchies of codes. Automating clinical coding has a long history in NLP research and has recently seen novel developments setting new state of the art results. A popular dataset used in this task is MIMIC-III, a large intensive care database that includes clinical free text notes and associated codes. We argue for the reconsideration of the validity MIMIC-III's assigned codes that are often treated as gold-standard, especially when MIMIC-III has not undergone secondary validation. This work presents an open-source, reproducible experimental methodology for assessing the validity of codes derived from EHR discharge summaries. We exemplify the methodology with MIMIC-III discharge summaries and show the most frequently assigned codes in MIMIC-III are under-coded up to 35%.
