Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies
Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies
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DOI：
10.1136/oemed-2015-103152
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发表时间：
2016-06-01
影响因子：
4.9
通讯作者：
Friesen, Melissa C.
中科院分区：
文献类型：
--
作者：
Russ, Daniel E.;Ho, Kwan-Yuet;Friesen, Melissa C.
背景将职称映射到标准化职业分类（SOC）代码是流行病学研究中识别职业风险因素的重要一步。由于手动编码是耗时的，并具有中等的可靠性，我们开发了一种算法，称为SOCcer（标准化职业编码计算机辅助流行病学研究）分配SOC-2010代码的基础上自由文本的工作描述components.Methods职称和基于任务的分类开发了比较工作描述多个源链接的工作和任务描述SOC代码。基于行业内SOC流行率开发了基于行业的分类器。这些分类器被用于逻辑模型训练使用14 983个工作与专家分配的SOC代码，以获得经验权重的算法，得分每个SOC/工作描述。我们为每项工作分配了得分最高的SOC代码。结果在11991个病例对照研究工作岗位中，SOCcer编码与人工编码在6位数和2位数水平上的一致率分别为44.5%和76.3%。一致性随着分数的增加而增加，提供了一种机制来识别需要审查的作业。观察到基于SOCcer和手动SOC分配的铅估计值之间具有良好的一致性（kappa 0.6-0.8）。观察到的检查工作说明，其中包括缩写和工作场所特定的technology.Conclusions虽然一些手工编码仍将是必要的，使用SOCcer可以提高效率，将职业纳入大规模的流行病学研究。
Background Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we developed an algorithm called SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) to assign SOC-2010 codes based on free-text job description components.Methods Job title and task-based classifiers were developed by comparing job descriptions to multiple sources linking job and task descriptions to SOC codes. An industry-based classifier was developed based on the SOC prevalence within an industry. These classifiers were used in a logistic model trained using 14 983 jobs with expert-assigned SOC codes to obtain empirical weights for an algorithm that scored each SOC/job description. We assigned the highest scoring SOC code to each job. SOCcer was validated in 2 occupational data sources by comparing SOC codes obtained from SOCcer to expert assigned SOC codes and lead exposure estimates obtained by linking SOC codes to a job-exposure matrix.Results For 11 991 case-control study jobs, SOCcer-assigned codes agreed with 44.5% and 76.3% of manually assigned codes at the 6-digit and 2-digit level, respectively. Agreement increased with the score, providing a mechanism to identify assignments needing review. Good agreement was observed between lead estimates based on SOCcer and manual SOC assignments (kappa 0.6-0.8). Poorer performance was observed for inspection job descriptions, which included abbreviations and worksite-specific terminology.Conclusions Although some manual coding will remain necessary, using SOCcer may improve the efficiency of incorporating occupation into large-scale epidemiological studies.