Freeman MaryBeth B, Pollack Lori A, Rees Judy R, Johnson Christopher J, Rycroft Randi K, Rousseau David L, Hsieh Mei-Chin
Cancer Surveillance Branch, Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.
New Hampshire State Cancer Registry and the Geisel School of Medicine at Dartmouth, Department of Epidemiology, Hanover, New Hampshire.
Am J Ind Med. 2017 Aug;60(8):689-695. doi: 10.1002/ajim.22739.
Although data on industry and occupation (I&O) are important for understanding cancer risks, obtaining standardized data is challenging. This study describes the capture of specific I&O text and the ability of a web-based tool to translate text into standardized codes.
Data on 62 525 cancers cases received from eight National Program of Cancer Registries (NPCR) states were submitted to a web-based coding tool developed by the National Institute for Occupational Safety and Health for translation into standardized I&O codes. We determined the percentage of sufficiently analyzable codes generated by the tool.
Using the web-based coding tool on data obtained from chart abstraction, the NPCR cancer registries achieved between 48% and 75% autocoding, but only 12-57% sufficiently analyzable codes.
The ability to explore associations between work-related exposures and cancer is limited by current capture and coding of I&O data. Increased training of providers and registrars, as well as software enhancements, will improve the utility of I&O data.
尽管行业和职业（I&O）数据对于理解癌症风险很重要，但获取标准化数据具有挑战性。本研究描述了特定I&O文本的获取以及基于网络的工具将文本转换为标准化代码的能力。
从八个国家癌症登记计划（NPCR）州收到的62525例癌症病例数据被提交给美国国家职业安全与健康研究所开发的基于网络的编码工具，以转换为标准化的I&O代码。我们确定了该工具生成的可充分分析代码的百分比。
在从图表摘要获得的数据上使用基于网络的编码工具，NPCR癌症登记处实现了48%至75%的自动编码，但只有12%至57%的代码可充分分析。
目前I&O数据的获取和编码限制了探索工作相关暴露与癌症之间关联的能力。加强对医疗服务提供者和登记员的培训以及软件改进，将提高I&O数据的实用性。
