Capture and coding of industry and occupation measures: Findings from eight National Program of Cancer Registries states

Abstract

Background 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. Methods 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. Results 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. Conclusions 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.

Availability and accuracy of occupation in cancer registry data among Florida firefighters

“…This may be because their longest held job was something other than a firefighting occupation, or it may be that the code is simply not an accurate representation of their occupation. The high percentage of those listed as unemployed or retired (27.3%) in our sample is likely due to the fact that data in the cancer registry record are obtained at the time of diagnosis, and given that a greater proportion of cancers are diagnosed in older age, cases are often unemployed or retired at that point[10]. Occupational fields are supposed to represent the longest held position, but it is clear that this is not always the case.…”

“…A recent study of eight NPCR states employed the web-based NIOSH Industry and Occupation Computerized Coding System (NIOCCS), developed by the National Institute for Occupational Safety and Health[12, 13], to translate text into standardized industry and occupation codes[10]. Results indicated that this was a useful tool for improving occupation fields; however, registries reported the need for increased training to collect higher quality information to be either coded by registrars or auto-coded by the web-based tool.…”

“…Via medical record abstraction, participants of the National Program of Cancer Registries (NPCR) collect text indicating usual occupation (“type of job patient engaged in for the greatest number of working years”) and text indicating usual industry (“type of business or industry where patient worked in his or her usual occupation”)[5]. These data are frequently retrieved from narrative fields in the medical record, which take no standard form, and coding often requires extensive manual review and processing[10]. Not only are these data frequently missing, they are often missing in a differential fashion based on facility, provider, insurance status, and occupation[4].…”

Perspectivas do uso de mineração de dados e aprendizado de máquina em saúde e segurança no trabalho

“…Outra ferramenta de data mining especializada em SST é a ferramenta gratuita disponibilizada pelo instituto de saúde ocupacional dos Estados Unidos, o National Institute for Occupational Safety and Health (NIOSH), para análise de narrativas. O software implementa tarefas de data mining, como stemming, entre outras tarefas, para realizar a codificação automatizada de ocupação e tipo de atividade 31,32 . A ferramenta está disponível para a língua inglesa e utiliza o padrão de codificação de ocupações internacional (SOC).…”

Codability of industry and occupation information from cancer registry records: Differences by patient demographics, casefinding source, payor, and cancer type

“…CCR sources of I&O information include admission and discharge summaries, face sheets, patient history, oncology consultation reports, and health and social history questionnaires the patient has completed. Still, I&O data are often missing from state registry records, or are recorded in such a way that precludes assignment of standardized codes that are comparable and therefore usable for analyses …”