Literature DB >> 29574892

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

Sharon R Silver1, Rebecca J Tsai1, Cyllene R Morris2, James M Boiano1, Jun Ju1, Marilyn S Scocozza2, Geoffrey M Calvert1.   

Abstract

INTRODUCTION: Industry and occupation (I&O) information collected by cancer registries is useful for assessing associations among jobs and malignancies. However, systematic differences in I&O availability can bias findings.
METHODS: Codability by patient demographics, payor, identifying (casefinding) source, and cancer site was assessed using I&O text from first primaries diagnosed 2011-2012 and reported to California Cancer Registry. I&O were coded to a U.S. Census code or classified as blank/inadequate/unknown, retired, or not working for pay.
RESULTS: Industry was codable for 37% of cases; 50% had "unknown" and 9% "retired" instead of usual industry. Cases initially reported by hospitals, covered by preferred providers, or with known occupational etiology had highest codable industry; cases from private pathology laboratories, with Medicaid, or diagnosed in outpatient settings had least. Occupation results were similar.
CONCLUSIONS: Recording usual I&O for retirees and improving linkages for reporting entities without patient access would improve I&O codability and research validity.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  occupation; cancer; coding; industry; registry; surveillance

Mesh:

Year:  2018        PMID: 29574892     DOI: 10.1002/ajim.22840

Source DB:  PubMed          Journal:  Am J Ind Med        ISSN: 0271-3586            Impact factor:   2.214


  3 in total

1.  Demographic considerations in analyzing decedents by usual occupation.

Authors:  Cora Peterson; Pamela K Schumacher; Andrea L Steege
Journal:  Am J Ind Med       Date:  2020-05-23       Impact factor: 3.079

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

Authors:  Laura A McClure; Tulay Koru-Sengul; Monique N Hernandez; Jill A Mackinnon; Natasha Schaefer Solle; Alberto J Caban-Martinez; David J Lee; Erin Kobetz
Journal:  PLoS One       Date:  2019-04-30       Impact factor: 3.240

3.  The quality of social determinants data in the electronic health record: a systematic review.

Authors:  Lily A Cook; Jonathan Sachs; Nicole G Weiskopf
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497

  3 in total

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