ArticleInjury epidemiology2021
Application of data linkage techniques to Pacific Northwest commercial fishing injury and fatality data.
Article in Injury epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Record Linkage for Malaria Deaths Data Recovery and Surveillance in Brazil.Tropical medicine and infectious disease · 2023Article
- Commercial Fishing Fatalities and Injuries Described by Linked Vessel Incidents.Journal of agromedicine · 2023Article
- Utilizing Haddon matrix to assess nonfatal commercial fishing injury factors in Oregon and Washington.Injury epidemiology · 2023Article
- Evaluation of a technical advisory board for an occupational injury surveillance research project: A qualitative study.Health science reports · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundCommercial fishing consistently has among the highest workforce injury and fatality rates in the United States. Data related to commercial fishing incidents are routinely collected by multiple organizations which do not currently coordinate or automatically link data. Each data set has the potential to generate a more complete picture to inform prevention efforts. Our objective was to examine the utility of using statistical data linkage methods to link commercial fishing incident data when personally identifiable information is not available.
methodsIn this feasibility study, we identified true matches and discrepancies between de-identified data sets using the Python Record Linkage Toolkit. Four commercial fishing data sets from Oregon and Washington were linked: the Commercial Fishing Incident Database, the Vessel Casualty Database, the Nonfatal Injuries Database, and the Oregon Trauma Registry. The data sets each covered different date ranges within 2000-2017, containing 458, 524, 184, and 11 cases respectively. Several data linkage classifiers were evaluated.
resultsThe Naïve-Bayes classifier returned the highest number of true matches between these small data sets. A total of 41 true matches and 8 close matches were identified, of which 29 were determined to be duplicates. In addition, linkage highlighted 4 records that were not commercial fishing cases from Oregon and Washington. The optimum match parameters were the date, state, vessel official number, and number of people on board.
conclusionsStatistical data linkage enables accurate, routine matching for small de-identified injury and fatality data sets such as those in commercial fishing. It provides information needed to improve the accuracy of existing data records. It also enables expanding and sharpening details of individual incidents in support of occupational safety research.
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