AI Article Synopsis

  • The TRACTOR project was launched in 2017 to explore health risks faced by the agricultural workforce in France, utilizing comprehensive data from the National Health Insurance Fund for Agricultural Workers.
  • By linking multiple health databases and cleaning the data, TRACTOR has compiled a vast dataset covering over 10 million individuals, capturing health events from 2002 to 2016.
  • This initiative aims to enhance health surveillance for agricultural workers by identifying work-related illnesses and generating hypotheses, ultimately contributing to a more effective health monitoring system.

Article Abstract

Objectives: A vast data mining project called 'TRACking and moniToring Occupational Risks in agriculture' (TRACTOR) was initiated in 2017 to investigate work-related health events among the entire French agricultural workforce. The goal of this work is to present the TRACTOR project, the challenges faced during its implementation, to discuss its strengths and limitations and to address its potential impact for health surveillance.

Methods: Three routinely collected administrative health databases from the National Health Insurance Fund for Agricultural Workers and Farmers (MSA) were made available for the TRACTOR project. Data management was required to properly clean and prepare the data before linking together all available databases.

Results: After removing few missing and aberrant data (4.6% values), all available databases were fully linked together. The TRACTOR project is an exhaustive database of agricultural workforce (active and retired) from 2002 to 2016, with around 10.5 million individuals including seasonal workers and farm managers. From 2012 to 2016, a total of 6 906 290 individuals were recorded. Half of these individuals were active and 46% had at least one health event (e.g. declared chronic disease, reimbursed drug prescription) during this 5-year period.

Conclusions: The assembled MSA databases available in the TRACTOR project are regularly updated and represent a promising and unprecedent dataset for data mining analysis dedicated to the early identification of current and emerging work-related illnesses and hypothesis generation. As a result, this project could help building a prospective integrated health surveillance system for the benefit of agricultural workers.

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Source
http://dx.doi.org/10.1093/annweh/wxab083DOI Listing

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