67
Views
1
CrossRef citations to date
0
Altmetric
Research Articlearticle

Using Partnerships and Multiple Data Sources to Surveil Agricultural Injuries: Considerations and Recommendations

, , & ORCID Icon
Pages 197-205 | Published online: 18 Dec 2023
 

ABSTRACT

This article describes an interprofessional collaboration between Sanford Health and North Dakota State University that strengthens agricultural injury surveillance in the upper Midwest by using multiple sources of health data and geographic information systems (GIS) technology. We provide methodological insights and considerations for using and combining facility-level trauma registry (FLTR) data, national data sets, and GIS to identify areas with disproportionate agricultural injury prevalence. Additionally, we discuss the benefits of FLTR data, how and why it is collected, the data it contains, and how it can be combined with national datasets to fill-in surveillance gaps. Lastly, we offer recommendations for building cross-institutional and interprofessional partnerships.

Acknowledgments

This project is supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number 5P20GM121341.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the National Institute of General Medical Sciences [5P20GM121341].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 163.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.