Non-fatal injury data: characteristics to consider for surveillance and research
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Non-fatal injury data: characteristics to consider for surveillance and research



Public Access Version Available on: June 01, 2023, 12:00 AM
Please check back on the date listed above.
  • English

  • Details:

    • Alternative Title:
      Inj Prev
    • Description:
      Background

      All data systems used for non-fatal injury surveillance and research have strengths and limitations that influence their utility in understanding non-fatal injury burden. The objective of this paper was to compare characteristics of major data systems that capture non-fatal injuries in the USA.

      Methods

      By applying specific inclusion criteria (eg, non-fatal and non-occupational) to well-referenced injury data systems, we created a list of commonly used non-fatal injury data systems for this study. Data system characteristics were compiled for 2018: institutional support, years of data available, access, format, sample, sampling method, injury definition/coding, geographical representation, demographic variables, timeliness (lag) and further considerations for analysis.

      Results

      Eighteen data systems ultimately fit the inclusion criteria. Most data systems were supported by a federal institution, produced national estimates and were available starting in 1999 or earlier. Data source and injury case coding varied between the data systems. Redesigns of sampling frameworks and the use of International Classification of Diseases, 9th Revision, Clinical Modification/International Classification of Diseases, 10th Revision, Clinical Modification coding for some data systems can make longitudinal analyses complicated for injury surveillance and research. Few data systems could produce state-level estimates.

      Conclusion

      Thoughtful consideration of strengths and limitations should be exercised when selecting a data system to answer injury-related research questions. Comparisons between estimates of various data systems should be interpreted with caution, given fundamental system differences in purpose and population capture. This research provides the scientific community with an updated starting point to assist in matching the data system to surveillance and research questions and can improve the efficiency and quality of injury analyses.

    • Pubmed ID:
      35210312
    • Pubmed Central ID:
      PMC9133150
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