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Dataset Information

Addressing health disparities using multiply imputed injury surveillance data.


ABSTRACT:

Background

Assessing disparities in injury is crucial for injury prevention and for evaluating injury prevention strategies, but efforts have been hampered by missing data. This study aimed to show the utility and reliability of the injury surveillance system as a trustworthy resource for examining disparities by generating multiple imputed companion datasets.

Methods

We employed data from the National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) for the period 2014-2018. A comprehensive simulation study was conducted to identify the appropriate strategy for addressing missing data limitations in NEISS-AIP. To evaluate the imputation performance more quantitatively, a new method based on Brier Skill Score (BSS) was developed to assess the accuracy of

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10316636 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature