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Mapping pediatric injuries to target prevention, education, and outreach
Camille L Stewart1, Shannon N Acker1, Laura Pyle2
1Department of Surgery, University of Colorado School of Medicine, Aurora, CO, United States.
Insights
Mapping pediatric injuries by zip code identified high-risk areas needing more resources. This data-driven approach helps target interventions for child injury prevention effectively.
Area of Science:
- Public Health
- Injury Prevention
- Health Informatics
Background:
- Targeting pediatric injury prevention interventions to specific populations presents challenges.
- Geographic mapping of injuries can identify areas needing increased resources and interventions.
Purpose of the Study:
- To determine if mapping pediatric injuries by zip code can identify regions requiring targeted interventions and resources.
- To analyze demographic and cost factors associated with pediatric injuries in identified high-risk zip codes.
Main Methods:
- Utilized trauma registries from two Level I trauma centers for children (0-17 years) injured between 2009-2013.
- Employed choropleth mapping to identify outlier zip codes with higher injury incidences.
- Conducted multivariate linear regression to identify predictors of injury rates and hospital charges.
Main Results:
- 5380 children experienced traumatic injuries, incurring over $200 million in hospital costs.
- Mapping revealed outlier zip codes with higher pediatric injury rates, specific injury mechanisms, and increased hospital charges.
- Demographic features linked to higher pediatric injury rates and costs were identified for targeted interventions.
Conclusions:
- Outlier zip codes with higher pediatric injury frequencies and treatment costs were identified.
- These findings facilitated funding acquisition for prevention and education initiatives.
- Geospatial analysis techniques are crucial for expanding evidence-based public health initiatives.
Background:
Initiatives exist to prevent pediatric injuries, but targeting these interventions to specific populations is challenging. We hypothesized that mapping pediatric injuries by zip code could be used to identify regions requiring more interventions and resources.
Methods:
We queried the trauma registries of two level I trauma centers for children 0-17years of age injured between 2009 and 2013 with home zip codes in our state. Maps were created to identify outlier zip codes. Multivariate linear regression analysis identified predictors within these zip codes.
Results:
There were 5380 children who resided in the state and were admitted for traumatic injuries during the study period, with hospital costs totaling more than 200 million dollars. Choropleth mapping of patient addresses identified outlier zip codes in our metro area with higher incidences of specific mechanisms of injury and greater hospital charges. Multivariate analysis identified demographic features associated with higher rates of pediatric injuries and hospital charges, to further target interventions.
Conclusions:
We identified outlier zip codes in our metro area with higher frequencies of pediatric injuries and higher costs for treatment. These data have helped obtain funding for prevention and education efforts. Techniques such as those presented here are becoming more important as evidence based public health initiatives expand.
Level Of Evidence:
Type of Study: Cost Effectiveness, II.
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