Geographic cluster analysis of injury severity and hospital resource use in a regional trauma system

Prehosp Emerg Care. Apr-Jun 2010;14(2):137-44. doi: 10.3109/10903120903538682.

Abstract

Objectives: To determine clusters of trauma incidents with high injury severity and resource utilization and to test their association with census demographic information.

Methods: Using "trauma band" unique identifiers and probabilistic linkage for unmatched cases, we matched injury location information collected from a centralized regional trauma communications center to the state trauma system registry for patients directly transported to two level I trauma centers for the years 2001-2003 in a three-county area. The injury locations were aggregated at the census tract level using a geographic information system (GIS). Moran's I analysis was used to determine clusters of census tracts that had a high incidence of either total trauma injuries, Injury Severity Scores (ISSs) >15, or high resource use (in-hospital mortality, admission to the intensive care unit, or major nonorthopedic surgery). These clusters were then tested for association with census tract demographics using logistic regression.

Results: Eight thousand seven hundred fifty-one injured persons were directly transported from the tricounty area to a trauma center during the study period. The mean (+/- standard deviation) age was 37 +/- 21 years, 67.4% were male, 18.9% had ISSs >15, and 29.8% had a high-resource-use indicator. Moran's I analysis demonstrated a single large cluster of incidents for total injuries, ISS >15, and occurrence of a high-resource-use indictor that overlapped except for one small census tract. Logistic regression revealed that the high-risk cluster was associated with a higher prevalence of nonwhite population and vacant housing and a lower prevalence of foreign-born residents and family housing.

Conclusions: GIS cluster analysis demonstrated high-risk census tracts for trauma incidents and associated population demographics. Geospatial analyses may assist injury prevention interventions and emergency medical services deployment strategies for trauma.

MeSH terms

  • Adult
  • Algorithms
  • Cluster Analysis
  • Female
  • Geographic Information Systems*
  • Hospitals / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Observation
  • Retrospective Studies
  • Trauma Severity Indices*