1. Home
  2. RiP
  3. View Record
https://www.imt.mx/

Linking Crash and Post-Crash Data

This project addresses two different but important issues in California. One is to provide a more accurate picture of traffic injuries in California by utilizing medical data to fill in where police crash reports may not capture a crash or may have limited information. In this case two immediate applications are to obtain a better estimate of pedestrian and bicyclist injury and a better estimate of traffic injury on tribal areas. The second is to get a more accurate picture of emergency medical services (EMS) response times as these may be impacted by crash location, EMS response team locations, emergency department (ED) and trauma center locations, communication access, etc. Based on this information the research team intends to develop a model of EMS response for California that can target variables that can be modified to reduce time between a traffic crash and medical treatment at an ED or trauma center. This project continues the work of the 2017 CSCRS project “Completing the Picture of Traffic Injuries: Understanding Data Needs and Opportunities for Road Safety.” Following are steps to start in 2018: (1) Comparing crash and medical data to evaluate “under-reporting” in crash reports -- starting in 2018 the team will utilize data provided through Crash Medical Outcomes Data (CMOD) to evaluate the degree to which crash data (i.e., police collision reports) under-report crash injuries. One focus of analyses will be on pedestrian/bicyclist injury; identifying factors (e.g., age, ethnicity, and geographic area) associated with level of reporting. Existing reports suggest that many pedestrian and bicyclist injuries may be missed in crash reports, and the team would like to develop estimates of this for the State of California. (2) Developing measures of EMS response times as a function of rural versus urban, cell phone coverage, trauma center location -- the team will request data as needed and conduct extensive analyses to determine the time elements between the various events in EMS response as a function of crash location, ED or trauma center location, communication coverage, dispatch policy, etc. The time elements, as listed in the NEMSIS Uniform Pre-Hospital EMS Dataset, include a series of times from the initial call to the time the patient arrives at the destination (ED or trauma center). The aim in the study is to obtain estimates of actual time involved in EMS response, from the initial call to the arrival of the patient at an ED or trauma center. The intent is to evaluate these times as a function of variables mentioned above, including distance, communication coverage, dispatch policies, etc. As a subpart of assessing EMS response times, the team will look specifically at response times in tribal areas in California.

Language

  • English

Project

  • Status: Active
  • Funding: $70,000
  • Contract Numbers:

    69A3551747113

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Collaborative Sciences Center for Road Safety

    University of North Carolina, Chapel Hill
    Chapel Hill, NC  United States  27514
  • Project Managers:

    Sandt, Laura

  • Performing Organizations:

    University of California, Berkeley

    444 Davis Hall
    Berkeley, CA  United States  94720

    University of Tennessee, Knoxville

    Knoxville, TN  United States 
  • Principal Investigators:

    Ragland, David

    Cherry, Christopher

  • Start Date: 20180301
  • Expected Completion Date: 20190531
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01667897
  • Record Type: Research project
  • Source Agency: Collaborative Sciences Center for Road Safety
  • Contract Numbers: 69A3551747113
  • Files: UTC, RiP
  • Created Date: Apr 30 2018 10:39AM