- Overall, how do geographic areas within your county compare on the consequence data rates? Do any stand out as high or low? Discuss differences.
- Do you think the data accurately reflect the related problems in the community? Why or why not?
- What does the trend data available for the consequences suggest in the different geographic areas? Is the problem increasing, decreasing, or staying the same? Discuss differences and patterns.
- Do the consequences in some geographic areas appear to be more of a problem than in others? Why?
- Are there differences in patterns of consequences between age groups?
- Are there differences in patters of consequence between gender?
- Are there differences in patterns of consequences between age and gender and location?
The Substance Misuse and Abuse Reduction Team
SMART (Substance Misuse and Abuse Reduction Team) is a drug prevention coalition with 45 volunteers. Our mission is to prevent teen Rx pain pill and alcohol abuse. SMART members contribute to this blog. To find out more call 801-851-7181 or email kyen@utahcounty.gov. See our website at www.smartutahcounty.info.
Monday, November 17, 2008
DPS Vehicle Crash Data
Review Utah Department of Public Safety vehicle crash data at - http://sites.google.com/site/utahcountycoalition/data-collection-workgroup). Answer the following questions:
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At first glance Santaquin and Springville seem to be drastically higher than the rest of the county. This data would be consistent with initial analysis showing the highest problem lies in South County. I have a few concerns about the manner in which the data is collected. The warning tag at the bottom suggests 3/4 of driver’s city of residents is not listed on the crash report. I would agree with this warning. The manner in which the data is collected at the time of the accident varies from officer to officer and usually consists of an interview with the suspect or simply filling out the report based on driver’s license information. People move and never update their address, despite a legal requirement. Many times, in that case of an injury accident, the suspect driver may be incapacitated or transported to the hospital. If so an officer may rely on driver’s license information for the suspect’s current address. That information has a tendency to be incorrect. I also think in notable to report that the officer in charge of the crash has the responsibility to recognize the use of drugs and alcohol as a factor. Some officers don’t care and other officers are undertrained meaning they lack experience or an ability to recognize the correlation. I feel the reported numbers are lower than what they should be. Also the crash reports itself is rather lengthy and cumbersome to complete. It is very possible the information contained was reported inaccurately due to officer inexperience. That being said the trend data still suggest a higher crash rate per 100,000 pop from Springville South.
Interesting enough the crash data suggests the target population in this category to be between about 20 and 45 with male being clearly the majority. Fatalities are low for both genders but male is still predominantly high. Crashes resulting in injury related to property damage are about even with injury showing slightly higher. Also looking at the time, day, and month of crash data weekends, Friday through Sunday has the highest crash rate. This I believe is due to weekend use related to “partying”. I have made DUI arrested from parties beginning Friday night spilling into Saturday morning and Saturday night spilling into Sunday morning. Sunday morning is a great time to look for DUI’s. Again these parties are related to alcohol and binge drinking. Also looking at the time of the crash there is a spike mid to late afternoon with a decrease in the early evening, a second spike late evening running into early morning with a decrease at around 5 AM, and a third spike at around 10 AM. The late afternoon spike correlates with commuter traffic and those traveling home from work. The 11-Midnight spike correlates with bars closing. The 10AM spike is a result of people driving home after a night or partying and more than likely had been passed out for several hours.
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