The pedestrian struck by a car presents challenges to trauma professionals for a number of reasons. Due to the size mismatch between the two, serious injuries are fairly common. And unfortunately, many injuries are occult, so it’s easy to dismiss patients who may be hiding serious problems.

The National Highway and Traffic Safety Administration (NHTSA) recently published its Traffic Safety Facts report for 2011. This 232 page tome contains a wealth of interesting and thought-provoking data. One of the more interesting tidbits that caught my eye had to do with pedestrians struck by cars.

Most normal people do not get hit by cars. There is nearly always some additional factor that allows this to occur:

• Don’t understand cars – this is a typical reason for small children, and I’ve also seen foreign visitors from countries with little auto traffic fall victim to this one. The developmentally disabled also fall into this category.
• Not paying attention – this category is growing rapidly due to smart phone use
• Can’t clear the intersection in time – this one gets the elderly. Due to physical constraints, they can’t move fast enough (4 ft/sec for most intersections) to get across in time
• Intoxicated – this basically puts an adult back into the first category above. These incidents tend to be clustered around bars, and the numbers peak at night, typically from midnight to 3am.

The NHTSA report has always detailed the age breakdown of pedestrians struck, but now they are reporting the number of “impaired walkers” as well.

• Overall, death by motor vehicle (occupants and pedestrians) involved alcohol 31% of the time (!!)
• 4,432 pedestrians were killed and about 69,000 were injured
• About one third of pedestrians killed tested positive for alcohol, and most were legally intoxicated!
• 14% of the nonintoxicated pedestrians were struck by an intoxicated driver vs 19% of intoxicated pedestrians

Bottom line: There are many reasons for getting hit by a car, and being intoxicated is an entirely avoidable one. These patients can be seriously injured, so don’t just shrug off complaints as being due to intoxication. Additional prevention efforts should be developed using the interesting patterns outlined in the NHTSA report.

Reference: NHTSA Traffic Safety Facts 2011

The July issue of Trauma MedEd is ready to go! Subscribers will receive it overnight Sunday night. This issue is devoted to Xrays. 

Included are articles on:

• Trauma team radiation exposure
• Repeating images in the trauma bay
• Using lateral chest xrays and CT for chest trauma
• and more!

As mentioned above, subscribers will get the issue delivered tomorrow night to their preferred email address. It will be available to everybody else on next Wednesday’s blog post.

Check out back issues, and subscribe now! Get it first by clicking here!

When trauma patients are enroute to the hospital, accurate arrival times are crucial. If the patient arrives later than announced, the trauma team waits and wastes time. If the patient gets there early, it’s really a form of undertriage and they may not be able to immediately get the critical services they need. A Portland study noted that more than half of transport time estimates were off by at least 10 minutes, and over a quarter were wrong by 10 minutes or more! Surely there must be a way to predict transport time more accurately!

Harbor-UCLA Medical Center developed a simulation using transport data from a single Oregon county for an entire year. Their goal was to determine the factors that influenced transport time and develop a Google Maps application that would be more accurate than current estimates. Route mapping software was used, with inclusion of variables such as patient demographics, use of lights and siren, time of day, and weather. Individual variables that were statistically found to be insignificant were removed, one at a time, until the best model was derived.

Nearly 50,000 transports were analyzed to create the Google Maps application. Here’s what it looks like:

And here are the interesting findings:

• Without a model, baseline accuracy was only 16% within 5 minutes of predicted
• Transport times were longer during daytime and rush hour (gee!)
• Shorter times occurred with use of lights and siren (gee whiz!)
• Age, sex, wet roads, and trauma system entry had no effect on times
• Use of the model within the Google Maps app increased accuracy to 73% within 5 minutes. Use of lights and siren boosted the accuracy to 78%

Bottom line: Yes, it is possible to enhance the accuracy of arrival predictions of your ambulances. This method should be adopted everywhere! Not only can it improve trauma team use and trauma patient treatment, it can improve ED resource usage for any incoming patient.

Rreference: Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps. Prehospital Emergency Care online first, doi:10.3109/ 10903127.2013.811562.