County of San Diego Division of Emergency Medical Services EMS Practical Application of Traffic...

County of San Diego Division of Emergency Medical Services

EMS

Practical Application of

Traffic Records

Barbara M. Stepanski, MPH;

Janace Pierce, MS;

Margaret Lutz, BA;

Dale Cooper;

Leslie Upledger Ray, MA, MPPA; Edward Castillo, PhD, MPH;

Alan Smith, MPH


EMS

Background

• There is a wealth of traffic record data now available

• The real usefulness is in sharing this with the community, so responsive and targeted interventions/programs may be developed


EMS

Background

• Patient record databases used to develop injury prevention campaigns– Prehospital patient records/run sheets

– EMS Surveillance

– Trauma Registry

– Medical Examiner

– State-Wide Integrated Traffic Records (SWITRS)

– Child Safety Seat Inspection


EMS

Background

• Prehospital, Trauma and ME records contain patient related data– Demographics -Injury and medical

– Location of incident -Transport logistics

• SWITRS records provide incident level data– Type of incident (vehicle type, location etc.)– Number of people involved, especially those not injured– Information on party at fault, contributing factors and violations– Incident specifics (road/weather conditions, speed)

• All critical in developing effective injury prevention campaigns


EMS

Example 1

Emergency Medical and Injury Atlas

• Designed to visually display tabular data using choropleth mapping

• Overall county and by regions• Contained information on injured patients by

incident category (MV, MC, pedestrian)– Prehospital

• Paramedic/EMT response

– Trauma Registry• Severe injury

– ME• Deaths

East Region

N

EW

S

Imp

eri

al C

oun

ty

SouthRegion

North CentralRegion

North Inland Region

North CoastalRegion

Pacific Ocean

Riverside County

Mexico

CentralRegion

5 0 5 10 Miles

Rates of Pedestrian Injury Resulting in Paramedic/EMT ResponseBy Subregional Area - FY 99/00

Source: County of San Diego, Health and Human Services Agency, Division of Emergency Medical Services, April 2002.Prehospital Patient Records, FY 99/00, Population Estimates: San Diego Association of Governments (SANDAG), 2000.* Rates not calculated on incidence less than 5.

Health ServicesRegion Border

SubregionalArea Border

Rate per 100,000 Population

0.00 - 20.00

20.00 - 40.00

40.00 - 60.00

60.00 - 80.00

80.00 - 100.00

Incidence < 5 *

CO

-9


EMS

Research Question

• Atlas identified the central San Diego community as having the highest rate of pedestrian injuries – why?

• Community felt it was due to high number of drunk pedestrians

• Investigators used SWITRS data to determine– Party at Fault Demographics– Victim Demographics– Causality and Violation– Incident location/logistics

Central Region Rates of Pedestrian Injury Resulting in Paramedic/EMT Response By Subregional Area - FY 99/00

Source: County of San Diego, Health and Human Services Agency, Division of Emergency Medical Services, April 2002.Prehospital Patient Records, FY 99/00; Population Estimates: San Diego Association of Governments (SANDAG), 2000.* Rates not calculated on incidence less than 5.

Health ServicesRegion Border

SubregionalArea Border

Rate per 100,000 Population

N

EW

S

0.00 - 20.00

20.00 - 40.00

40.00 - 60.00

60.00 - 80.00

80.00 - 100.00

Incidence < 5 *

C-9

0.5 0 0.5 1 1.5 Miles

Southeast San Diego

Mid-City

Central San Diego

Pacific Ocean

$

$

$

$

$

$

$

$

$

$

$

$

$

$$

$

$

$

$

$$

$

$

$

$

$

$$

$

$

$

$

$

$

$

$ $$

$

$

$

$

$$

$

$

$

$

$

$

$

$ $

$$

$$

$

$

$ $

$

$

$

$$

$

$

$

$

$

$

$

$$

$

$

$

$

$

$

$

$

$$

$

$

$

$

$

$

$

$$

$

$$$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$$

$

$

$

$

$$

$

$

$

$

$

$

$

$$

$

$ $

$

$

$

$

$

$

$

$$

$

$

$

$

$

$

$

$

$

$$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$ $

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

$

San DiegoBay

I-8

I-5

SR-163

SR-94

I-805

I-5

I-15

Balboa Park

CORONADO

Pedestrian Crashes in

Central San DiegoDriver At FaultPedestrian at Fault

Unknown/Equipment/Signals/Other

$$$

Parks%UCentral San DiegoSub-Regional Area

%U

Produced by County of San Diego Health and Human Services Agency, Emergency Medical Services.

N

Data Source: SWITRS FY 96/97 Incomplete 8/98.

Every reasonable effort has been made to assure the accuracy of this map. However, neither the SanGIS participants nor San Diego Data Processing Corporation assume any liability arising from its use.

0.6 0 0.6 1.2 Miles

Pedestrian Crashes in the Gaslamp Area of San Diego

%$

%

$ $

$$

$

%

$$

$

%

$

$ $

$

$

$$

$

$

$

$

$BROADWAY

MARKET

HARBOR

Convention Center

Horton Plaza

E

F

G

ISLAND

J

04TH

01S

T

STA

TE

KE

TTN

ER

08TH

N

Driver At FaultPedestrian at Fault

Driver UI Alcohol/Drugs

Pedestrian UI Alcohol/Drugs

Unknown/Other

%

%

$$$


San Diego Trolley

San

Die

go T

rolle

y

Parks%UCentral San DiegoSub-Regional Area

%U



0 400 800 1200 Feet

%$

%

$

$

%

$

$$

$

%

$$

$

%

$

%

$

$ $

$

$

$

$$

$

$

$

$

$

0 400 800 1200 Feet




$$$

%

%

Unknown/Other

Pedestrian UI Alcohol/Drugs

Driver UI Alcohol/Drugs

Pedestrian at FaultDriver At Fault

N

Pedestrian Crashes in the Gaslamp Area of San Diego


EMS

Conclusions

• Contrary to community opinion pedestrian crashes were rarely due to PUI (pedestrian under the influence)

• Most common violations were failure to yield (driver turning right and looking left) and crossing outside of a crosswalk (jaywalking)

• Community refocused pedestrian injury prevention campaign to emphasize these issues


EMS

Example 2

Pediatric Pedestrian Injuries

• One out of every seven injury calls for paramedic assistance to a child under age 15 was for pedestrian related injury

• With these high numbers investigators questioned the logistics associated with such incidents

• It was hypothesized that hours in which children travel to and from school would have an increased number of pedestrian injury crashes


EMS

Research Questions

• How does prehospital data compare with SWITRS data for child pedestrian crashes?

• How are child pedestrian injuries distributed– Demographically (age, gender, race/ethnicity)– Temporally (Day/night, day of week)– Geographically

• What were the actions of the driver and the pedestrian leading up to the crash?


EMS

Pedestrian Action by Age

0% 10% 20% 30% 40% 50% 60% 70%

Not Stated

Crossing in Crosswalk atIntersection

Crossing in CrosswalkNot at Intersection

Crossing, Not inCrosswalk

In Road, IncludingShoulder

Not in Road

Approaching/LeavingSchoolbus

1 to 4 5 to 9 10 to 14

Source: County of San Diego Health and Human Services Agency, Division of Emergency Medical Services, SWITRS database, FY 96/97 – 99/00


EMS

Pediatric PedestrianWhere and When?

Mid-City SRA• The highest incidence

– 99/100,000 for Prehospital– 135 /100,000 for SWITRS

• Hours of Day – high incidence of injuries occurred during school travel times (7-9am and 2-6pm)

– 45/100,000 for Prehospital– 66/100,000 for SWITRS

#Y

#S

#Y

#Y

#S

$Z

$Z

$T$Z

$Z

$Z

$T

$T

%[

%U

%[

#Y

#S#S

$Z

$Z

$Z

$Z$T

$T

$T

$Z

$Z

%[

%U

%[

%[

%[

%U

#S

#Y

#S

$Z

$Z

$T

$Z

$Z

$Z

$Z

%[

%[

%[

%[

%[

%[

%[

%[

%[

%U

%U

#Y

#Y

#Y

#S

$Z

$Z$Z

$Z$T

$T

$Z

$Z

$Z

$T

%[

%[

%[ %U

÷

÷

÷

÷

÷

÷

÷÷

÷

÷

÷

÷

÷

÷

÷

÷

÷

÷

÷ ÷

÷

÷ ÷

÷

÷

÷

÷

÷

÷

÷

÷ ÷

÷

÷

÷

÷

÷

÷÷

÷

÷

÷

÷

÷÷

÷

÷

÷

÷ ÷

÷÷

÷

÷

÷

÷

÷

÷

÷

N

EW

S

%[

%U

%[

%U

Male-Non School Travel Hours

Male-School Travel hours

Female-School Travel hours

Female-Non School Travel Hours

Ages 10-14

Ages 5-9





$T

$Z

$T

$Z

#Y

#S

#Y

#S





Ages 0-4

Source: SWITRS FY 96/97County of San Diego Health and Human Services Agency, Emergency Medical Services, 1999

÷

%U

Schools

Parks

I-8

Fairmount

Orange

54th

University

El Cajon Blvd

I-15

I-805

Source: SWITRS FY 96/97County of San Diego Health and Human Services Agency, Emergency Medical Services, 1999

0.3 0 0.3 0.6 Miles

Child Pedestrian Crashes in Mid-City Sub-Regional AreaBy Age Group, Gender, and School Travel Hours


EMS

What Were They Doing?

• 52% of the children injured were crossing the street outside of a crosswalk

• The proportion struck while crossing outside of a crosswalk decreased with increasing age (57% aged 0-4; 59% aged 5-9; 42% aged 10-14)

• 26% of the children injured were crossing the street at a crosswalk (55% were aged 10-14)

• Contrary to common belief, only 4 (<1%) of the 1234 students were injured while approaching or leaving a school bus


EMS

Results

• Most (46% of the Prehospital and 51% of the SWITRS) cases occurred in the hours children travel to and from school, which is 25% of the weekday hours.

• Mid City area made up 6.8% of the county’s population under age 15, but accounted for 14% of the Prehospital and 15% of the SWITRS pedestrian incidents in this age group.

• Victims were 60% male in Prehospital, 59% SWITRS


EMS

Conclusions

• At the county level, the distribution of pedestrian injuries mirrors population density patterns.

• Childhood pedestrian injuries tend to cluster in time according to when children may be walking to or from school.

• School bus associated injuries do not contribute to pedestrian injuries to the degree previously thought.

• Most childhood pedestrian injuries can be attributed to unsafe street-crossing behavior by the child.


EMS

Example 3

Elderly Drivers

• Concerns– Physical limitations

– Possibly higher crash rates

– More severe injuries due to fragility of aging bodies

• Proposed license restrictions– Reverse graduated licensing


EMS

Elderly DriversPopulation

• Nationally, 70+ age group increased 2.1 times faster than the total population from 1989 to 1998

• Locally, the population over 55 is expected to more than double by 2020

• The number of drivers and collisions are expected to increase proportionally


EMS

Elderly DriversResearch Questions

• What is the crash rate in elderly?– Compared with other age groups– Severity

• What factors contribute to crashes involving elderly drivers?

• What impact do older drivers have on the overall population?


EMS

SWITRS

Percent of Drivers at Fault by Age*

51%

41%37% 36% 36%

44%

59%63%59%

0%

10%

20%

30%

40%

50%

60%

70%

15-19 20-24 25-34 35-44 45-54 55-64 65-74 75-84 85+

Source: SWITRS Database, FY 99/00

*Drivers at fault/Drivers in injury collisions

%


EMS

SWITRS

Rate (per Licensed Drivers) of At-Fault Collision by Age*

2396

1379

671494 412 358 365

532821

0

500

1000

1500

2000

2500

3000

15-19 20-24 25-34 35-44 45-54 55-64 65-74 75-84 85+

Age Group

Rat

e p

er 1

00,0

00

Source: SWITRS Database, FY 99/00

*Drivers at fault/Licensed drivers


EMS

Conclusions

• Crash rates and at-fault rates are lower in seniors than previously thought

• Crash rates of 55-64 and 65-74 are comparable to middle-aged drivers

• Highest crash and fault rates in youngest drivers (16-24)

• Percent at fault comparable to 16-24 year-olds


EMS

Conclusions (cont.)

• Results question the proposed restrictions on elderly drivers, which may be detrimental to their independence

• Results support the need to focus safe driving interventions on young drivers


EMS

Example 4

Child Safety Seat Studies

• Prehospital data provides child safety seat use rates for those children injured in a crash

• SWITRS records provide child safety seat use rates for those children involved in injury crashes, violations, faults

• Seat inspections provide child safety seat misuse rates for those inspected


EMS

Child Safety Seat Studies - Results• Prehospital setting

– 8% of children 0-9 seen by paramedics/EMTs are due to MV crashes

• 50% 0-4 YO are not restrained in a child seat– 11% of 0-4 YO are completely unrestrained

• 20% of 5-9 YO are completely unrestrained• Child passengers of impaired drivers were significantly (p=.03) less

likely to wear active restraints than passengers in crashes where the other driver was at fault.

• CSS Inspections– No inspection events occurred in the most densely populated

0-9 year old population areas

– Majority of participants traveled up to 15 miles to attend an event


EMS

Why Are Traffic Records Important to Public Health?

• Contain critical information on the event– How it happened?– Who was involved?– What they did/last action?– Who was at fault?– What were the contributing factors?

• This information allows public health to develop prevention campaigns that target the event not the injured victim


EMS

Acknowledgements

The investigators would like to thank

Buckle Up San Diego

San Diego Safe Communities 2000

San Diego Safe Kids Coalition

San Diego County Prehospital Agencies, Hospitals, and Paramedics/EMTs

For more information please contact:Barbara M. Stepanski, MPH

County of San Diego HHSA Division of Emergency Medical Services

6255 Mission Gorge Road

San Diego, CA 92120

phone - (619) 285-6429

[email protected]

County of San Diego Division of Emergency Medical Services EMS Practical Application of Traffic...

Documents

Transcript of County of San Diego Division of Emergency Medical Services EMS Practical Application of Traffic...