motorcycle related crash victims and their associates hospital charges in illinois mehdi nassirpour...
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Motorcycle Related Crash Victims and Their
Associates Hospital Charges in Illinois
Mehdi NassirpourWei Wu
Illinois Department of Transportation Division of Transportation Safety
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Objectives
Overview of the Traffic Safety Programs Overview of Facts on Motorcycles Limitations of Crash Data Data Linkage Programs (CODES) Motorcycle Related injuries and Cost Results and Policy Implications Future Plans
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Illinois Highway Safety Program Areas
Occupant Protection Impaired Driving Speed Control Traffic Records Emergency Medical
Services Pedestrian/Bicycle Motorcycle Safety Large Truck Police Traffic
Services Distracted Driving
We are required to identify those programs most effective in reducing crashes, injuries, and deaths, and eligible use of highway safety funds awarded to the State of Illinois
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Highlights of Activities and Accomplishments
Coordinated with other highway safety programs during major safety campaigns (CIOT, YD&DYL, and Drive Sober or Get Pulled Over.
Student training has increased from 16,701 in 2009 to 20,361 in 2012, an increase of 21.9% annually.
Educational outreach has increased through educational/promotional events from 3 per year to 15 events in 2013.
Produced and aired first public informational videos for television in 2010 - 2013.
Developed and went online with www.STARTSEEINGMOTORCYCLES.org web site.
Developed and distributed a new “START SEEING MOTORCYLES” and “DON’T DRINK AND RIDE” poster for distribution at various locations statewide.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
What We Know about Motorcycles
Motorcyclists have high death rates
Motorcycle deaths are increasing
Motorcycles are becoming popular
About 50% of motorcycle driver deaths involved in Single vehicle crashes
Demographics--average age of riders is going up (37)
Engine size is increasing—The higher the engine size, the higher the probability of being fatally injured
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
What We Know about Motorcycles Rider Characteristics differ by types of
motorcycles Alcohol use is a problem among
motorcyclists Supersport motorcycles have the highest
overall collisions Motorcycles don’t have safety gear that is
comparable to what we found in passenger cars
Rider safety training and education tend to reduce motorcycle related crashes (based on anecdotal information) Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Helmet Laws Laws requiring all motorcyclists to wear a
helmet are in place in 19 states (Universal Helmet Law).
Laws requiring only some motorcyclists (most often age 17 and under) to wear a helmet are in place in 28 states.
Two states (Florida and Michigan) allow motorcyclists over the age of 21 to ride without helmet if they have a certain level of medical insurance (over $10,000 or $20,000).
There is no motorcycle helmet use law in 3 states (Illinois, Iowa, and New Hampshire).
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Motorcyclist Fatalities
2004 2005 2006 2007 2008 2009 2010 2011 2012 20130
200
400
600
800
1000
1200
1400
1600
157 158 132 157 135 130 131 145 148 155
1355 13631254 1248
1043911 927 918 956 991
Motorcycle Fatality Total Fatality
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Change in Composition of Fatalities
73.2%
2.5%
9.8%
14.4%
2003
Passenger vehicle occupants
Large trucks, buses & other vehicle occupants
Motorcyclists
Peds, bicyclists & other non-occupants
65.6%3.2%
15.3%
15.8%
2013
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Registered Motorcycles in Illinois by Year
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
0.0
50,000.0
100,000.0
150,000.0
200,000.0
250,000.0
300,000.0
350,000.0
400,000.02
62
,83
3
27
2,1
80
27
7,8
36
30
3,0
03
32
2,9
45
36
5,4
48
34
6,4
10
34
9,9
28
35
6,4
46
36
0,8
83
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Motorcycle Fatalities and Fatality Rate Per 100,000 Registered Motorcycles, by Year
(Illinois)2
00
4
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
0
20
40
60
80
100
120
140
160
180157 158
132
157
135 130 131145 148 155
Fatality Fatality Rate
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Motorcycle Fatalities and Fatality Rate Per 100,000 Registered Motorcycles, by Year
(US)2
00
4
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
0
1000
2000
3000
4000
5000
6000
Fatality Fatality Rate
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Percent No Valid Motorcycle License Among Motorcycle Riders Involved in Fatal Crashes by
Year (Illinois Versus US)
2004 2005 2006 2007 2008 2009 2010 2011 20120.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
16.8%
20.8%
26.3%
19.9%
16.5% 17.1%
8.3%9.3% 8.8%
20.8% 20.9%
22.4%
24.0%22.0%
19.4% 18.7%
22.1%20.8%
% No Valid Lic. (Illinois) % No Valid Lic. (US)
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Total Motorcycle Fatalities and Licensed Motorcyclists by Age (2010-
2012)
16 - 20
21 - 25
26 - 30
31 - 35
36 - 40
41 - 45
46 - 50
51 - 55
56 - 60
61+0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
3.8%
12.5%
10.4%
9.0%
10.8%
8.5%
11.3% 13.4%
9.4%
10.8%
1.6%
4.8%
6.7%7.7%
10.0%
11.9%
14.8%15.4%
12.4% 14.7%
% Fatlities % licensed MotorcyclistsPresented at the International Forum on Traffic
Records & Information Systems in St. Louis, MO
Percent Helmeted Motorcyclists who died in Motor Vehicle Crashes by Age
(2010-2012)
16 - 20
21 - 25
26 - 30
31 - 35
36 - 40
41 - 45
46 - 50
51 - 55
56 - 60
61+0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
50.0%43.8%
20.8%
25.0%
28.9%
10.9%
13.9%16.7%
12.3%
17.5%
32.6%
% Helmeted MootrcyclistPresented at the International Forum on Traffic
Records & Information Systems in St. Louis, MO
Motorcycle Fatalities, Total Injuries, and A-Injuries by Age Group (2010-2012)
Ages 0 to 15 Ages 16 to 20 Ages 21 to 34 Ages 35 to 44 Ages 45 to 64 Ages 65+0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
0.2% 2.
7%
35.0
%
19.5
%
37.9
%
4.7%
1.2%
6.9%
33.5
%
22.0
%
33.4
%
3.0%
1.1%
5.7%
29.7
%
24.4
%
36.2
%
2.9%
Fatalities Total Injuries A-Injuries
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Motorcycle Fatalities, Total Injuries, and A-Injuries by 23 County Model Location (2010-
2012)
County is in 23 County Model County is not in 23 County model0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
67.0%
33.0%
75.7%
24.3%
69.4%
29.6%
Fatalities Total Injuries A-Injuries
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Percent Fatalities by BAC Test in 2012
0.00 BAC 0.01 to 0.07 0.08 and greater No test given Test Performed, Results Unknown
0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%50.0%55.0%
48.3%
5.2%
32.0%
8.2%3.4%
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Motorcycle Fatalities, Total Injuries, and A-Injuries by Time of Day (2010-2012)
3AM to 6AM 6AM to 9AM 9AM to NOON NOON to 3PM 3PM to 6PM 6PM to 9PM 9PM to MIDNIGHT
MIDNIGHT to 3AM-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
4.7%
4.7%
9.1%
14.5
%
24.1
%
21.9
%
11.8
%
9.1%
2.3%
5.9%
9.7%
20.5
%
25.5
%
19.5
%
11.0
%
5.7%
2.8% 4.
7%
9.6%
20.1
%
24.9
%
20.0
%
11.5
%
6.4%
Fatalities Total Injuries A-Injuries
Motorcycle Helmet Use for Fatalities, Total Injuries, and A-Injuries by Time of Day (2010-2012)
3AM to 6AM 6AM to 9AM 9AM to NOON NOON to 3PM 3PM to 6PM 6PM to 9PM 9PM to MIDNIGHT
MIDNIGHT to 3AM
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%45.0%
5.3%
10.5%
29.7%
28.8%
25.5%
24.7%
4.2%
5.4%
31.8%
42.8%37.8%
30.2% 28.5%31.9%
13.1%
23.7%25.0%
39.1%32.3%
27.8%
25.3%
25.5%
10.6%
19.7%
Fatalities Total Injuries A-Injuries
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Illinois Data Linkage Project (Crash Outcome Data Evaluation System)
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
What is CODES?
Crash Outcome Data Evaluation System CODES evolved from the (Intermodal
Surface Transportation Efficiency Act of 1991 (ISTEA 1991)--ISTEA mandated that National Highway Traffic Safety Administration (NHTSA) to prepare a report to Congress about the benefits of safety belt and helmet use.
NHTSA sponsored the CODES projects and awarded grants to several states to link their databases.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
CODES (Data Linkages) Provide funding to states to link their existing
traffic-safety related databases Injuries resulting from motor vehicle crashes
is a major public health problem. Injuries can be prevented, or reduced, if we
understand their type, severity and cost. Crash data alone do not indicate the injury
problem in terms of the medical and financial consequences.
By linking crash data to their specific medical and financial outcomes, we can identify prevention factors.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Strategy Link crash report records to medical
treatment records in a computer database to learn the full story
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Data Linkage ModelBayesian Statistical Theory—The
main objective of this theory is to calculate the probability of an uncertain claim in light of prior information and new experimental evidence.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
CODES2000/Linksolve Linkage Software
• It is developed by Strategic Matching , Inc. that had contract with NHTSA.
• It is a probabilistic records Linkage Software that includes effective algorithms for data preparation, analysis, and comparison.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Benefits of Linked Data
Linked data can be disaggregated to provide information to local communities.
Linkage enhances the value of each state data file being linked by expanding the comprehensiveness of each state data set.
Linkage provides access to more detailed medical information for highway and traffic safety evaluation; and linkage provides more detailed safety information for injury control purposes.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Benefits of Linked Data
Collaboration of traffic safety and health care communities
The linked data can be used by multiple users for different purposes.
The linked data process results in increased data quality.
Linking data encourages standardized and computerization of state data.Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Linked Data Process in (2010-2011)
Hospital Inpatient and Emergency Department (ED) Database
Crash
Total Crash Victim= 1,323,842
Linked Total=105,828 Outpatient =98,829Inpatient=6,999
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Total Hospital Records= 2,454,006
Frequency and Percentage Distribution of All Crashes and Motorcycle Crashes
All Crash persons
Motorcycle Occupants
Individuals involved in Crash
Frequency
Percent Frequency
Percent
Total hospital discharge data used for the linkage
2,454,006 100.0%
- -Total inpatient discharge records
192,238 7.83%- -
Total outpatient discharge records
2,261,768 92.2%- -
Total number of individuals involved in crashes
1,323,842 100.0% 8,647 100.0%
Linked hospital inpatients
7,000 0.53% 1,102 12.7%
Linked hospital Outpatient
98,828 7.5% 3,331 38.5%
Linked crash individuals (in & out)
105,828 8.0% 4,433 51.3%
Not linked crash individuals
1,218,014 92.0% 4,214 48.7%Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Percent Total Inpatient and Outpatient Motorcycle Occupants by Gender
Male Female0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%82.8%
17.2%
85.1%
14.9%
82.0%
18.0%
Total Inpatient Outpatient
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Percent Total Inpatient and Outpatient Motorcycle Occupants by Age Group
Ages 0 to 15 Ages 16 to 20 Ages 21 to 34 Ages 35 to 44 Ages 45 to 64 Ages 65+0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
1.0%
6.2%
31.8
%
20.6
%
36.6
%
3.8%
0.5%
4.6%
29.9
%
22.1
%
37.2
%
5.6%
1.2%
6.7%
32.4
%
20.1
%
36.4
%
3.2%
Total Inpatient Outpatient
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Motorcycle Fatalities, Total Injuries, and A-Injuries by Age Group (2010-2011)
Ages 0 to 15 Ages 16 to 20 Ages 21 to 34 Ages 35 to 44 Ages 45 to 64 Ages 65+0.0%5.0%
10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%50.0%
0.7%
4.4%
29.9
%
14.6
%
44.1
%
6.3%
1.0%
6.1%
31.4
%
20.6
%
37.0
%
3.9%
0.8%
5.4%
28.0
%
21.5
%
40.3
%
3.9%
Fatalities Total Injuries A-Injuries
Helmet Use by Age
Age 0 to 15
Age 16 to 20
Age 21 to 24
Age 25 to 34
Age 35 to 44
Age 45 to 54
Age 55 to 64
Age 65 to 74
Age 75 & Over
30.00%
35.00%
40.00%
45.00%
50.00%
55.00%
60.00%
65.00%
70.00%
60.22%
49.85% 49.70% 49.07%
45.50%
42.68%
48.48%
60.22%
67.21%
52.47%
45.94%
43.81%
41.55%
38.38%37.09%
44.04%
56.81%
58.77%
All People Involved Linked Injury
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Frequency and Percentage Distributions of Linked Motorcycle Occupants By
Helmet Status
Helmeted Not Helmete
d
Miscoded/Not
Available
Inpatient Discharge
393(35.7%)
706(64.1%)
3(0.2%)
Outpatient Discharge (ED)
1442(43.3%)
1872(56.2%)
16(0.5%)
Total Hospital Discharge
1835(41.4%)
2578(58.2%)
19(0.4%)
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Percent Head Injuries by Helmet Status
Helmeted Not Helmeted0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
12.3%
22.9%
Total helmeted with head injury =225Total helmeted with no head injury=1610
Total Not helmeted with head injury =590Total Not helmeted with no head injury=1988
Note: the relationship between Helmet use and head injury is significant. Odd Ratio (OR) value is over 0.34 indicates that wearing helmet a protective against head injury.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Frequency and Percentage Distributions of Helmet Use and Head
Injury
Helmet UseNo
Injury Minor
Moderat
e Serious Severe Critical
No Helmet 2005 150 169 68 162 43
%77.20% 5.78% 6.51% 2.62% 6.24% 1.66%
Helmeted1610 37 93 31 52 12
%87.74% 2.02% 5.07% 1.69% 2.83% 0.65%
All3615 187 261 99 214 55
%81.58% 4.22% 5.89% 2.23% 4.83% 1.24%
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Average Hospital Charge Per Discharge
All Crash Victims
Motorcycle Occupants
Inpatient Discharge
$68,659 $86,703
Outpatient Discharge (ED)
$4,407 $7,576
Total Hospital Discharge
$8,657 $27,248
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Average Hospital Charge by Age
Age 0 to 15
Age 16 to 20
Age 21 to 24
Age 25 to 34
Age 35 to 44
Age 45 to 54
Age 55 to 64
Age 65 to 74
Age 75 & Over
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
$42,356
$98,584
$78,475
$89,154 $87,428$82,933
$97,206
$76,403
$44,997
$5,608$7,097 $7,224 $7,228 $7,772 $7,803 $8,240 $7,443 $5,693
$10,387
$23,962$21,378
$27,920 $28,967$26,455
$31,405 $32,200
$22,932
Inpatient Outpatient All
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Average Hospital Charge Per Discharge (Mean)
Helmeted
Not Helmete
d
Percent Differenc
e
Inpatient Discharge $86,644 $86,737 0.11%Outpatient Discharge (ED) $6,936 $8,065 16.28%Total Hospital Discharge $24,015 $29,532 22.97%
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Average Hospital Charge Per Discharge (Median)
Helmeted
Not Helmete
d
Percent Differenc
e
Inpatient Discharge $44,928 $45,505 1.28%Outpatient Discharge (ED) $3,931 $5,246 33.44%Total Hospital Discharge $6,028 $9,015 49.56%
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Mean Charges by Gender
Female Male$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
$100,000
$84,450 $87,042
$7,763 $7,537
$23,208$28,024
Mean Charges (Inp) Mean Charges (Out) Mean Charges (All)
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Research Questions
What variables predict a head injury?
What Variables Predict Hospital Charges
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Definition of Selected Variables
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Variables Definition Gender Dummy variable with a value of 1 for male occupants and 0 for female occupants
Age Self-explanatoryOccupant Type Dummy variable with a value of 1 for operator and 0 for passenger Time of Day Dummy variable with a value of 1 for occupants involved in nighttime crashes
(6:00PM – 5:59AM) and 0 for occupants involved in daytime crashes (6:00AM – 5:59PM)
Day of Week Dummy variable with a value of 1 for occupants involved in weekend crashes and 0 for occupants involved in weekday crashes
Crash Location Dummy variable with a value of 1 for occupants involved in crashes on rural roads and 0 for occupants involved in crashes on other roads
Alcohol Involvement
Dummy variable with a value of 1 for occupants involved in alcohol related crashes and 0 for all other occupants
Helmet Use Dummy variable with a value of 1 for occupants wore helmet in crashes and 0 for all unprotected occupants involved in crashes
Injury location Dummy variable with a value of 1 for occupants experienced head injury from crashes and 0 for all other occupants who do not have head injury from crashes.
Intersection Related
Dummy variable with a value of 1 for occupants who are involved in Intersection-related crashes and 0 for all other occupants who are not involved in intersection-related crashes
Hospital Charges Total hospital charge per discharge
Result of Logistic Regression Analysis on Head Injury
SELECTED VARIABLES EstimateStd
ErrorChi
Square P-value Odd Ratio
Intercept -2.2045 0.0850 672.5434 <.0001
HELMET STATUS (HELMETED=1) -0.6540 0.1026 -6.38 <.0001 0.519
ALCOHOL IMPAIRMENT (IMPAIRED=1) 0.6884 0.1094 6.29 <.0001 1.237
GENDER (MALE=1) 0.2127 0.1646 1.29 0.1967 1.237
AGE 0.0093 0.0029 3.17 0.0015 1.009
RURAL/URBAN (RURAL=1) -0.0124 0.0949 -0.13 0.8959 0.990
TIME OF CRASH (Night=1) 0.2952 0.0869 3.4 0.0007 1.047
DAY OF WEEK (WEENKEND=1) 0.0476 0.0853 0.56 0.5771 1.127
OPERATOR/PASSENGER (OPERATOR=1) 0.1164 0.2125 0.55 0.5846 0.840
INTERSECTION-RELATED (INTERSECTION=1) -0.1742 0.0877 -1.98 0.0473 1.066
SPEED RELATED (SPEED=1) 0.0617 0.0963 0.64 0.524 1.749
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Results of Regression Analysis on Hospital Charges
SELECTED VARIABLES EstimateStd
Error t Value Pr > |t|
Intercept 8.385294647 0.04118056
203.62 <.0001
HELMET STATUS (HELMETED=1) -0.117429630
0.01826189
-6.43 <.0001
ALCOHOL IMPAIRMENT (IMPAIRED=1)
0.253635155 0.02833548
8.95 <.0001
GENDER (MALE=1) -0.125676045
0.03295624
-3.81 0.0001
AGE 0.007631491 0.00064118
11.90 <.0001
RURAL/URBAN (RURAL=1) -0.078932129
0.01999662
-3.95 <.0001
TIME OF CRASH (Night=1) 0.056650762 0.01925361
2.94 0.0033
DAY OF WEEK (WEENKEND=1) 0.011761866 0.01812550
0.65 0.5164
OPERATOR/PASSENGER (OPERATOR=1)
0.264075735 0.04015645
6.58 <.0001
HEAD/NO HEAD INJURY (HEAD INJURY=1)
0.483135120 0.00781381
61.83 <.0001
INTERSECT RELATED (INTERSECTION=1)
-0.116574196
0.01882384
-6.19 <.0001
SPEED RELATED (SPEED=1) 0.140418178 0.01897580
7.40 <.0001
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Definition of Serious Injury
The FHWA recommends “serious injuries” as “`suspected serious injury' (A)” as identified in the latest edition of the MMUCC. The MMUCC definition of a suspected serious injury (A) is any injury, other than fatal, which results in one or more of the following:1. Severe laceration resulting in exposure of underlying tissues,
muscle, organs, or resulting in significant loss of blood;2. Broken or distorted extremity (arm or leg);3. Crush injuries;4. Suspected skull, chest, or abdominal injury other than bruises or
minor lacerations;5. Significant burns (second and third degree burns over 10 percent or
more of the body);6. Unconsciousness when taken from the crash scene; or7. Paralysis.(Illinois Definition: severe lacerations, broken limbs, skull or chest injuries, and abdominal injuries)
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Problem with Definition of Serious Injury
The DOT also recognizes that as serious injury data is migrated to the MMUCC definition, variances may occur in the data collected and reported by States and that States should make necessary adjustments in establishing targets to accommodate these changes.
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Proposed Solution
Finally, in section 490.207(d), the FHWA recommends, but would not require, that States prepare themselves so that no later than calendar year 2020, serious injuries data is collected through and reported by a hospital records injury outcome reporting system that links injury outcomes from hospital inpatient and emergency discharge databases to crash reports. An example of a crash outcome data linkage system is the NHTSA Crash Outcome Data Evaluation System (CODES).
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Comparing KABCO to MAIS Categories
Max AIS Score by Crash Severity Level for Year 2010-2011
Max AIS Property
Damaged Only Mild Moderate Incapacitated Killed Total
Scores N % N % N % N % N % N %
No Injury 1 0.5% 4 1.9% 23 1.0% 14 0.8% 13 9.5% 55 1.2%
Mild 136 66.7% 154 67.0% 1267 58.4% 524 31.0% 24 17.9% 2105 47.5%
Moderate 53 25.9% 59 25.5% 648 29.9% 609 36.0% 23 16.7% 1391 31.4%
Serious 7 3.3% 7 3.2% 150 6.9% 325 19.2% 27 19.8% 516 11.6%Severe 6 3.0% 5 2.3% 75 3.5% 197 11.6% 12 8.6% 295 6.7%Critical 1 0.7% 0 0.0% 7 0.3% 24 1.4% 37 26.8% 69 1.6%
Maximum 0 0.0% 0 0.0% 0 0.0% 1 0.1% 1 0.7% 2 0.0%
All 203 100.0% 230 100.0% 2169 100.0% 1694 100.0% 137 100.0% 4433 100.0%
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Future Plan
Complete the analysis of the linked data
Develop a comprehensive profile of Motorcyclists who injured in motor vehicle crashes using 2012 data
Produce Fact Sheets and reports on several traffic safety issues
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO
Contact Information Mehdi NassirpourWei WuDivision of Traffic Safety at IDOT1340 North 9th Springfield, IL 62702Email: [email protected]
DTS’ Evaluation Website:http://www.dot.il.gov/trafficsafety/tsevaluation.html
Contact Information Mehdi NassirpourWei WuDivision of Traffic Safety at IDOT1340 North 9th Springfield, IL 62702Email: [email protected]
DTS’ Evaluation Website:http://www.dot.il.gov/trafficsafety/tsevaluation.html
Presented at the International Forum on Traffic Records & Information Systems in St. Louis, MO