Acknowledgements. n Research team: Dr. Bingham (PI), Dr. Carter, Dr. Flannagan, Mr. Bowman, Ms. Almani

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Evaluation of crash-related fatalities and serious injuries associated with the Michigan Motorcycle Helmet Law Repeal Utilizing Linked Crash and Hospital-Level Data Dr. Lisa Buckley

Acknowledgements n Research team: Dr. Bingham (PI), Dr. Carter, Dr. Flannagan, Mr. Bowman, Ms. Almani n Funder: Insurance Institute for Highway Safety n Dr. Mark Hemmila and Michigan Trauma Quality Improvement Program, MTQIP

National picture

1975-2012 Deaths of motorcyclists and vehicle occupants in the US 40,000 10,000 30,000 8,000 6,000 20,000 4,000 10,000 0 passenger vehicles motorcyclists 1975 80 85 90 95 2000 05 10 2,000 0 IIHS - http://www.iihs.org/iihs/topics/presentations

Map of motorcycle helmet laws March 2014 WA OR CA NV ID MT UT AZ WY CO NM ND SD NE KS OK TX MN IA MO AR LA WI IL MS MI IN OH KY TN AL GA NH VT ME NY MA PA NJ RI WV CT VA DE MD NC DC SC universal law AK FL partial law no law HI IIHS - http://www.iihs.org/iihs/topics/presentations

April 12, 2012 Michigan law now allows motorcyclists to decide for themselves, if certain conditions are met, whether or not to wear a helmet. To legally not wear a helmet, a motorcycle operator must: Be at least 21 years old. Have at least $20,000 in first-party medical benefits. Have held a motorcycle endorsement for at least two years, or have passed an approved motorcycle safety course. Secretary of State, Department of State http://www.michigan.gov/sos/0,4670,7-127-1585_50413-277037--,00.html

Project aims Examine impact of repeal of motorcycle helmet law: crash data trauma data observation study

Trauma Registry Data From consortium, The Michigan Trauma Quality Improvement Program (MTQIP) 23 adult Level 1 and 2 Trauma Centers De-identified individual patient-level data Most complete source for a statewide assessment of hospital data

Michigan State Police (MSP) crash records Crashes: occur on a public roadway involve a personal injury or property damage of >$1000 or more. Record a measure of crash severity: fatal, disabling, nondisabling, possible injury, property damage only. Fatal crashes are within 30 days. Includes: location, circumstances, description of the crash, the vehicle, and occupants

Key definitions Motorcycle: two- / three-wheeled, motorized, with minimum engine size of 50cc road-legal vehicle Helmet: Identified in crash or trauma data as wearing a helmet Dataset dates: Jan 1, 2011 to Dec 31, 2013

Benefits to data linkage More complete picture incorporates what happens at the scene and hospital Allows an understanding of where the crashes occur, the outreach of a hospital Allows us to examine change in deaths at the scene compared deaths in ED Allows validation of data e.g. helmet wearing rates

Data linkage Used probabilistic linkage Includes all motorcyclists or moped riders Linked on age, sex, hour of crash (within 1hr) Included when one trauma record matches only one crash record Excludes motorcyclists who crashed and died at scene or were not transported to a Level- 1/Level-2 hospital

Data Linkage Challenges Transfer patients there is a separate entry for each hospital case and need to link each person. As transfer patients are not a random sample of injured motorcyclists it was important to link them. Needed to hand code each transfer case. Ties e.g. same crash, two motorcyclists, same year of birth.

Sample Demographics & Helmet Use Before After Mean age (years) 44.75 44.33 Percent helmet wearing 91.97 62.90 Males percent helmet wearing 85.08 63.73 Females percent helmet wearing 92.98 57.83

percent Crash Severity Police Reported 50 45 40 35 30 25 20 Before After 15 10 5 0 Killed Disabling Injury Nondisabling Injury Possible Injury No Injury

Percent of crashes by speed limit 40 35 percent crashes 30 25 20 15 10 5 Before After 0 15 20 25 30 35 40 45 50 55 60 65 70 Speed

Fatality Rates Percent Before After Discharge from ED as death 3.00 2.19 Discharge from Hospital as death 5.82 5.39 Overall Crash data (includes death within 30 days of crash) 6.38 6.75

ISS Score, GCS Score, Surgical/ Operative Intervention Before After Mean ISS 15.18 15.19 % GCS >8 88.19 88.32 % Surgery 31.78 39.29

Clinical Case Definition (CDC) Occurrence of injury to the head with one or more of: Observed or self-reported decreased consciousness (i.e. Concussion) Amnesia Skull fracture Objective neurological or neuropsychological abnormality Diagnosed intracranial lesion (e.g. Epidural, Subdural, SAH, Intracerebral)

ICD-9 Codes 800.0-801.9 - Fracture of the vault or base of the skull 803.0-804.9 - Other and unqualified and multiple fractures of the skull 850.0-854.1 - Intracranial injury, including concussion, contusion, laceration, and hemorrhage. Additional TBI cases from death certificates: 873.0-873.9 Other open wound of head.

percent Overall head injury 60 50 40 30 20 10 0 Before After (46.15%) (56.32%)

percent Skull fracture 16 14 12 10 8 6 4 2 0 Before After (9.38%) (14.84%)

percent Intracranial injury 45 40 35 30 25 20 15 10 5 0 Before After (38.84%) (40.64%)

percent Open head wound 30 25 20 15 10 5 0 Before After (14.82%) (26.14%)

ICU & Ventilator Days Mean No. of Days Before After ICU 2.604 2.897 Ventilator 1.465 1.582

percent Alcohol Involved Crashes 40 35 30 25 20 15 10 5 Before After 0 Alcohol Positive % above.08 Mean BAC when alcohol positive: Before=.0449; After=.0529

Odds of head injury type with nonhelmet use Odds Ratio Confidence Interval Any head injury 3.38 (2.42-4.69) Intracranial injury 1.93 (1.44-2.59) Skull fracture 3.79 (2.56-5.59) Open head wound 3.12 (2.23-4.33) Alcohol is also a significant predictor of head injury

Head Injury by Rider Helmet Use and BAC Before and After Repeal Before (N=369) After (N=434) BAC 0.08 (n = 283) BAC > 0.08 (n = 86) BAC 0.08 (n = 332) BAC > 0.08 (n = 102) Helmet 94.7% 76.7% 65.6% 51.0% No Helmet 5.3% 23.3% 34.4% 49.0%

Next steps In-depth examination of head injuries Evaluate in- vs. out-of-hospital mortality Prior literature has reported possible shift in fatalities from hospital environment to out-ofhospital with helmet law repeal Explore whether those already at high-risk before repeal (i.e. drunk riders) are now population shifting to unhelmeted drunk riders explaining lack of change in mortality

Thank you lisadb@umich.edu