1. Can Linking Motor Vehicle Crash (MVC) Data Improve MVC Injury Surveillance? Jennifer Jones, MPH Anna Waller, ScD August 8, 2016 2016 Traffic Records Forum

2. Disclaimers Funding Source: The work was funded through a grant by the North Carolina Governor's Highway Safety Program. Data Disclaimer: NC DETECT is a statewide public health syndromic surveillance system, funded by the NC Division of Public Health (NC DPH) Federal Public Health Emergency Preparedness Grant and managed through collaboration between NC DPH and UNC-CH Department of Emergency Medicine’s Carolina Center for Health Informatics. The NC DETECT Data Oversight Committee does not take responsibility for the scientific validity or accuracy of methodology, results, statistical analyses, or conclusions presented.

3. Background

4. MVCs are one of the leading causes of fatal and unintentional injury in the U.S. 32,675 people killed 2,338,000 people injured 6,064,000 people involved in crash (DMV) **Statistics are from the 2014 NHTSA Traffic Facts

5. Sources of MVC Injury Data Police Crash Reports Emergency Medical Services (EMS) Data Medical Record Data KABCO Injury Scale Data SourcesInjury Classification Disposition, patient injured, primary impression, chief complaint Diagnostic codes, disposition, triage notes, chief complaint

6. What is Data Linkage? Used to link data from more than one source Challenging if there are no common unique patient identifiers (e.g. Social Security #, First and Last Name, Drivers License #) Types of linkages: 1.Deterministic: data sources must have an exact match on all linkage variables 2.Probabilistic: linkage variables are given a weight and data are linked according to probability of a match. Requires direct patient identifiers.

7. Objectives 1.Compare the picture of MVC injury according to three different MVC injury data sources 2.Attempt to link MVC data using exact deterministic linkage

8. Methods

9. Data Sources Emergency Medical Services (EMS): All EMS records for the 2013 calendar year in response to MVCs Police Crash Reports: 2013 crash reports occurring in Wake County, NC (including crashes on publically maintained roads and public vehicle access roads) Emergency Department (ED): 2013 MVC-related ED visits by Wake County residents AND all MVC-related ED visits to EDs located in Wake County

10. Methods Descriptive statistics were used to compare the picture of MVC injury according to each data source separately Exact deterministic linkage was used to link data sources Linkage Variables:  Patient Gender  Patient Date of Birth  Crash Date  Crash Time* * Event time was allowed to vary to allow for travel times and/or differences in recording time

11. Results

12. Table 1: Comparison of Persons Involved in MVCs based on data source, N (%) Descriptive Variables Crash Report* N=72,202 ED Visit Data N=17,662 EMS Data N=9,463 Gender Female35,366 (49.1%)9,491 (53.7%)4,417 (54.4%) Age 0-157,952 (11.1%)1,806 (10.2%)713 (9.7%) 16-209,217 (12.9%)1,913 (10.8%)843 (11.4%) 21-3523,601 (33.0%)6,533 (37.0%)2,520 (34.1%) 36-5520,619 (28.9%)5,377 (30.4%)2,177 (29.5%) 56 +10,060 (14.1%)2,033 (11.5%)1,135 (15.4%) Transported to Hospital via EMS Yes7,467 (10.3%)1,564 (14.3%)5,243 (55.7%) Crash Time 12 AM – 5:59 AM1,670 (5.9%)1,190 (6.7%)993 (10.5%) 6 AM – 11:59 AM7,458 (26.2%)3,944 (22.3%)2,232 (23.6%) 12 PM – 5:59 PM12,558 (44.1%)6,796 (38.5%)4,014 (42.4%) 6 PM – 11:59 PM6,762 (23.8%)5,732 (32.5%)2,224 (23.5%) Season Winter (Dec- Feb)7,175 (25.2%)4,150 (23.5%)2,281(24.1%) Spring (Mar – Apr)6,973 (24.5%)4,354 (24.7%)2,292 (24.2%) Summer (June- Aug)6,543 (23.0%)4,232 (24.0%)2,308(24.4%) Fall (Sept – Nov)7,757 (27.3%)4,926 (27.9%)2,582 (27.3%) *28,448 crashes reported (denominator for crash time and season for crash reports)

13. Crash Report  EMS Data Linkage Crash Reports N=72,202 Excluded: n=2,145: - Pt (patient) not found or EMS did not respond (n=1,257) - Gender missing (n=124) - Pt DOB missing (n=764) Excluded, n=64,833: - No mention of EMS reporting to scene (n=64,735) - Gender missing (n=2) - DOB missing (n=96) N=7,318N=7,369 Excluded: n=29 - Duplicated records N=4,086 (52.3%) Linked N=4,115 Unlinked Records Wake EMS N=9,463 Wake EMS N=3,232 Crash Records N=3,283

14. Comparison of Linked vs. Unlinked EMS Data Comparison of Linked vs. Unlinked Crash Data

15. Linked EMS-Crash Reports  ED Visit Data ED Data N=17,662 Excluded: n=0 Excluded, n=1 - Missing Gender N=4,086N=17,661 Excluded: n=11 - Duplicated records N=3,134, 77% Linked N=3,145 Unlinked Records Linked EMS- Crash Data N=4,086 Linked EMS- DMV Data N=952, 23% ED Data N=14,527, 82%

16. Comparison of Linked vs. Unlinked EMS-Crash Data Comparison of Linked vs. Unlinked ED Data

17. Classification of Injury for Comparison Serious injury (n=247):  Transferred to another unit or admitted: 235  Died: 12 Injury (n=2,818):  Discharged to home: 2,724  Left without seeing doctor or against medical advice: 75  Other: 19 No injury (n=952):  DMV-EMS linked records that did not link to ED records Note: ED disposition was missing for 69 people in the linked DMV- DMV-ED linked data

18. ED Disposition: Admitted Pts/ Pts Transferred to Another Unit/Pts that Died (N=247) N=191, 77% Pts Transported by EMS  122 had B injuries  64 had C injuries  5 had No injury or injury was unknown N=54, 22% Pts Transported by EMS and had K or A Injuries N=0 DMV EMS Pts listed as no treatment/no transport by EMS and with B or C injuries by DMV, N=2, 1%

19. ED Disposition: Patients that were discharged or left without being seen or against medical advice (n=2,818) N=3, 0% EMS treated but did not transport  Unknown injury: 3 N=2,587, 92% Pts classified with B or C injuries  Transported via EMS: 2,497  No treatment/no transport by EMS: 88  EMS Assisted on scene: 2 N=22, 0.8% Pts Treated but not transported by EMS and had B or C Injuries DMVEMS Pts without B/C Injuries (n=206, 8%):  A Injuries: Transported by EMS (n=12)  No Injury: Transported by EMS (n=165); No treatment or transport by EMS or EMS Assist (n=13)  Injury Unknown: Transported by EMS (n=16)

20. Pts that did not link to ED visit Data (n=952) N=484, 51% Pts that did not receive treatment /transport by EMS: B injuries: 67 C Injuries: 413 Unknown Injury: 4 N=38, 4% Pts classified with no injury: Transported by EMS: 18 Treated/No transport: 19 Assist: 1 N=123, 13% Pts listed as no injury and received no treatment/ transport by EMS DMVEMS Pts with injury classifications and that received EMS support (307, 32%):  K or A Injuries: Transported by EMS (n=29); Dead on Scene (n=2)  B Injuries: Transported by EMS (n=79); Treated/No Transport (n=26), Assist (n=1)  C Injuries: Transported by EMS (n=96); Treated/No Transport (n=64); Assist (n=6)  Unknown Injuries: Transported by EMS (n=2); Treated No Transport (n=2)

21. Conclusions

22.  EMS is not required at many MVC crashes  MVC injury data agree if patients are seriously injured  Most MVC patients are discharged home from the emergency department and not admitted to the hospital

23. Recommendations 1)Add a Yes/No variable to crash reports indicating if EMS reported to the scene 2)Include a patient identifier on MVC data sources 3)Improve ED reporting of transport mode

24. Strengths/Limitations Strengths:  Able to link 3 separate MVC data sources without direct identifiers  Compared how the picture of MVC injury differs among three different data sources Limitations:  No direct identifier to verify accuracy of linkage  Secondary data analysis- subject to missing data

25. Acknowledgments Jeff Williams and Mike Bachman with Wake EMS Dennis Falls and Clifton Barnett with NC DETECT Eric Rodgman and David Harkey at the UNC Highway Safety Research Center Frank Hackney with NC GHSP Alan Dellapenna with NC Department of Health and Human Services

26. Thank you! jjones86@live.unc.edu anna_waller@med.unc.edu