Demographic, Clinical, and Mortality Trends of Law Enforcement–Related Trauma: A Trauma Quality Improvement Program Analysis | Emergency Medicine | JAMA Surgery | JAMA Network
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Figure.  Cause of Injury by External Cause Code Description
Cause of Injury by External Cause Code Description

Most injuries (938 of 1420 [66.0%]) were caused by firearms or ammunition, followed by manhandling (66 [4.6%]), injuries from blunt objects (57 [4.0%]), and injuries from sharp objects (12 [0.8%]). A total of 347 injuries (24.4%) were caused by unknown or unspecified mechanisms.

Table.  Risk of Law Enforcement (LE) Firearm-Related Injury and Mortality Risk Subanalysis Across Demographic, Hospital, and Injury Parameters
Risk of Law Enforcement (LE) Firearm-Related Injury and Mortality Risk Subanalysis Across Demographic, Hospital, and Injury Parameters
1.
Crosby  AE, Lyons  B.  Assessing homicides by and of US law-enforcement officers.   N Engl J Med. 2016;375(16):1509-1511. doi:10.1056/NEJMp1609905PubMedGoogle ScholarCrossref
2.
Hornor  MA, Hoeft  C, Nathens  AB.  Quality benchmarking in trauma: from the NTDB to TQIP.   Curr Trauma Rep. 2018;4(2):160-169. doi:10.1007/s40719-018-0127-1Google ScholarCrossref
3.
Feldman  JM, Chen  JT, Waterman  PD, Krieger  N.  Temporal trends and racial/ethnic inequalities for legal intervention injuries treated in emergency departments: US men and women age 15-34, 2001-2014.   J Urban Health. 2016;93(5):797-807. doi:10.1007/s11524-016-0076-3PubMedGoogle ScholarCrossref
4.
US Census Bureau. QuickFacts: United States population estimates base, April 1, 2010 (V2019). Accessed October 1, 2020. https://www.census.gov/quickfacts/fact/table/US/ PST040219#PST040219
5.
Hyland  SS, Davis  E. Local police departments, 2016: personnel. Accessed September 22, 2020. https://www.bjs.gov/content/pub/pdf/lpd16p.pdf
6.
Office of Juvenile Justice and Delinquency Prevention. Race profile of arrests by offense, 2014-2016. Accessed September 1, 2020. https://www.ojjdp.gov/ojstatbb/crime/ucr.asp?table_in=2
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    Research Letter
    May 5, 2021

    Demographic, Clinical, and Mortality Trends of Law Enforcement–Related Trauma: A Trauma Quality Improvement Program Analysis

    Author Affiliations
    • 1Yale School of Medicine, New Haven, Connecticut
    • 2Division of Otolaryngology, Department of Surgery, Yale School of Medicine, New Haven, Connecticut
    • 3Department of Surgery, Houston Methodist Hospital, Houston, Texas
    • 4Department of Surgery, Division of Plastic and Reconstructive Surgery, University of Massachusetts Medical School-Baystate, Springfield
    JAMA Surg. 2021;156(7):685-687. doi:10.1001/jamasurg.2021.0697

    Recent activist movements have increased public attention surrounding the use of force by law enforcement (LE) officers in the US. While epidemiological research revealed the prevalence of legal intervention events,1 recent literature is lacking about the nature of and clinical outcomes from such traumatic injuries.

    Methods

    The American College of Surgeons Trauma Quality Improvement Program (TQIP) captures a subset of patients who meet certain injury severity criteria across the nationally representative National Trauma Data Bank and facilitates outcomes benchmarking.2 Study and consent exemption were approved by the Yale Institutional Review Board. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    We analyzed TQIP data from 2014 through 2016, capturing 1420 injuries that included the phrase “legal intervention” in the external cause code description designated by the International Classification of Diseases, Ninth Revision (ICD-9) or ICD-10, the latter of which defines legal intervention as “any injury sustained as a result of an encounter with any law enforcement official.” Incidents captured only by ICD-10 codes (482 of 1420 [33.9%]) further differentiated patients as suspects (401 [28.2%]), LE officials (73 [5.1%]), or bystanders (8 [0.6%]). Statistical analyses were conducted using R version 3.5.1 (The R Foundation). The level of significance for multivariate logistic regression was held to a 2-tailed P value less than .05.

    Results

    Of 1420 LE-related injuries, 1340 patients (94.4%) were male, and the mean (SD) age was 35.6 (12.7) years. According to external cause code descriptions, 937 incidents (66.0%) involved injuries by firearms or ammunition (Figure). Most injuries were characterized as penetrating injuries (947 [66.7%]), followed by blunt injuries (432 [30.4%]). An increase in cases was observed from 452 in 2014 to 500 in 2016. Ages ranged from 16 to 86 years, with 37 cases (2.6%) involving minors and the greatest proportion of cases involving those aged 18 to 45 years (1041 [73.3%]).

    A total of 854 of 1420 cases (60.1%) involved intensive care unit admission, and 892 patients (62.8%) had hospital admissions longer than 3 days. A total of 709 patients (49.9%) incurred injuries to the torso and spine, while 596 (42.0%) and 457 (32.2%) involved the extremities and the head and neck regions, respectively. Among those with head and neck injuries, 338 of 457 (74.0%) sustained a traumatic brain injury.

    The largest racial/ethnic category was non-Hispanic/Latino White patients (609 [42.9%]), followed by non-Hispanic/Latino Black patients (328 [23.1%]). Compared with the TQIP database’s distribution of ages (mean [SD] age of 53.2 [21.8] years), our data set was considerably younger (mean [SD] age of 35.6 [12.7] years). Non-Hispanic/Latino White patients make up 64.0% of the TQIP data set but only 42.9% (609 of 1420) of our study population. Non-Hispanic/Latino Black and Hispanic/Latino patients, who make up 11.5% and 9.5%, respectively, of the 829 805 unique instances in the TQIP data set, were disproportionately represented in our study cohort (23.1% [328 of 1420] and 17.5% [248 of 1420], respectively).

    Prior studies of national averages have reported that compared with White individuals, Black individuals experienced injuries involving legal intervention at rates approximately 5-fold higher.1,3 For reference, from 2014 to 2016, Black individuals made up 14% of the US population,4 11% of LE officers,5 and 27% to 28% of all arrests.6 In the subset of our cohort in which the patient’s role as a suspect or LE officer was known, the proportion of non-Hispanic/Latino Black individuals was 26.2% (105 of 401) and 26.0% (19 of 73), respectively.

    Mortality analyses were conducted for 1397 patients with known death status (1214 [86.9%] nonfatal; 183 [13.1%] fatal) using multivariate logistic regression (Table). While controlling for hospital characteristics, mechanism of injury, injury type, age, sex, and racial/ethnic category, only Injury Severity Score was associated with increased mortality (odds ratio, 1.12; 95% CI, 1.09-1.14; P < .001). This finding suggests that among those who sustained injuries, mortality was largely independent of demographic, hospital, or mechanistic factors.

    Discussion

    Our study adds to the limited literature surrounding the epidemiology and outcomes of injuries sustained in the setting of legal intervention by all involved parties. To our knowledge, it is the first to use the nationally representative and standardized TQIP database to accomplish this aim, although it has limitations, including underreporting of ICD encoding for legal intervention, incomplete data, and selection bias from omission of (less-severe) injuries for patients who do not present to trauma centers, which preferentially capture urban populations. Our findings highlight differences among racial/ethnic backgrounds, which likely have multifactorial and complex origins.3 Further study on this topic is essential to address inequities, mitigate health care costs, and improve management and prevention strategies.

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    Article Information

    Accepted for Publication: February 13, 2021.

    Published Online: May 5, 2021. doi:10.1001/jamasurg.2021.0697

    Corresponding Author: Yan Ho Lee, MD, Division of Otolaryngology, Department of Surgery, Yale School of Medicine, 47 College Pl, 2nd Floor Otolaryngology, New Haven, CT 06510 (yan.lee@yale.edu).

    Author Contributions: Ms Bourdillon had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Study concept and design: Bourdillon, Salehi, J. Lee.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Bourdillon, Salehi, Steren.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Bourdillon, Steren.

    Administrative, technical, or material support: Salehi, Steren.

    Study supervision: Salehi, J. Lee, Pei, Y. Lee.

    Conflict of Interest Disclosures: None reported.

    References
    1.
    Crosby  AE, Lyons  B.  Assessing homicides by and of US law-enforcement officers.   N Engl J Med. 2016;375(16):1509-1511. doi:10.1056/NEJMp1609905PubMedGoogle ScholarCrossref
    2.
    Hornor  MA, Hoeft  C, Nathens  AB.  Quality benchmarking in trauma: from the NTDB to TQIP.   Curr Trauma Rep. 2018;4(2):160-169. doi:10.1007/s40719-018-0127-1Google ScholarCrossref
    3.
    Feldman  JM, Chen  JT, Waterman  PD, Krieger  N.  Temporal trends and racial/ethnic inequalities for legal intervention injuries treated in emergency departments: US men and women age 15-34, 2001-2014.   J Urban Health. 2016;93(5):797-807. doi:10.1007/s11524-016-0076-3PubMedGoogle ScholarCrossref
    4.
    US Census Bureau. QuickFacts: United States population estimates base, April 1, 2010 (V2019). Accessed October 1, 2020. https://www.census.gov/quickfacts/fact/table/US/ PST040219#PST040219
    5.
    Hyland  SS, Davis  E. Local police departments, 2016: personnel. Accessed September 22, 2020. https://www.bjs.gov/content/pub/pdf/lpd16p.pdf
    6.
    Office of Juvenile Justice and Delinquency Prevention. Race profile of arrests by offense, 2014-2016. Accessed September 1, 2020. https://www.ojjdp.gov/ojstatbb/crime/ucr.asp?table_in=2
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