Pattern of law enforcement–related injuries in the United States

Chang, David C.; Williams, Mallory; Sangji, Naveen F.; Britt, L. D.; Rogers, Selwyn O.

doi:10.1097/ta.0000000000001000

Cited by 20 publications

(22 citation statements)

References 1 publication

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“…On the other hand, this research also tends to focus more on characteristics of the events themselves, and is often more detailed with regard to pre-cursors of force than is typical of medical scholarship. Some of this research is focused at the national-level from an epidemiological or public health framework (e.g., Chang et al., 2016; Miller et al., 2017), while other studies conducted at the agency-level focus more on determining the situational factors and other correlates of injury to subjects and officers (e.g., Castillo et al., 2012), as well as specific concerns such as mental health status (Morabito & Socia, 2015; Rossler & Terrill, 2017). A sizeable body of work focuses specifically on Conducted Energy Devices (CEDs) and OC Spray, and their role in injury or injury reduction as well as their overall effectiveness (e.g., Brandl & Stroshine, 2017; Jenkinson et al., 2006; MacDonald et al., 2009; Paoline et al., 2012; Smith et al., 2007; Taylor & Woods, 2010; Terrill & Paoline, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

“…National-level research has provided evidence on injury trends, primarily derived from Centers for Disease Control (CDC) data. For example, Chang et al. (2016) examined national data for the period 2003–2011, and noted that while the Federal Bureau of Investigation’s (FBI) Law Enforcement Officers Killed and Assaulted (LEOKA) statistics showed a decline in assaults on police officers during that time period, CDC data showed an increase in hospital admissions and nonfatal injuries to citizens related to police action.…”

Section: Literature Reviewmentioning

confidence: 99%

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Police Use of Force and Injury: Multilevel Predictors of Physical Harm to Subjects and Officers

et al. 2020

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The police must on occasion use physical force and weapons in order to apprehend and control subjects and fulfil the police function. It is inevitable that some of these interactions will result in injuries to both subjects and officers, with a range of both tangible and intangible harms and costs. It is therefore important to study injuries related to the use of force with an eye toward identifying opportunities to minimize injury and reduce the harms and costs. Injuries to both subjects and officers were examined in a sample of more than 10,000 use of force incidents drawn from 81 agencies located in 8 states. In addition to describing injury rates across a broad spectrum of situational and agency characteristics, we present multilevel logistic regression models predicting subject and officer injury. Among key findings, we report that the likelihood of injury for both subjects and officers is lower when force incidents end quickly and with the minimal necessary superior level of force relative to subject resistance, and higher for both subjects and officers when subjects flee. At the agency level, we find that the likelihood of injury varies by agency size and type. Finally, we explored possible higher-level variation and found that agencies in the sample from Midwestern states (primarily Wisconsin) have substantially lower injury rates that appear to be associated with their less frequent use of weapons and greater reliance on low-level physical force tactics, as compared to agencies in the sample from Western and other states.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Police Use of Force and Injury: Multilevel Predictors of Physical Harm to Subjects and Officers

et al. 2020

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“…1 When the wounding mechanism is a firearm, White and Black patients are more likely to die than Hispanic patients. 2 These pre-existing studies all call for further study of this important public health problem to better understand injuries sustained during interaction with law enforcement to begin to work toward injury prevention and mitigation.…”

Section: Discussionmentioning

confidence: 99%

“…Existing literature suggests that there are racial differences among patients injured by civilians as compared with those injured during LI 1 and that outcomes after LI-associated injuries may vary by race. 2 One study found that despite comparable injury severity among civilian interpersonal violence (CIV) and injuries sustained during LI, patients injured during LI may have worse outcomes. 3 It is clear that injuries sustained during the course of LI differ in substantial ways from those inflicted on civilians by other civilians.…”

mentioning

confidence: 99%

Gunshot wounds sustained during legal intervention versus those inflicted by civilians: A comparative analysis

Schellenberg

Liasidis

Inaba

et al. 2021

J Trauma Acute Care Surg

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BACKGROUND:Existing data demonstrate that injuries sustained during legal intervention (LI) differ from those incurred during civilian interpersonal violence (CIV), but gunshot wounds (GSWs) have not yet been specifically examined. This study was undertaken to provide an in-depth analysis of patients shot during LI versus CIV. METHODS:Patients injured by GSW and captured by the National Trauma Data Bank (2007-2017) were included. Exclusions were transfer from outside hospital or self-inflicted, accidental, or undetermined injury intent GSWs. Study groups were defined by injury circumstances: GSWs sustained during LI versus CIV. Univariable analysis compared demographics, clinical/injury data, and outcomes. RESULTS:In total, 248,726 patients met inclusion/exclusion criteria: 98% (n = 243,150) CIV versus 2% (n = 5,576) LI. Race varied significantly between study groups (p < 0.001). White patients were the most commonly injured race after LI (n = 2,176, 39%). Black patients were the most commonly injured race after CIV (n = 139,067, 57%). Psychiatric disease (9% vs. 2%, p < 0.001) was more common among LI GSWs. The LI patients were more frequently tachycardic (18% vs. 13%, p < 0.001), hypotensive (26% vs. 14%, p < 0.001), and comatose (34% vs. 15%, p < 0.001). The LI patients had higher Injury Severity Scores (13 vs. 9, p < 0.001), required emergent surgical intervention (39% vs. 28%, p < 0.001) and intensive care unit admission (47% vs. 32%, p < 0.001) more often, and had longer hospital stay (4 vs. 3 days, p < 0.001). Mortality was higher after LI (27% vs. 14%, p < 0.001). CONCLUSION:Significant racial and injury severity differences exist between patients shot during LI and CIV. White patients were the most commonly injured race after LI, while Black patients were the most commonly injured race during CIV. In addition, Black patients were overrepresented in both groups when compared with their proportion in the US population. LI patients were more significantly injured, as quantified by clinical, injury, and outcomes variables including increased mortality. Further study of patients shot during LI is needed to better understand this increased burden of injury.

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“…The International Classification of Diseases, Ninth Revision, Clinical Modification, includes external cause-ofinjury codes identifying injuries owing to contact with law enforcement (E970-E978). Using these codes, prior studies have identified 715 118 nonfatal injuries, 3958 hospitalizations, and 3156 deaths between 2003 and 2011 from US Centers for Disease Control and Prevention data and the Nationwide Inpatient Sample, 4 and 55 400 fatal and nonfatal injuries in 2012 from the Vital Statistics mortality census, Nationwide Inpatient and Emergency Department Samples, and journalists' reports. 5 In this study, we used a nationally representative database to determine whether the incidence of emergency department (ED) visits for injures by law enforcement increased relative to total ED visits from 2006 to 2012.…”

Section: Us Emergency Department Encounters For Law Enforcement-assocmentioning

confidence: 99%

US Emergency Department Encounters for Law Enforcement–Associated Injury, 2006-2012

2017

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were considered to have the weekend effect if they were admitted on the weekend and their observed length of stay was greater than the upper bound of the 95% CI of the model-derived expected length of stay. Multilevel models including hospital covariates, such as structural characteristics, hospital size, and hospital resources, were used to determine associations between EHR elements and the weekend effect. Additional hospital-level confounders including weekend-specific staffing, resource allocation, surgeon staffing, and models of surgical care (ie, acute care surgery programs) could not be assessed owing to limitations of the data set. This study was deemed exempt from institutional review board approval by the Loyola University Medical Center institutional review board based on the use of publicly available, deidentified patient data. All statistical analyses were performed using Stata version 13 (StataCorp LP).Results | There were 2979 patients who met the criteria for inclusion. Of these, 2033 did not have the weekend effect and 946 had the weekend effect. Patients without the weekend effect were more likely to be exposed to high-speed EHR connectivity (62.6% vs 57.3%, P = .006), EHR in the operating room (90.0% vs 87.3%, P = .03), electronic operating room scheduling (91.6% vs 89.1%, P = .03), computerized physician order entry (45.0% vs 41.0%, P = .04), and electronic bed management systems (79.9% vs 73.2%, P < .001).Specific components of EHR systems decreased the odds of having the weekend effect. These included electronic operating room scheduling (adjusted odds, 0.67; 95% CI, 0.46-0.97; P = .03) and electronic bed management systems (adjusted odds, 0.65; 95% CI, 0.50-0.84; P = .001) ( Figure).Discussion | Implementation of EHR systems is one mechanism to help hospitals combat an important temporal disparity of care, the weekend effect, for patients undergoing urgent general surgical procedures. Specific components of EHR systems, including electronic operating room scheduling and electronic bed management systems, are most strongly associated with decreasing the odds of the weekend effect. Together, these data illustrate an important relationship that may exist between EHR systems and temporal care disparities in nonelective surgical settings.

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Pattern of law enforcement–related injuries in the United States

Abstract: Epidemiologic study, level III.

Cited by 20 publications

References 1 publication

Police Use of Force and Injury: Multilevel Predictors of Physical Harm to Subjects and Officers

Police Use of Force and Injury: Multilevel Predictors of Physical Harm to Subjects and Officers

Gunshot wounds sustained during legal intervention versus those inflicted by civilians: A comparative analysis

US Emergency Department Encounters for Law Enforcement–Associated Injury, 2006-2012

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