Abstract
Objective:
This study aimed to evaluate hospital resource utilization in the treatment of firearm-related injuries compared to other penetrating and blunt traumas.
Background:
Trauma is a leading cause of morbidity and mortality in the United States, with firearm injuries becoming the leading cause of pediatric death as of 2020. Despite the known mortality, the burden of inpatient healthcare for initially nonfatal firearm injuries is poorly understood.
Methods:
A retrospective cohort study of the National Inpatient Sample was performed. The study population included patients with firearm injuries, penetrating traumas, and blunt traumas from 2017 to 2021. Primary interventions assessed included surgical procedures performed during hospitalization, and the outcomes evaluated were costs, length of stay, and mortality. Comparisons were made between the 3 injury groups (firearm, penetrating trauma, and blunt trauma) across these key variables.
Results:
Among 10,653,446 patients identified, 243,295 (2.3%) had a firearm injury, 287,110 (2.7%) had a penetrating injury, and 10,123,041 (95%) had blunt trauma. Patients sustaining firearm injuries required more resuscitative interventions and major surgical procedures, such as pericardiotomy, chest tube placement, exploratory thoracotomy, and laparotomy. The mean length of inpatient stay was longer for firearm injuries (7.8 days) compared with penetrating (5.7 days) and blunt trauma (6.0 days, P < 0.001). Inpatient death rates were higher for firearm injuries (6.5%) compared with penetrating (0.6%) and blunt trauma (2.8%, P < 0.001). Total hospital costs were higher for firearm injuries ($30,529) compared with penetrating ($12,243) and blunt trauma ($18,333, P < 0.001). Firearm injuries remained a significant predictor of higher hospital costs, even after adjusting for other factors (adjusted incidence rate ratio 1.256; P < 0.001).
Conclusions:
Although firearm injuries account for only a proportion of total trauma cases, they are associated with higher inpatient resource utilization, as measured by interventions and hospital costs. These findings highlight the need for focused prevention efforts and resource allocation to address unique challenges posed by firearm injuries.
Keywords: firearm injuries, surgery, trauma, costs
INTRODUCTION
Firearm injury is a leading cause of morbidity and mortality in the United States.1 In 2022 alone, the Centers for Disease Control and Prevention recorded over 48,000 firearm deaths and nearly 172,000 nonfatal firearm injuries.2,3 Despite improvements in treatment protocols and emergency management, firearm injuries are associated with a high case fatality rate (CFR) compared with other traumatic mechanisms, frequently involving multisystem injuries and requiring substantial healthcare resources.4–6 Recent data suggests a greater lethality of firearm injuries (CFR, 22%) compared with stab wounds (CFR, 2.2%) or motor vehicle crashes (CFR, 2.4%).7–9
While firearm-related mortality has been well documented, data capturing the incidence, clinical course, and resource requirements for nonfatal firearm injuries remain limited.10,11 National data suggest that nonfatal firearm injuries occur at over twice the rate of firearm-related deaths, highlighting the importance of understanding the treatment and resource demands associated with survival.12 Furthermore, prior studies have reported financial costs of emergency department care for firearm injuries, with estimates averaging over $29,000 per patient and $1.59 billion in total annual charges, based on nationally representative samples.13 However, these reports have not specifically examined inpatient care patterns and provided context to hospital resource utilization and costs associated with firearm injuries, compared with other traumatic injuries.
The objective of this study was to determine the utilization of inpatient hospital care and resources—as measured by procedural interventions and hospital costs—among patients hospitalized with firearm injuries and to compare these patterns to patients with penetrating or blunt injuries. We hypothesized that firearm injuries would be associated with greater overall inpatient resource utilization and higher hospital costs compared with other traumatic injury mechanisms, due to the increased severity and multi-system nature of these injuries.
METHODS
Population and Data Source
This retrospective cohort study utilized the National Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality discharge data from 2017 to 2021. This study was deemed exempt from full institutional review board approval as it utilized a publicly available, de-identified dataset. The study sample included patients based on the International Classification of Disease 10th revision (ICD-10-CM) injury codes relating to blunt, penetrating, or firearm traumas. All cases that did not meet these inclusion criteria (eg, injuries unrelated to the trauma mechanisms of interest) were excluded from the study. A detailed list of inclusion criteria and relevant ICD-10-CM codes is provided in the Supplemental Data File (eTable 1, https://links.lww.com/AOSO/A512). Records involving more than one mechanism were classified according to the priority of mechanism, with firearm injury mechanisms taking precedence (following penetrating trauma and blunt trauma, respectively). National estimates for each trauma category were obtained by applying the NIS survey weights. Trauma mechanisms were further classified by intent (eg, unintentional, self-inflicted, assault, undetermined, or legal intervention or war), and blunt trauma was subclassified by cause (eg, falls, motor vehicle collisions, or struck by or against).
Primary Exposure
The primary exposure of interest in this study was the trauma mechanism sustained by the patient, which was classified into 3 categories as described: firearm injuries, penetrating injuries (excluding firearm injuries), and blunt trauma.
Demographics, Case, and Hospital Characteristics
For included cases, demographic information was analyzed and compared between trauma mechanisms, including age, race, sex, payor status, and median household income. Median household income was estimated based on the patient’s reported zip code (obtained from Claritas) and reported by quartile classification per year by NIS. Additional admission and hospital-related factors were analyzed, including location and teaching hospital status, region, and time of admission. Metrics relating to injury type and severity were determined, including injury severity score (ISS) and location of injury. ISS was computed using the R package icdpicr, which converts ICD-10-CM codes to the Abbreviated Injury Scale.
Inpatient Course
To evaluate the inpatient hospital resource utilization relating to each trauma mechanism, major life-sustaining procedures, resuscitative measures, and surgical procedures were compared. ICD-10 codes for each intervention were grouped and are provided in Supplemental Data (eTable 2, https://links.lww.com/AOSO/A512). Inpatient complications were identified and grouped by system according to previous literature,14 which were updated to fit ICD-10 criteria (Supplemental Data, eTable 3, https://links.lww.com/AOSO/A512). Finally, the length of inpatient stay and disposition after hospital discharge were compared.
Primary Outcome: Hospital Costs
The NIS provides total charges relating to each inpatient case, which reflects the amount a hospital billed for services, and generally does not include professional fees and non-covered charges. Estimated costs for each discharge record in the NIS were derived by converting total hospital charges using hospital-specific cost-to-charge ratios provided by the NIS. These ratios are based on accounting reports collected by the Centers for Medicare and Medicaid Services. After calculating the estimated cost for each discharge, discharge weights were applied to generate nationally representative estimates. All cost estimates were inflation-adjusted with reference to 2017 US dollar values using the latest Consumer Price Index data (https://www.bls.gov/data/inflation_calculator.htm).
Statistical Analysis
Categorical variables were expressed as frequencies/percentages and compared between the 3 trauma categories using χ2 tests. Continuous variables were expressed as mean ± standard deviation (SD) and/or median (interquartile range) and compared across groups using analysis of variance (ANOVA).
Univariable and multivariable negative binomial regression models were used to examine the associations between inflation-adjusted hospital costs and patient characteristics, including trauma mechanism. Variable selection was initially informed by prior literature and their relevance to trauma outcomes and hospital resource utilization. These included age, race, sex, insurance status, household income, year, geographic region, trauma mechanism, injury location, and ISS. All clinically relevant variables and those with P < 0.05 in the univariable analyses, were included in the multivariable-adjusted model. A full list of included variables and their definitions is provided in Supplemental Data (eTable 4, https://links.lww.com/AOSO/A512). Results from the regression models were reported as incidence rate ratios (IRRs) with 95% confidence intervals (CIs), and analyses accounted for discharge-level sampling weights, as recommended by the NIS for data collected after 2012. Finally, forest plots were generated from the estimated IRRs derived from the multivariable (adjusted) negative binomial regression coefficients to visually present associations with inpatient costs.
All variables were examined for missing data. Patients’ characteristics had a low percentage of missing data (<3%), except for the location of injury (16%) and ISS (23%). Outcome data on costs also had a low percentage of missing data (<2%). To avoid multicollinearity, only ISS was included in the multivariable model, with missing/unknown values coded as a separate category. As a sensitivity analysis, we re-estimated the multivariable model both including the missing ISS category (see Supplemental Data, eTable 5, https://links.lww.com/AOSO/A512) and excluding it (see Table 4). The results showed minimal differences in the magnitude of the estimates, indicating the robustness of the findings.
TABLE 4.
Univariable and multivariable negative binomial regression models examining the associations between inflation-adjusted hospital costs and patient characteristics.
| Predictors of Hospital Costs | ||||||
|---|---|---|---|---|---|---|
| Univariable Analysis | Multivariable Analysis | |||||
| IRR | 95% CI | P value | aIRR | 95% CI | P value | |
| Age group | ||||||
| 1–5 years (reference) | — | — | — | — | — | — |
| <1 year | 0.745 | 0.736–0.754 | <0.001 | 0.750 | 0.741–0.759 | <0.001 |
| 6–11 years | 1.109 | 1.099–1.119 | <0.001 | 1.163 | 1.153–1.173 | <0.001 |
| 12–18 years | 1.373 | 1.363–1.383 | <0.001 | 1.464 | 1.453–1.475 | <0.001 |
| 19–34 years | 1.528 | 1.518–1.538 | <0.001 | 1.660 | 1.649–1.671 | <0.001 |
| 35–54 years | 1.452 | 1.442–1.461 | <0.001 | 1.700 | 1.689–1.712 | <0.001 |
| ≥55 years | 1.152 | 1.145–1.160 | <0.001 | 1.629 | 1.618–1.639 | <0.001 |
| Race | ||||||
| White (reference) | — | — | — | — | — | |
| Black/African American | 1.211 | 1.209–1.213 | <0.001 | 1.138 | 1.136–1.140 | <0.001 |
| Asian/Pacific Islander | 1.352 | 1.347–1.357 | <0.001 | 1.087 | 1.083–1.091 | <0.001 |
| Hispanic | 1.265 | 1.263–1.267 | <0.001 | 1.088 | 1.086–1.090 | <0.001 |
| Native American | 1.242 | 1.235–1.250 | <0.001 | 1.054 | 1.047–1.061 | <0.001 |
| Other | 1.309 | 1.305–1.313 | <0.001 | 1.147 | 1.143–1.150 | <0.001 |
| Sex | ||||||
| Male (reference) | — | — | — | — | — | — |
| Female | 0.803 | 0.803–0.804 | <0.001 | 0.912 | 0.911–0.914 | <0.001 |
| Primary Payor | ||||||
| Medicaid (reference) | — | — | — | — | — | — |
| Medicare | 0.707 | 0.706–0.708 | <0.001 | 0.858 | 0.857–0.860 | <0.001 |
| Private | 0.897 | 0.895–0.898 | <0.001 | 0.959 | 0.957–0.961 | <0.001 |
| Self-pay | 0.788 | 0.786–0.790 | <0.001 | 0.841 | 0.838–0.843 | <0.001 |
| No charge | 0.699 | 0.693–0.705 | <0.001 | 0.800 | 0.793–0.807 | <0.001 |
| Other | 0.900 | 0.898–0.903 | <0.001 | 0.949 | 0.946–0.952 | <0.001 |
| Median household income for zip code | ||||||
| Quartile 1 (reference) | — | — | — | — | — | — |
| Quartile 2 | 0.994 | 0.993–0.996 | <0.001 | 1.014 | 1.012–1.015 | <0.001 |
| Quartile 3 | 1.026 | 1.025–1.028 | <0.001 | 1.021 | 1.020–1.023 | <0.001 |
| Quartile 4 | 1.091 | 1.089–1.092 | <0.001 | 1.064 | 1.062–1.065 | <0.001 |
| Calendar year | ||||||
| 2017 (reference) | — | — | — | — | — | — |
| 2018 | 0.992 | 0.991–0.994 | <0.001 | 0.991 | 0.990–0.993 | <0.001 |
| 2019 | 1.045 | 1.043–1.047 | <0.001 | 1.039 | 1.038–1.041 | <0.001 |
| 2020 | 1.132 | 1.130–1.134 | <0.001 | 1.114 | 1.112–1.116 | <0.001 |
| 2021 | 1.189 | 1.187–1.191 | <0.001 | 1.189 | 1.187–1.191 | <0.001 |
| Location & teaching status of hospital | ||||||
| Urban teaching | — | — | — | — | — | — |
| Urban nonteaching | 0.881 | 0.880–0.882 | <0.001 | 0.927 | 0.926–0.929 | <0.001 |
| Rural | 0.887 | 0.885–0.888 | <0.001 | 0.950 | 0.949–0.952 | <0.001 |
| Region | ||||||
| South (reference) | — | — | — | — | — | — |
| Midwest | 0.993 | 0.991–0.994 | <0.001 | 1.011 | 1.010–1.013 | <0.001 |
| Northeast | 1.103 | 1.102–1.105 | <0.001 | 1.072 | 1.071–1.074 | <0.001 |
| West | 1.466 | 1.464–1.468 | <0.001 | 1.377 | 1.375–1.379 | <0.001 |
| Trauma mechanism | ||||||
| Blunt trauma (reference) | — | — | — | — | — | |
| Firearm trauma | 1.661 | 1.655–1.667 | <0.001 | 1.256 | 1.251–1.261 | <0.001 |
| Penetrating trauma | 0.669 | 0.667–0.671 | <0.001 | 0.655 | 0.652–0.657 | <0.001 |
| Location of injury | ||||||
| Head or neck (reference) | — | — | — | |||
| Thorax | 0.951 | 0.949–0.952 | <0.001 | † | † | † |
| Torso | 0.814 | 0.813–0.816 | <0.001 | |||
| Extremity | 0.804 | 0.803–0.805 | <0.001 | |||
| Multiple | 1.454 | 1.448–1.461 | <0.001 | |||
| Injury Severity score | ||||||
| 1–3 (reference) | — | — | — | — | — | — |
| 4–8 | 1.072 | 1.071–1.074 | <0.001 | 1.092 | 1.091–1.094 | <0.001 |
| 9–15 | 1.212 | 1.210–1.214 | <0.001 | 1.205 | 1.203–1.207 | <0.001 |
| 16–24 | 1.506 | 1.503–1.509 | <0.001 | 1.414 | 1.411–1.417 | <0.001 |
| 25–74 | 2.517 | 2.512–2.522 | <0.001 | 2.246 | 2.242–2.251 | <0.001 |
| 75 | 6.303 | 6.022–6.602 | <0.001 | 5.382 | 5.133–5.647 | <0.001 |
Excluded for multicollinearity.
IRR incidence rate ratio; aIRR, adjusted incidence ratio; CI, confidence interval.
All analyses were performed according to recommended Agency for Healthcare Research and Quality/HCUP methods to account for complex survey design, cluster, stratification, and weighting, and in agreement with the best research practices for conducting research using the NIS database. All data processing and statistical analysis were performed using R statistical computing software (version 4.4.1; R Core Team 2024).
RESULTS
Patient Cohort
The analysis identified a total of 2,130,690 unweighted cases that met inclusion criteria. After applying sampling weights, this represented 10,653,446 trauma cases nationwide, including 243,295 (2.3%) firearm injuries, 287,110 (2.7%) penetrating injuries, and 10,123,041 (95%) blunt traumatic injuries (Supplemental Data, Figure 1, https://links.lww.com/AOSO/A512). A breakdown of national estimates for each trauma mechanism per year is provided in Supplemental Data, eTable 6, https://links.lww.com/AOSO/A512.
Patient Characteristics
The next step involved examining the characteristics of patients across the 3 injury mechanisms. Significant differences were found between groups, as summarized in Table 1. For example, firearm-injured patients were younger (median age of 30 years) compared to those with penetrating or blunt traumas (median ages of 32 and 71 years, respectively). Demographic factors such as race, gender, and insurance type also differed across the groups. A significantly greater proportion of patients sustaining firearm injuries were Black (53%) compared to penetrating and blunt traumas (17% and 9.7%, respectively). Most firearm-injured patients were male (87%), representing the largest gender gap compared to penetrating (60% male) and blunt traumas (47% male). The most common insurance type for firearm-injured patients was Medicaid (47%), compared to penetrating trauma patients (39% Medicaid). Comparatively, the most common insurance type for bluntly injured patients was Medicare (62%) followed by private insurance (18%).
TABLE 1.
Patients’ Characteristics by Tauma Mechanism
| Patients’ Characteristics (Estimated Total NIS Universe) | |||||
|---|---|---|---|---|---|
| All Traumas (N = 10,653,446) |
Firearm Injury (N = 243,295) |
Penetrating Trauma (N = 287,110) |
Blunt Trauma (N = 10,123,041) |
P value | |
| Age (mean ±SD) | 65 (±22) | 34 (±15) | 36 (±18) | 66 (±21) | <0.001 |
| Age, median (IQR) | 70 (52–82) | 30 (22–42) | 32 (22–48) | 71 (55–83) | |
| Race | |||||
| White | 7,673,462 (74%) | 62,120 (27%) | 164,990 (60%) | 7,446,352 (76%) | <0.001 |
| Black/African American | 1,125,330 (11%) | 123,850 (53%) | 46,445 (17%) | 955,035 (9.7%) | |
| Asian/Pacific Islander | 218,745 (2.1%) | 2110 (0.9%) | 4760 (1.7%) | 211,875 (2.2%) | |
| Hispanic | 976,030 (9.4%) | 34,830 (15%) | 42,615 (15%) | 898,585 (9.1%) | |
| Native American | 72,695 (0.7%) | 1870 (0.8%) | 4745 (1.7%) | 66,080 (0.7%) | |
| Other | 287,955 (2.8%) | 9015 (3.9%) | 11,470 (4.2%) | 267,470 (2.7%) | |
| Unknown | 299,230 (2.8%) | 9500 (3.9%) | 12,085 (4.2%) | 277,645 (2.7%) | |
| Sex | |||||
| Male | 5,186,718 (49%) | 212,315 (87%) | 172,070 (60%) | 4,802,333 (47%) | <0.001 |
| Female | 5,464,733 (51%) | 30,755 (13%) | 114,930 (40%) | 5,319,048 (53%) | |
| Unknown | 1995 (0.02%) | 225 (0.1%) | 110 (0.04%) | 1660 (0.02%) | |
| Primary payor | |||||
| Medicaid | 1,401,740 (13%) | 114,530 (47%) | 110,480 (39%) | 1,176,730 (12%) | <0.001 |
| Medicare | 6,302,737 (59%) | 26,855 (11%) | 41,830 (15%) | 6,234,052 (62%) | |
| Private | 1,981,914 (19%) | 43,310 (18%) | 77,265 (27%) | 1,861,339 (18%) | |
| Self-pay | 487,085 (4.6%) | 42,045 (17%) | 34,840 (12%) | 410,200 (4.1%) | |
| No charge | 39,865 (0.4%) | 3075 (1.3%) | 3080 (1.1%) | 33,710 (0.3%) | |
| Other | 421,600 (4.0%) | 12,875 (5.3%) | 18,775 (6.6%) | 389,950 (3.9%) | |
| Unknown | 18,505 (0.2%) | 605 (0.2%) | 840 (0.3%) | 17,060 (0.2%) | |
| Median household income for zip code | |||||
| Quartile 1 | 2,996,479 (29%) | 124,015 (52%) | 97,645 (35%) | 2,774,819 (28%) | <0.001 |
| Quartile 2 | 2,741,324 (26%) | 54,965 (23%) | 73,170 (27%) | 2,613,189 (26%) | |
| Quartile 3 | 2,527,504 (24%) | 38,300 (16%) | 61,465 (22%) | 2,427,739 (24%) | |
| Quartile 4 | 2,173,904 (21%) | 19,370 (8.2%) | 43,440 (16%) | 2,111,094 (21%) | |
| Unknown | 214,235 (2.0%) | 6645 (2.7%) | 11,390 (4.0%) | 196,200 (1.9%) | |
| Calendar Year | |||||
| 2017 | 2,049,999 (19%) | 45,565 (19%) | 58,760 (20%) | 1,945,674 (19%) | <0.001 |
| 2018 | 2,123,295 (20%) | 43,055 (18%) | 58,545 (20%) | 2,021,695 (20%) | |
| 2019 | 2,182,410 (20%) | 42,865 (18%) | 56,630 (20%) | 2,082,915 (21%) | |
| 2020 | 2,114,429 (20%) | 54,315 (22%) | 57,380 (20%) | 2,002,734 (20%) | |
| 2021 | 2,183,313 (20%) | 57,495 (24%) | 55,795 (19%) | 2,070,023 (20%) | |
| Location & teaching status of hospital | |||||
| Urban teaching | 7,157,358 (68%) | 189,355 (79%) | 200,120 (70%) | 6,767,883 (68%) | <0.001 |
| Urban nonteaching | 2,070,710 (20%) | 29,770 (12%) | 50,795 (18%) | 1,990,145 (20%) | |
| Rural | 1,315,249 (12%) | 21,425 (8.9%) | 33,510 (12%) | 1,260,314 (13%) | |
| Unknown | 110,129 (1.0%) | 2745 (1.1%) | 2685 (0.9%) | 104,699 (1.0%) | |
| Region | |||||
| South | 4,196,841 (40%) | 113,040 (47%) | 111,740 (39%) | 3,972,061 (40%) | <0.001 |
| Midwest | 2,179,855 (21%) | 50,155 (21%) | 59,935 (21%) | 2,069,765 (21%) | |
| Northeast | 1,908,054 (18%) | 28,855 (12%) | 49,825 (18%) | 1,829,374 (18%) | |
| West | 2,258,567 (21%) | 48,500 (20%) | 62,925 (22%) | 2,147,142 (21%) | |
| Unknown | 110,129 (1.0%) | 2745 (1.1%) | 2685 (0.9%) | 104,699 (1.0%) | |
| Mechanism type | |||||
| Fall | 8,050,777 (80%) | — | — | 8,050,777 (80%) | <0.001 |
| Struck by/against | 391,770 (3.9%) | — | — | 391,770 (3.9%) | |
| Motor vehicle collision | 1,680,495 (17%) | — | — | 1,680,495 (17%) | |
| Cut/pierce | 287,110 (100%) | — | 287,110 (100%) | — | |
| Firearm | 243,295 (100%) | 243,295 (100%) | — | — | |
| Injury intent | |||||
| Assault | 152,115 (1.4%) | 93,645 (38%) | 58,470 (20%) | — | <0.001 |
| Self-inflicted | 188,700 (1.8%) | 19,100 (7.9%) | 169,600 (59%) | — | |
| Unintentional | 178,920 (1.7%) | 119,970 (49%) | 58,950 (21%) | — | |
| Legal intervention/war | 1575 (.01%) | 1485 (0.6%) | 90 (<0.1%) | — | |
| Undetermined | 9095 (0.1%) | 9095 (3.7%) | * | — | |
| Location of injury | |||||
| Head or neck | 3,312,639 (37%) | 58,305 (26%) | 45,730 (17%) | 3,208,604 (38%) | <0.001 |
| Thorax | 1,028,335 (11%) | 48,765 (21%) | 25,130 (9.4%) | 954,440 (11%) | |
| Torso | 754,325 (8.4%) | 43,935 (19%) | 21,325 (8.0%) | 689,065 (8.1%) | |
| Extremity | 3,715,693 (41%) | 64,660 (28%) | 156,435 (59%) | 3,494,598 (41%) | |
| Multiple | 159,410 (1.8%) | 11,610 (5.1%) | 18,685 (7.0%) | 129,115 (1.5%) | |
| Unknown | 1,683,044 (16%) | 16,020 (6.6%) | 19,805 (6.9%) | 1,647,219 (16%) | |
| Injury Severity score | |||||
| 1–3 | 2,170,484 (26%) | 39,475 (21%) | 146,930 (60%) | 1,984,079 (25%) | <0.001 |
| 4–8 | 2,416,034 (29%) | 22,105 (12%) | 35,195 (14%) | 2,358,734 (30%) | |
| 9–15 | 1,888,334 (23%) | 37,615 (20%) | 36,905 (15%) | 1,813,814 (23%) | |
| 16–24 | 893,910 (11%) | 35,335 (19%) | 14,585 (5.9%) | 843,990 (11%) | |
| 25–74 | 855,220 (10%) | 53,535 (28%) | 11,525 (4.7%) | 790,160 (10%) | |
| 75 | 1145 (<0.1%) | 80 (<0.1%) | * | 1060 (<0.1%) | |
| Unknown | 2,428,319 (23%) | 55,150 (23%) | 41,965 (14.6%) | 2,331,204 (23%) | |
Censored for absolute number of cases ≤10
SD, standard deviation; IQR, interquartile range.
Socioeconomic and Geographic Patterns
The most frequent median household income for firearm-injured patients was the lowest quartile (52%), whereas significantly less patients injured by penetrating or blunt trauma fell in this category (35% and 28%, respectively). Additionally, a trend of increasing firearm injuries from 2017 to 2021 was observed, and these injuries were most commonly seen in teaching hospitals, primarily in southern regions of the US.
Trauma Mechanisms and Injury Location
Next, trauma mechanisms and injury locations were examined. Among patients with blunt trauma, falls accounted for the majority of injuries (79%). Firearm injuries were most frequently classified as unintentional (49%) or assault-related (38%), while penetrating traumas were predominantly self-inflicted (59%). Injury location analysis revealed that the extremities were the most affected region across all trauma mechanisms. Notably, patients with firearm injuries had higher injury severity, with 28% having an ISS of 25 or greater.
Inpatient Course
Firearm-injured patients required over 144,165 interventional procedures (standard error, 1221) based on selected procedural and operative codes during this 5-year study. The number of hospital interventions required differed significantly between groups. Firearm-injured patients required more transfusions and resuscitative procedures, including cardiopulmonary resuscitation and extracorporeal membrane oxygenation than patients sustaining penetrating or blunt traumas. The frequency of various surgical procedures was also higher in firearm-injured patients, including thoracic interventions (eg, pericardiotomy, chest tube placement, and exploratory thoracotomy), brain surgeries (eg, craniotomy), spine surgeries (eg, fusions and drainage), abdominal surgeries (eg, exploratory laparotomy and solid organ resections), extremity surgeries (eg, amputation and fasciotomy), tracheostomies, and feeding tube placements.
Inpatient Complications
Inpatient complications were then compared between trauma mechanisms. Firearm injuries were associated with the highest rate of neurologic complications and septicemia, followed by blunt and penetrating traumas. Differences were also observed in pulmonary, cardiac, and urinary complications. Moreover, firearm-injured patients had a longer mean inpatient length of stay (7.8 days) compared to those with penetrating (5.7 days) and blunt injuries (6.0 days). Inpatient mortality was also higher for firearm-injured patients (6.6%) compared to those with penetrating (0.6%) or blunt traumatic injuries (2.8%). A detailed comparison of hospital course interventions, complications, and disposition by trauma mechanism is provided in Table 2.
TABLE 2.
Inpatient Hospital Course, by Trauma Mechanism
| Hospital Course (Estimated Total NIS Universe) | |||||
|---|---|---|---|---|---|
| All Traumas (N = 10,653,446) |
Firearm Injury (N = 243,295) |
Penetrating Trauma (N = 287,110) |
Blunt Trauma (N = 10,123,041) |
P value | |
| Transfusions | |||||
| Transfusion of nonautologous | 2690 (<0.1%) | 580 (0.2%) | 170 (<0.1%) | 1940 (<0.1%) | <0.001 |
| Transfusion of packed red cells | 675,640 (6.3%) | 28,700 (12%) | 10,805 (3.8%) | 636,135 (6.3%) | <0.001 |
| Transfusion of platelets | 94,065 (0.9%) | 5645 (2.3%) | 1860 (0.6%) | 86,560 (0.9%) | <0.001 |
| Transfusion of coagulation factors | 1475 (<0.1%) | 40 (<0.1%) | 15 (<0.1%) | 1420 (<0.1%) | 0.200 |
| Other transfusion | 108,375 (1.0%) | 11,565 (4.8%) | 3585 (1.2%) | 93,225 (0.9%) | <0.001 |
| Resuscitative measures | |||||
| CPR | 51,650 (0.5%) | 3495 (1.4%) | 700 (0.2%) | 47,455 (0.5%) | <0.001 |
| ECMO | 10,935 (0.1%) | 435 (0.2%) | 170 (<0.1%) | 10,330 (0.1%) | <0.001 |
| Thorax | |||||
| Pericardiotomy | 6115 (<0.1%) | 2020 (0.8%) | 1530 (0.5%) | 2565 (<0.1%) | <0.001 |
| Chest tube | 243,755 (2.3%) | 26,110 (11%) | 17,605 (6.1%) | 200,040 (2.0%) | <0.001 |
| Exploratory thoracotomy | 4490 (<0.1%) | 1300 (0.5%) | 985 (0.3%) | 2205 (<0.1%) | <0.001 |
| Brain | |||||
| Craniotomy for drainage | 73,445 (0.7%) | 2955 (1.2%) | 200 (<0.1%) | 70,290 (0.7%) | <0.001 |
| Excision or extraction of brain | 11,435 (0.1%) | 1520 (0.6%) | 80 (<0.1%) | 9835 (<0.1%) | <0.001 |
| Spine | |||||
| Occipital-cervical spinal fusions | 3635 (<0.1%) | 25 (<0.1%) | * | 3610 (<0.1%) | <0.001 |
| Cervical and cervicothoracic spinal fusions | 86,910 (0.8%) | 470 (0.2%) | 55 (<0.1%) | 86,385 (0.9%) | <0.001 |
| Thoracic and thoracolumbar spinal fusions | 56,625 (0.5%) | 480 (0.2%) | 35 (<0.1%) | 56,110 (0.6%) | <0.001 |
| Lumbar, sacral, and sacro-iliac spinal fusions | 43,470 (0.4%) | 510 (0.2%) | 50 (<0.1%) | 42,910 (0.4%) | <0.001 |
| Inspection and drainage of spinal cord | 2545 (<0.1%) | 80 (<0.1%) | 20 (<0.1%) | 2445 (<0.1%) | 0.04 |
| Abdomen | |||||
| Exploratory laparotomy | 37,375 (0.4%) | 12,365 (5.1%) | 5205 (1.8%) | 19,805 (0.2%) | <0.001 |
| Colorectal resections | 34,665 (0.3%) | 13,480 (5.5%) | 890 (0.3%) | 20,295 (0.2%) | <0.001 |
| Small bowel resections | 19,230 (0.2%) | 8110 (3.3%) | 870 (0.3%) | 10,250 (0.1%) | <0.001 |
| Ostomy creations | 14,950 (0.1%) | 5010 (2.1%) | 360 (0.1%) | 9580 (<0.1%) | <0.001 |
| Splenectomy | 23,965 (0.2%) | 3665 (1.5%) | 625 (0.2%) | 19,675 (0.2%) | <0.001 |
| Liver resections | 2385 (<0.1%) | 1310 (0.5%) | 70 (<0.1%) | 1005 (<0.1%) | <0.001 |
| Gastric resections | 4510 (<0.1%) | 2170 (0.9%) | 270 (<0.1%) | 2070 (<0.1%) | <0.001 |
| Extremities | |||||
| Upper extremity amputations | 1725 (<0.1%) | 95 (<0.1%) | 70 (<0.1%) | 1560 (<0.1%) | <0.001 |
| Lower extremity amputations | 20,755 (0.2%) | 900 (0.4%) | 475 (0.2%) | 19,380 (0.2%) | <0.001 |
| Extremity fasciotomy | 2555 (<0.1%) | 480 (0.2%) | 125 (<0.1%) | 1950 (<0.1%) | <0.001 |
| Respiratory support | |||||
| Tracheostomy | 71,005 (0.7%) | 7950 (3.3%) | 1220 (0.4%) | 61,835 (0.6%) | <0.001 |
| Feeding access | |||||
| Creation of feeding tube | 77,985 (0.7%) | 4210 (1.7%) | 560 (0.2%) | 73,215 (0.7%) | <0.001 |
| Inpatient complications by system | |||||
| Pulmonary | 914,560 (8.6%) | 15,220 (6.3%) | 6,575 (2.3%) | 892,765 (8.8%) | <0.001 |
| Cardiac | 279,755 (2.6%) | 2205 (0.9%) | 1385 (0.5%) | 276,165 (2.7%) | <0.001 |
| Neurologic | 7835 (<0.1%) | 280 (0.1%) | 80 (<0.1%) | 7475 (<0.1%) | <0.001 |
| Urinary | 1,770,089 (17%) | 24,810 (10%) | 17,035 (5.9%) | 1,728,244 (17%) | <0.001 |
| Septicemia | 585,890 (5.5%) | 17,960 (7.4%) | 8795 (3.1%) | 559,135 (5.5%) | <0.001 |
| Inpatient course | |||||
| Length of stay (mean days, ±SD) | 6.0 (±8.2) | 7.8 (±12.3) | 5.7 (±8.3) | 6.0 (±8.1) | <0.001 |
| Length of stay (median days, IQR) | 4.0 (2.0–7.0) | 4.0 (2.0–9.0) | 4.0 (2.0–6.0) | 4.0 (2.0–7.0) | |
| Disposition | |||||
| Died | 298,235 (2.8%) | 15,920 (6.5%) | 1735 (0.6%) | 280,580 (2.8%) | <0.001 |
| Routine | 3,910,754 (37%) | 153,940 (63%) | 218,370 (76%) | 3,538,444 (35%) | |
| Home health care | 1,780,139 (17%) | 29,240 (12%) | 12,830 (4.5%) | 1,738,069 (17%) | |
| Transfer to short-term hospital | 395,160 (3.7%) | 13,770 (5.7%) | 13,590 (4.7%) | 367,800 (3.6%) | |
| Transfer, other | 4,262,863 (40%) | 30,035 (12%) | 40,030 (14%) | 4,192,798 (41%) | |
| Discharged alive, unknown destination | 935 (<0.1%) | 40 (<0.1%) | * | 895 (<0.1%) | |
| Unknown | 5360 (<0.1%) | 350 (0.1%) | 555 (0.2%) | 4455 (0.04%) | |
Censored for absolute number of cases ≤10.
CPR indicates cardiopulmonary resuscitation; ECMO, extracorporeal membrane oxygenation; SD, standard deviation; IQR, interquartile range.
Hospital Costs
Finally, the primary outcome, hospital cost (derived from hospital charges), was analyzed in relation to trauma mechanisms. The total charges associated with firearm injuries were approximately $32,002,213,182 over the 5-year study period, and total costs were $7,011,524,116. Hospital costs differed significantly by trauma mechanism, with firearm injuries incurring the highest mean total costs of $30,529 compared to penetrating and blunt injuries ($12,243 and $18,333, respectively) (Table 3). Costs were additionally adjusted to account for inflation each year and remained highest for firearm injuries ($29,224) compared to penetrating and blunt injuries ($11,764 and $17,594, respectively). The negative binomial models identified several factors influencing hospital inflation-adjusted costs. Notably, in both univariable and multivariable analysis, firearm injury was found to be significantly associated with increased hospital costs compared to blunt traumatic injuries [adjusted IRR (aIRR) 1.256 (95% CI = 1.251–1.261), P < 0.001]. Penetrating injuries were associated with decreased hospital costs [aIRR 0.655 (95% CI = 0.652–0.657), P < 0.001]. The results of both univariable and multivariable negative-binomial models are displayed in Table 4 and Figure 1.
TABLE 3.
Hospital Costs and Inflation Adjusted Costs Per Year
| Hospital Costs (Estimated Total NIS Universe) | ||||
|---|---|---|---|---|
| Firearm Injury (N = 243,295) |
Penetrating Trauma (N = 287,110) |
Blunt Trauma (N = 10,123,041) |
P value | |
| Costs (mean ± SD) | <0.001 | |||
| 2017 | 27,496 (±41,263) | 11,278 (±21,539) | 16,406 (±22,830) | |
| 2018 | 26,846 (±39,982) | 11,164 (±20,858) | 16,676 (±22,703) | |
| 2019 | 29,267 (±42,204) | 12,092 (±20,703) | 17,816 (±24,998) | |
| 2020 | 32,168 (±49,107) | 13,022 (±19,775) | 19,720 (±27,718) | |
| 2021 | 35,110 (±57,589) | 13,756 (±23,009) | 20,965 (±29,467) | |
| All years | 30,529 (±47,394) | 12,243 (±21,217) | 18,333 (±25,768) | |
| Costs adjusted for inflation (mean ± SD) | <0.001 | |||
| 2017 | 27,496 (±41,263) | 11,278 (±21,539) | 16,406 (±22,830) | |
| 2018 | 26,282 (±39,142) | 10,929 (±20,420) | 16,326 (±22,227) | |
| 2019 | 28,214 (±40,684) | 11,657 (±19,957) | 17,175 (±24,098) | |
| 2020 | 30,270 (±46,209) | 12,253 (±18,608) | 18,557 (±26,082) | |
| 2021 | 32,582 (±53,443) | 12,766 (±21,353) | 19,456 (±27,345) | |
| All years | 29,224 (±45,137) | 11,764 (±20,415) | 17,594 (±24,639) | |
SD, standard deviation.
FIGURE 1.
Influencers of hospital costs. Multivariable analysis examining predictors of hospital costs. aIRR indicates adjusted incidence rate ratio.
DISCUSSION
This study aimed to characterize hospital resource utilization associated with firearm injuries. Our findings underscore the increasing frequency of firearm injuries and their associated physical and financial costs. Specifically, we identified that firearm injuries disproportionately affect young, Black males and require significant resuscitative and life-altering procedures, invasive surgeries, and long inpatient stays than other traumatic injuries. In addition to the direct costs of hospitalization, firearm injuries result in increased long-term morbidity and a high risk of mortality. Altogether, this highlights an alarming burden on individuals and health systems conferred by firearms.
As a mechanism of traumatic injury, firearms impart significant physical injury, as evidenced by our data demonstrating higher ISS (with ISS >25 in 28% of patients with firearm injury vs. 4.7% and 10% for penetrating and blunt trauma) and greater inpatient mortality (6.6% with firearm injury vs 0.6% and 2.8% for penetrating and blunt trauma). This is likely due to the destructive ballistic nature of bullets, whose impact extends along the path of injury and beyond anatomic boundaries, thus carrying a significant mortality risk.15 The burden of firearm injuries expands beyond lives lost, as survivors face both immediate and long-term sequelae after injuries, imparting an immeasurable burden. Firearm-injured patients required more major resuscitative and surgical procedures, experienced high complication rates, and required more days in the hospital. This is consistent with prior research in children, where patients sustaining a penetrating trauma (where ~56% of cases were classified as a firearm injury), required more transfusions and operations, experienced more complications, and required longer inpatient stays than those sustaining a blunt trauma.14 The increased frequency of life-saving and invasive procedures required for firearm injuries imparts a significant physical and mental toll on patients and families who face debilitating and painful interventions to address complex injuries.16 Moreover, high complication rates and longer hospital stays further contribute to significant physical and mental loads.17 Although the lethality of firearm injuries has been demonstrated previously,7 this is the first study to quantify and characterize a significant inpatient strain on patients.
Despite challenges in studying firearm injury, previous work has attempted to characterize long-term outcomes that persist after the index admission. For example, survivors of firearm injuries suffer secondary debilitating mental health sequelae.18 At long-term follow-up, patients with firearm injuries reported increases in anxiety, substance use, fatigue, and higher risk of long-term disability, unemployment, diminished global health, and worse physical function scores.19–21 Moreover, when directly compared to patients injured by an motor vehicle collision, firearm-injured patients were more likely to have daily pain and worse physical and mental health-related quality of life.22 In children, firearm injury exposure has also been linked to high rates of post-traumatic stress symptoms and high rates of re-injury.23 In addition to mental health sequelae, high rates of feeding tube insertions, ostomy formation, and tracheostomy creations at index admission translate to a lasting physical disability for firearm injury survivors. Although long-term impacts have been recognized, further prospective work is needed to identify preventative solutions and support systems to address this increasing problem.
In addition to the physical and mental impact, the burden of firearm injury carries significant financial consequences. Previously, an emergency department-based evaluation estimated over $369 million in immediate charges for firearm-related visits per year, higher per record compared to other traumatic assaults.5,24 Comparatively, our study revealed greater inpatient costs—specifically with costs estimated to be over $7 billion over the study period. A 2013-based estimate revealed the cost of nonfatal firearm injuries to be approximately $2.5 billion for medical treatment alone, with an additional $23.5 billion for behavioral healthcare, criminal legal response, lost wages, and lost quality of life.25 Estimates of lifetime medical and productivity costs for firearm survivors range from $48 to $175 billion,26,27 and have been valued as high as $557 billion.28 Previous studies suggest a significant gap between firearm-injury and penetrating-injury inpatient-related costs.29 In reality, this discrepancy is even greater when considering the total economic cost associated with longer-term productivity losses and mental health care costs associated with firearm injury.30 In addition, the younger average age of firearm-injured individuals and greater risk of mortality contribute to widening economic costs through years of life lost and the devastating toll on families and communities.31,32
The high medical costs and long-term health impacts of firearm injuries are borne by government programs, private insurance, and out-of-pocket expenses for the uninsured. This study reveals that 58% of firearm-injured patients possess government insurance, highlighting a significant public cost and the socioeconomic factors linked to firearm violence. Previous research showed that the government covered 41% of initial hospitalization costs for firearm injuries, totaling nearly $2.7 billion.33 Additionally, about 30.1% of firearm injury hospitalizations were uninsured.29 Moreover, previous data valued more than 80% of self-pay patients falling below the 50th income percentile, suggesting that this group would be unable to absorb full hospital charges without a third-party negotiator.33 Recent data also indicate rising firearm injury-related costs for Medicaid-insured patients, which disproportionately affect disadvantaged individuals and safety-net hospitals.34
Given high per-hospital costs, astronomical overall hospitalization costs, and low proportion of private insurance coverage, firearm injuries pose a pronounced burden on our healthcare system.35 Importantly, reimbursement for care provided can be problematic, especially for urban safety-net hospitals experiencing high volumes of firearm injuries (in this study, 98% of firearm-injured patients were seen at urban hospitals). There remains a significant gap in reimbursement rates between privately insured patients and Medicare or Medicaid patients.36 Thus, this reimbursement differential may exacerbate the disproportionate burden faced by hospitals caring for increasing numbers of firearm-injured patients. Increasing Medicaid reimbursement rates for firearm-related injuries could significantly impact disparities among patients and families struggling to afford life-saving care.
Recognizing the challenges in studying firearm injury in the United States, there are limitations in this study that warrant discussion. The inclusion criteria utilized required identification of firearm injuries through injury codes in a retrospective fashion through the NIS database, which introduces the possibility of misclassification or missing data. Furthermore, readmissions were not accounted for, and all traumatic cases were treated as independent encounters. Importantly, this study examines the subset of trauma patients admitted to a hospital (eg, initially nonfatal injuries) and does not account for prehospital mortalities. This is particularly relevant in the context of firearm injuries, which have a higher out-of-hospital death rate (projected as high as 57%) compared to other traumatic mechanisms.37 However, since the aim of this study was to better classify the patient and hospital burden (or inpatient resource utilization) associated with firearms as a traumatic mechanism, utilization of the NIS database allowed for direct comparison of firearms to penetrating and blunt traumas for those patients requiring inpatient care. Regarding financial calculations, since HCUP includes only costs billed by the facility, the costs likely underestimate the true costs, instead reflecting an initial cost of hospital care.38 Nevertheless, many limitations are overcome by the comparative nature of firearms as a mechanism versus penetrating or blunt trauma, given that the nature of the data is constant across groups.
CONCLUSIONS
The burden of firearm injury is astronomical, not only borne by the number of patients affected, but by the significant inpatient care required, increased risk of complications, and heightened costs associated with firearm traumas. This burden may be attributed to the increased severity of injury among those hospitalized with firearm injuries. This study revealed more than 243,000 Americans hospitalized for firearm traumas, with the provision of over 100,000 invasive procedures, and $7 billion in inpatient costs or $32 billion in inpatient charges estimated in just 5 years—higher than previous study estimates. These findings build on existing evidence demonstrating the unprecedented toll firearm injuries have on both the patient and healthcare system overall and emphasize the importance of addressing the public health crisis that is firearm violence in this country.
Acknowledgments
Study conception and design: C.S., C.P.N., E.C., B.K.R., and R.K.-C. Acquisition of data: C.S., C.P.N., and E.C. Analysis and interpretation of data: C.P.N., T.C., A.S., C.C., and C.S. Drafting of manuscript: C.P.N. and E.C. Critical revision of manuscript: C.S., C.P.N., E.C., B.K.R., and R.K.-C.
Supplementary Material
Footnotes
Disclosure: The authors declare that they have nothing to disclose. C.S. is funded by the National Institutes of Health and Eunice Kennedy Shriver National Institute of Child Health and Human Development for a project titled “Evaluating Implementation and Feasibility of Evidence-Based Universal Screening and Intervention Strategies for Firearm Injury and Mortality Prevention Among Youth and Adults in Emergency Departments,” grant R61HD104566-01. The funders had no role in the design or conduct of this study.
All other authors received no external funding and have no conflicts of interest to disclose.
For more information on accessing HCUP data, visit AHRQ HCUP (https://hcup-us.ahrq.gov/) and refer to the Data Use Agreement.
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.annalsofsurgery.com).
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