Emergency department pediatric readiness of United States trauma centers in 2021: Trauma center facility characteristics and opportunities for improvement.

BACKGROUND: Emergency department (ED) pediatric readiness has been associated with lower mortality for injured children but has historically been suboptimal in non-pediatric trauma centers. Over the past decade, the National Pediatric Readiness Project (NPRP) has invested resources in improving ED pediatric readiness. This study aimed to quantify current trauma center pediatric readiness and identify associations with center-level characteristics to target further efforts to guide improvement. METHODS: The study cohort included all centers that responded to the 2021 NPRP national assessment and contributed data to the National Trauma Databank (NTDB) the same calendar year. Center characteristics and pediatric (0-15y) volume from the NTDB were linked to weighted pediatric readiness scores (wPRS) obtained from the NPRP assessment. Univariate and multivariable analyses were used to determine associations between wPRS and trauma center type as well as center-level facility characteristics. RESULTS: The wPRS was reported for 77% (749/973) of centers that contributed to the NTDB. ED Pediatric Readiness was highest in ACS level one pediatric trauma centers (PTCs), but wPRS in the highest quartile was seen among all adult and pediatric trauma center types. Independent predictors of high wPRS included ACS level one PTC verification, pediatric trauma volume, and the presence of a PICU. Higher-level adult trauma centers and pediatric trauma centers were more likely to have pediatric-specific physician requirements, pediatric emergency care coordinators, and pediatric quality improvement initiatives. CONCLUSION: ED pediatric readiness in trauma centers remains variable and is predictably lower in centers that lack inpatient resources. There is, however, no aspect of ED pediatric readiness that is constrained to high-level pediatric facilities, and a highest quartile wPRS was achieved in all types of adult centers in our study. Ongoing efforts to improve pediatric readiness for initial stabilization at non-pediatric centers are needed, particularly in centers that routinely transfer children out. LEVEL OF EVIDENCE: Epidemiologic, Level III.

Characteristics of Firearm Injury by Injury Intent: The Need for Tailored Interventions.

INTRODUCTION: While the U.S. has high quality data on firearm-related deaths, less information is available on those who arrive at trauma centers alive, especially those discharged from the emergency department. This study sought to describe characteristics of patients arriving to trauma centers alive following a firearm injury, postulating that significant differences in firearm injury intent might provide insights into injury prevention strategies. METHODS: This was a multi-center prospective cohort study of patients treated for firearm-related injuries at 128 U.S. trauma centers from 3/2021-2/2022. Data collected included patient-level sociodemographic, injury and clinical characteristics, community characteristics, and context of injury. The outcome of interest was the association between these factors and the intent of firearm injury. Measures of urbanicity, community distress, and strength of state firearm laws were utilized to characterize patient communities. RESULTS: 15,232 patients presented with firearm-related injuries across 128 centers in 41 states. Overall, 9.5% of patients died, and deaths were more common among law enforcement and self-inflicted (SI) firearm injuries (80.9% and 50.5%, respectively). These patients were also more likely to have a history of mental illness. SI firearm injuries were more common in older White men from rural and less distressed communities, whereas firearm assaults were more common in younger, Black men from urban and more distressed communities. Unintentional injuries were more common among younger patients and in states with lower firearm safety grades whereas law enforcement-related injuries occurred most often in unemployed patients with a history of mental illness. CONCLUSIONS: Injury, clinical, sociodemographic, and community characteristics among patients injured by a firearm significantly differed between intents. With the goal of reducing firearm-related deaths, strategies and interventions need to be tailored to include community improvement and services that address specific patient risk factors for firearm injury intent. LEVEL OF EVIDENCE: Level III, Prognostic/Epidemiological.

A multi-dimensional approach to identifying high performing trauma centers across the United States.

INTRODUCTION: The differentiators of centers performing at the highest level of quality and patient safety are likely both structural and cultural. We aimed to combine five indicators representing established domains of trauma quality, and to identify and describe the structural characteristics of consistently performing centers. METHODS: Using ACS-TQIP data from 2017-2020, we evaluated five quality measures across several care domains for adult patients in level I and II trauma centers; 1) time to operating room (OR) for patients with abdominal gunshot wounds (GSW) and shock, 2) proportion of patients receiving timely venous thromboembolism (VTE) prophylaxis, 3) failure to rescue (death following a complication), 4) major hospital complications, and 5) mortality. Overall performance was summarized as a composite score incorporating all measures. Centers were ranked from highest to lowest performer. Principal Component Analysis (PCA) showed the influence of each indicator on overall performance and supported the composite score approach. RESULTS: We identified 272 level I and II centers, with 28 and 27 centers in the top and bottom 10%, respectively. Patients treated in high performing centers had significant lower rates of death major complications, and failure to rescue, compared to low performing centers (p < 0.001). The median time to OR for GSW was almost half that in high compared to low performing centers, and rates of timely VTE prophylaxis were over two-fold greater (p < 0.001). Top performing centers were more likely to be level I centers and cared for a higher number of severely injured patients per annum. Each indicator contributed meaningfully to the variation in scores and centers tended to perform consistently across most indicators. CONCLUSIONS: The combination of multiple indicators across dimensions of quality sets a higher standard for performance evaluation and allows the discrimination of centers based on structural elements, specifically level 1 status, and trauma center volume. LEVEL OF EVIDENCE: Prognostic and Epidemiological, III.

Initial Imaging of Pregnant Patients in the Trauma Bay-Discussion and Review of Presentations at a Level-1 Trauma Centre.

Trauma is the leading non-obstetric cause of maternal and fetal mortality and affects an estimated 5-7% of all pregnancies. Pregnant women, thankfully, are a small subset of patients presenting in the trauma bay, but they do have distinctive physiologic and anatomic changes. These increase the risk of certain traumatic injuries, and the gravid uterus can both be the primary site of injury and mask other injuries. The primary focus of the initial management of the pregnant trauma patient should be that of maternal stabilization and treatment since it directly affects the fetal outcome. Diagnostic imaging plays a pivotal role in initial traumatic injury assessment and should not deviate from normal routine in the pregnant patient. Radiographs and focused assessment with sonography in the trauma bay will direct the use of contrast-enhanced computed tomography (CT), which remains the cornerstone to evaluate the potential presence of further management-altering injuries. A thorough understanding of its risks and benefits is paramount, especially in the pregnant patient. However, like any other trauma patient, if evaluation for injury with CT is indicated, it should not be denied to a pregnant trauma patient due to fear of radiation exposure.

Morbidity and Length of Stay After Injury Among People Experiencing Homelessness in North America.

Importance: Traumatic injury is a leading cause of hospitalization among people experiencing homelessness. However, hospital course among this population is unknown. Objective: To evaluate whether homelessness was associated with increased morbidity and length of stay (LOS) after hospitalization for traumatic injury and whether associations between homelessness and LOS were moderated by age and/or Injury Severity Score (ISS). Design, Setting, and Participants: This retrospective cohort study of the American College of Surgeons Trauma Quality Programs (TQP) included patients 18 years or older who were hospitalized after an injury and discharged alive from 787 hospitals in North America from January 1, 2017, to December 31, 2018. People experiencing homelessness were propensity matched to housed patients for hospital, sex, insurance type, comorbidity, injury mechanism type, injury body region, and Glasgow Coma Scale score. Data were analyzed from February 1, 2022, to May 31, 2023. Exposures: People experiencing homelessness were identified using the TQP's alternate home residence variable. Main Outcomes and Measures: Morbidity, hemorrhage control surgery, and intensive care unit (ICU) admission were assessed. Associations between homelessness and LOS (in days) were tested with hierarchical multivariable negative bionomial regression. Moderation effects of age and ISS on the association between homelessness and LOS were evaluated with interaction terms. Results: Of 1 441 982 patients (mean [SD] age, 55.1 [21.1] years; (822 491 [57.0%] men, 619 337 [43.0%] women, and 154 [0.01%] missing), 9065 (0.6%) were people experiencing homelessness. Unmatched people experiencing homelessness demonstrated higher rates of morbidity (221 [2.4%] vs 25 134 [1.8%]; P < .001), hemorrhage control surgery (289 [3.2%] vs 20 331 [1.4%]; P < .001), and ICU admission (2353 [26.0%] vs 307 714 [21.5%]; P < .001) compared with housed patients. The matched cohort comprised 8665 pairs at 378 hospitals. Differences in rates of morbidity, hemorrhage control surgery, and ICU admission between people experiencing homelessness and matched housed patients were not statistically significant. The median unadjusted LOS was 5 (IQR, 3-10) days among people experiencing homelessness and 4 (IQR, 2-8) days among matched housed patients (P < .001). People experiencing homelessness experienced a 22.1% longer adjusted LOS (incident rate ratio [IRR], 1.22 [95% CI, 1.19-1.25]). The greatest increase in adjusted LOS was observed among people experiencing homelessness who were 65 years or older (IRR, 1.42 [95% CI, 1.32-1.54]). People experiencing homelessness with minor injury (ISS, 1-8) had the greatest relative increase in adjusted LOS (IRR, 1.30 [95% CI, 1.25-1.35]) compared with people experiencing homelessness with severe injury (ISS ≥16; IRR, 1.14 [95% CI, 1.09-1.20]). Conclusions and Relevance: The findings of this cohort study suggest that challenges in providing safe discharge to people experiencing homelessness after injury may lead to prolonged LOS. These findings underscore the need to reduce disparities in trauma outcomes and improve hospital resource use among people experiencing homelessness.

Vision Transformer-based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool.

Purpose To develop an automated triage tool to predict neurosurgical intervention for patients with traumatic brain injury (TBI). Materials and Methods A provincial trauma registry was reviewed to retrospectively identify patients with TBI from 2005 to 2022 treated at a specialized Canadian trauma center. Model training, validation, and testing were performed using head CT scans with binary reference standard patient-level labels corresponding to whether the patient received neurosurgical intervention. Performance and accuracy of the model, the Automated Surgical Intervention Support Tool for TBI (ASIST-TBI), were also assessed using a held-out consecutive test set of all patients with TBI presenting to the center between March 2021 and September 2022. Results Head CT scans from 2806 patients with TBI (mean age, 57 years ± 22 [SD]; 1955 [70%] men) were acquired between 2005 and 2021 and used for training, validation, and testing. Consecutive scans from an additional 612 patients (mean age, 61 years ± 22; 443 [72%] men) were used to assess the performance of ASIST-TBI. There was accurate prediction of neurosurgical intervention with an area under the receiver operating characteristic curve (AUC) of 0.92 (95% CI: 0.88, 0.94), accuracy of 87% (491 of 562), sensitivity of 87% (196 of 225), and specificity of 88% (295 of 337) on the test dataset. Performance on the held-out test dataset remained robust with an AUC of 0.89 (95% CI: 0.85, 0.91), accuracy of 84% (517 of 612), sensitivity of 85% (199 of 235), and specificity of 84% (318 of 377). Conclusion A novel deep learning model was developed that could accurately predict the requirement for neurosurgical intervention using acute TBI CT scans. Keywords: CT, Brain/Brain Stem, Surgery, Trauma, Prognosis, Classification, Application Domain, Traumatic Brain Injury, Triage, Machine Learning, Decision Support Supplemental material is available for this article. © RSNA, 2024 See also commentary by Haller in this issue.

Surgical Stabilization of Rib Fractures for Flail Chest: Analysis of Center-Based Variability in Practice and Outcomes.

BACKGROUND: Given the lack of high-quality data on patient selection for surgical stabilization of rib fractures (SSRF), significant variability in practice likely exists across trauma centers. We aimed to determine whether centers with a more liberal approach to SSRF had improved outcomes. METHODS: We performed a retrospective cohort study of adult patients with flail chest admitted to level I or II trauma centers participating in the American College of Surgeons' Trauma Quality Improvement Program. The primary outcome was hospital mortality; secondary outcomes included discharge status, tracheostomy, duration of mechanical ventilation, and hospital length of stay. Logistic regression was performed to calculate center-level observed/expected rates of SSRF and centers were grouped into quintiles from "most liberal" to "most restrictive". Multivariable regression was used to determine the association between these quintiles and outcomes. We also used an instrumental variable analysis to evaluate the association between SSRF and mortality at the patient level. RESULTS: Among 23,619 patients with flail chest across 354 centers, 22% underwent SSRF. Center rates of fixation ranged from 0-88%. Higher rates of SSRF were not associated with lower mortality overall (highest vs. lowest quintile OR 0.86, 95% CI 0.63-1.17). However, centers with a more liberal approach to SSRF had lower rates of independent status at discharge, higher tracheostomy rates, longer duration of mechanical ventilation, and longer hospital and ICU length of stay. The patient level analysis demonstrated that SSRF as was associated with a 25% lower risk of death. CONCLUSIONS: Overall, centers with a liberal approach to SSRF do not show improved outcomes among patients with a flail chest, but have higher resource utilization. Results at the patient level suggest that there is a population likely to benefit but these patients remain to be identified through further research. LEVEL OF EVIDENCE: Prognostic/epidemiological, Level III.

The impact of referring hospital resources on interfacility overtriage: A population-based analysis.

BACKGROUND: Nearly half of patients transferred from non-trauma to trauma centres have minor injuries. The transfer of patients with minor injuries to trauma centres is not associated with any known patient benefit and represents an opportunity to reduce healthcare costs and improve patient experience. In this study, we evaluated the relationship between hospital resources and overtriage, with the objective of identifying targets for system-level intervention. METHODS: We conducted a population-based cohort study of adults, age ≥ 16, presenting with minor injuries to non-trauma centres in Ontario, Canada (2009-2020). The primary outcome was overtriage, defined as transfer to a trauma centre. Hierarchical logistic regression was used to evaluate the association between hospital resources and a patient's likelihood of being overtriaged, adjusting for case-mix. RESULTS: amongst 165,302 patients with minor injuries, 15,641 (9.5 %) were transferred to a trauma centre (overtriage). Presence of a CT scanner, surgical support, or intensive care unit had no impact on a patient's likelihood of overtriage. Relative to community hospitals, presentation to a teaching hospital was independently associated with greater odds of overtriage (OR 2.97, 95 % CI: 1.26-7.00). Accounting for case-mix and resources, the median difference in a patient's odds of overtriage varied 3.7-fold across non-trauma centres (MOR 3.76). CONCLUSIONS: There is significant variability in overtriage across non-trauma centres, even after adjusting for case-mix and hospital resources. These finding suggests that some centres have developed processes to minimize overtriage independent of available resources. Broad implementation of these processes may represent an opportunity for system-wide quality improvement.

Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.

PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been associated with decreases in mortality, multiorgan system failure, and number of blood products used. Various prediction tools have been developed for the initiation of MHP, but no single tool has demonstrated strong prediction with early clinical data. We sought to develop a massive transfusion prediction model using machine learning and early clinical data. METHODS: Using the National Trauma Data Bank from 2013 to 2018, we included severely injured trauma patients and extracted clinical features available from the pre-hospital and emergency department. We subsequently balanced our dataset and used the Boruta algorithm to determine feature selection. Massive transfusion was defined as five units at 4 h and ten units at 24 h. Six machine learning models were trained on the balanced dataset and tested on the original. RESULTS: A total of 326,758 patients met our inclusion with 18,871 (5.8%) requiring massive transfusion. Emergency department models demonstrated strong performance characteristics with mean areas under the receiver-operating characteristic curve of 0.83. Extreme gradient boost modeling slightly outperformed and demonstrated adequate predictive performance with pre-hospital data only, as well as 4-h transfusion thresholds. CONCLUSIONS: We demonstrate the use of machine learning in developing an accurate prediction model for massive transfusion in trauma patients using early clinical data. This research demonstrates the potential utility of artificial intelligence as a clinical decision support tool.

Admitting Hospital Influences on Withdrawal of Life-Sustaining Treatment Decision for Patients With Severe Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Withdrawal of life-sustaining treatment (WLST) in severe traumatic brain injury (TBI) is complex, with a paucity of standardized guidelines. We aimed to assess the variability in WLST practices between trauma centers in North America. METHODS: This retrospective study used data from trauma centers through the American College of Surgeons Trauma Quality Improvement Program between 2017 and 2020. We included adult patients (>16 years) with severe TBI and a documented decision for WLST. We constructed a series of hierarchical logistic regression models to adjust for patient, injury, and hospital attributes influencing WLST; residual between-center variability was characterized using the median odds ratio. The impact of disparate WLST practices was further assessed by ranking centers by their conditional random intercept and assessing mortality, length of stay, and WLST between quartiles. RESULTS: We identified a total of 85 511 subjects with severe TBI treated across 510 trauma centers, of whom 20 300 (24%) had WLST. Patient-level factors associated with increased likelihood of WLST were advanced age, White race, self-pay, or Medicare insurance status (compared with private insurance). Black race was associated with reduced tendency for WLST. Treatment in nonprofit centers and higher-severity intracranial and extracranial injuries, midline shift, and pupil asymmetry also increased the likelihood for WLST. After adjustment for patient and hospital attributes, the median odds ratio was 1.45 (1.41-1.49 95% CI), suggesting residual variation in WLST between centers. When centers were grouped into quartiles by their propensity for WLST, there was increased adjusted mortality and shorter length of stay in fourth compared with first quartile centers. CONCLUSION: We highlighted the presence of contextual phenomena associated with disparate WLST practice patterns between trauma centers after adjustment for case-mix and hospital attributes. These findings highlight a need for standardized WLST guidelines to improve equity of care provision for patients with severe TBI.

Benchmarking Pediatric Trauma Care in Mixed Trauma Centers: Adult Risk-Adjusted Mortality Is Not a Reliable Indicator of Pediatric Outcomes.

BACKGROUND: Trauma center benchmarking has become standard practice for assessing quality. The American College of Surgeons adult trauma center verification standards do not specifically require participation in a pediatric-specific benchmarking program. Centers that treat adults and children may therefore rely solely on adult benchmarking metrics as a surrogate for pediatric quality. This study assessed discordance between adult and pediatric mortality within mixed trauma centers to determine the need to independently report pediatric-specific quality metrics. STUDY DESIGN: A cohort of trauma centers (n = 493, including 347 adult-only, 44 pediatric-only, and 102 mixed) that participated in the American College of Surgeons TQIP in 2017 to 2018 was analyzed. Center-specific observed-to-expected mortality estimates were calculated using TQIP adult inclusion criteria for 449 centers treating adults (16 to 65 years) and using TQIP pediatric inclusion criteria for 146 centers treating children (0 to 15 years). We then correlated risk-adjusted mortality estimates for pediatric and adult patients within mixed centers and evaluated concordance of their outlier status between adults and children. RESULTS: The cohort included 394,075 adults and 97,698 children. Unadjusted mortality was 6.1% in adults and 1.2% in children. Mortality estimates had only moderate correlation ( r = 0.41) between adult and pediatric cohorts within individual mixed centers. Mortality outlier status for adult and pediatric cohorts was discordant in 31% (32 of 102) of mixed centers (weighted Kappa statistic 0.06 [-0.11 to 0.22]), with 78% (23 of 32) of discordant centers having higher odds of mortality for children than for adults (6 centers with average adult mortality and high pediatric mortality and 17 centers with low adult mortality and average pediatric mortality, p < 0.01). CONCLUSIONS: Adult mortality is not a reliable surrogate for pediatric mortality in mixed trauma centers. Incorporation of pediatric-specific benchmarks should be required for centers that admit children.

Internal and external validation of an updated ICD-10-CA to AIS-2005 update 2008 algorithm.

BACKGROUND: Administrative data are a powerful tool for population-level trauma research but lack the trauma-specific diagnostic and injury severity codes needed for risk-adjusted comparative analyses. The objective of this study was to validate an algorithm to derive Abbreviated Injury Scale (AIS-2005 update 2008) severity scores from Canadian International Classification of Diseases (ICD-10-CA) diagnostic codes in administrative data. METHODS: This was a retrospective cohort study using data from the 2009 to 2017 Ontario Trauma Registry for the internal validation of the algorithm. This registry includes all patients treated at a trauma center who sustained a moderate or severe injury or were assessed by a trauma team. It contains both ICD-10-CA codes and injury scores assigned by expert abstractors. We used Cohen's kappa (𝜅) coefficient to compare AIS-2005 Update 2008 scores assigned by expert abstractors to those derived using the algorithm and the intraclass correlation coefficient to compare assigned and derived Injury Severity Scores. Sensitivity and specificity for detection of a severe injury (AIS score, ≥ 3) were then calculated. For the external validation of the algorithm, we used administration data to identify adults who either died in an emergency department or were admitted to hospital in Ontario secondary to a traumatic injury (2009-2017). Logistic regression was used to evaluate the discriminative ability and calibration of the algorithm. RESULTS: Of 41,869 patients in the Ontario Trauma Registry, 41,793 (99.8%) had at least one diagnosis matched to the algorithm. Evaluation of AIS scores assigned by expert abstractors and those derived using the algorithm demonstrated a high degree of agreement in identification of patients with at least one severe injury (𝜅 = 0.75; 95% confidence interval [CI], 0.74-0.76). Likewise, algorithm-derived scores had a strong ability to rule in or out injury with AIS ≥ 3 (specificity, 78.5%; 95% CI, 77.7-79.4; sensitivity, 95.1; 95% CI, 94.8-95.3). There was strong correlation between expert abstractor-assigned and crosswalk-derived Injury Severity Score (intraclass correlation coefficient, 0.80; 95% CI, 0.80-0.81). Among the 130,542 patients identified using administrative data, the algorithm retained its discriminative properties. CONCLUSION: Our ICD-10-CA to AIS-2005 update 2008 algorithm produces reliable estimates of injury severity and retains its discriminative properties with administrative data. Our findings suggest that this algorithm can be used for risk adjustment of injury outcomes when using population-based administrative data. LEVEL OF EVIDENCE: Diagnostic Tests/Criteria; Level II.

Treatment of Acute Traumatic Central Cord Syndrome: A Study of North American Trauma Centers.

BACKGROUND AND OBJECTIVES: Central cord syndrome (CCS) is expected to become the most common traumatic spinal cord injury, yet its optimal management remains unclear. This study aimed to evaluate variability in nonoperative vs operative treatment for CCS between trauma centers in the American College of Surgeons Trauma Quality Improvement Program, identify patient- and hospital-level factors associated with treatment, and determine the association of treatment with outcomes. METHODS: Adults with CCS were identified from the Trauma Quality Improvement Program database (2014-2016). Mixed-effects modeling with a random intercept for trauma centers was used to examine the adjusted association of patient- and hospital-level variables with nonoperative treatment. The random-effects output of the model assessed the risk-adjusted variability in nonoperative treatment across centers. Outlier hospitals were identified, and the median odds ratio was calculated. The adjusted effect of nonoperative treatment on mortality, morbidity, and hospital length of stay (LOS) was examined at the patient and hospital level by mixed-effects regression. RESULTS: Three thousand, nine hundred twenty-eight patients across 255 centers were eligible; of these, 1523 (38.8%) were treated nonoperatively. Older age, noncommercial insurance (odds ratio [OR] 1.26, 95% CI 1.08-1.48, P = .004), absence of fracture (OR 0.58, 95% CI 0.49-0.68, P < .001), severe head injury (OR 1.41, 95% CI 1.09-1.82, P = .008), and comatose presentation (1.82, 95% CI 1.15-2.89, P = .011) were associated with nonoperative treatment. Twenty-eight hospitals were outliers, and the median odds ratio was 2.02. Patients receiving nonoperative treatment had shorter LOS (mean difference -4.65 days). Nonoperative treatment was associated with lesser in-hospital morbidity (OR 0.49, 95% CI 0.37-0.63, P < .001) at the patient level. There was no difference in mortality. CONCLUSION: Operative decision-making for CCS is influenced by patient factors. There remains substantial variability between trauma centers not explained by case-mix differences. Nonoperative treatment was associated with shorter hospital LOS and lesser inpatient morbidity.

Surgeon views on firearm safety counseling in clinical practice: A cross-sectional survey.

BACKGROUND: Firearms are commonplace in the United States, and one proposed strategy to decrease risk of firearm injury is to have physicians counsel their patients about safe firearm ownership. Current rates of firearm safety counseling by surgeons who care for injured people are unknown. METHODS: This study used an anonymous cross-sectional survey derived from previously published survey instruments and was piloted (n = 13) at the annual meeting of the American Association for the Surgery of Trauma (2022). The finalized survey was distributed using a quick response code during two sessions at the 2022 American College of Surgeons Clinical Congress. Eligible participants included the surgeons and surgical trainees who attended these sessions. RESULTS: One hundred fourteen individuals completed the survey (20% response rate), and a majority were male (n = 71 [62.3%]), attending surgeons (n = 108 [94.7%]), and specialized in acute care surgery (n = 72 [63.2%]). Few participants (n = 43 [37.7%]) reported counseling patients on firearm safety as part of their routine clinical practice; however, the majority (n = 102 [89.5%]) believed that surgeons should provide firearm safety counseling. Counseling rates did not vary significantly by age, sex, surgical specialty, or region of practice, but attitudes toward counseling did differ by firearm safety counseling practices ( p = 0.03) and region of practice (0.04). Noted barriers to counseling included lack of time (n = 47 [41.2%]), perceived lack of training (n = 43 [37.7%]), and lack of firearm knowledge/experience (n = 36 [31.6%]). CONCLUSION: Most surgeon respondents did not provide firearm safety counseling to their patients despite the fact the majority believed they should. This suggests that counseling interventions that do not solely rely on surgeons for implementation could increase the number of patients who receive firearm safety guidance during clinical encounters. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.

Withdrawal of Life-Sustaining Treatment for Pediatric Patients With Severe Traumatic Brain Injury.

Importance: The decision to withdraw life-sustaining treatment for pediatric patients with severe traumatic brain injury (TBI) is challenging for clinicians and families with limited evidence quantifying existing practices. Given the lack of standardized clinical guidelines, variable practice patterns across trauma centers seem likely. Objective: To evaluate the factors influencing decisions to withdraw life-sustaining treatment across North American trauma centers for pediatric patients with severe TBI and to quantify any existing between-center variability in withdrawal of life-sustaining treatment practices. Design, Setting, and Participants: This retrospective cohort study used data collected from 515 trauma centers through the American College of Surgeons Trauma Quality Improvement Program between 2017 and 2020. Pediatric patients younger than 19 years with severe TBI and a documented decision for withdrawal of life-sustaining treatment were included. Data were analyzed from January to May 2023. Main Outcomes and Measures: A random intercept multilevel logistic regression model was used to quantify patient, injury, and hospital characteristics associated with the decision to withdraw life-sustaining treatment; the median odds ratio was used to characterize residual between-center variability. Centers were ranked by their conditional random intercepts and quartile-specific adjusted mortalities were computed. Results: A total of 9803 children (mean [SD] age, 12.6 [5.7]; 2920 [29.8%] female) with severe TBI were identified, 1003 of whom (10.2%) had a documented decision to withdraw life-sustaining treatment. Patient-level factors associated with an increase in likelihood of withdrawal of life-sustaining treatment were young age (younger than 3 years), higher severity intracranial and extracranial injuries, and mechanism of injury related to firearms. Following adjustment for patient and hospital attributes, the median odds ratio was 1.54 (95% CI, 1.46-1.62), suggesting residual variation in withdrawal of life-sustaining treatment between centers. When centers were grouped into quartiles by their propensity for withdrawal of life-sustaining treatment, adjusted mortality was higher for fourth-quartile compared to first-quartile centers (odds ratio, 1.66; 95% CI, 1.45-1.88). Conclusions and Relevance: Several patient and injury factors were associated with withdrawal of life-sustaining treatment decision-making for pediatric patients with severe TBI in this study. Variation in withdrawal of life-sustaining treatment practices between trauma centers was observed after adjustment for case mix; this variation was associated with differences in risk-adjusted mortality rates. Taken together, these findings highlight the presence of inconsistent approaches to withdrawal of life-sustaining treatment in children, which speaks to the need for guidelines to address this significant practice pattern variation.

Hospital learning curves for robot-assisted surgeries: a population-based analysis.

BACKGROUND: Robot-assisted surgery has been rapidly adopted. It is important to define the learning curve to inform credentialling requirements, training programs, identify fast and slow learners, and protect patients. This study aimed to characterize the hospital learning curve for common robot-assisted procedures. STUDY DESIGN: This cohort study, using administrative health data for Ontario, Canada, included adult patients who underwent a robot-assisted radical prostatectomy (RARP), total robotic hysterectomy (TRH), robot-assisted partial nephrectomy (RAPN), or robotic portal lobectomy using four arms (RPL-4) between 2010 and 2021. The association between cumulative hospital volume of a robot-assisted procedure and major complications was evaluated using multivariable logistic models adjusted for patient characteristics and clustering at the hospital level. RESULTS: A total of 6814 patients were included, with 5230, 543, 465, and 576 patients in the RARP, TRH, RAPN, and RPL-4 cohorts, respectively. There was no association between cumulative hospital volume and major complications. Visual inspection of learning curves demonstrated a transient worsening of outcomes followed by subsequent improvements with experience. Operative time decreased for all procedures with increasing volume and reached plateaus after approximately 300 RARPs, 75 TRHs, and 150 RPL-4s. The odds of a prolonged length of stay decreased with increasing volume for patients undergoing a RARP (OR 0.87; 95% CI 0.82-0.92) or RPL-4 (OR 0.77; 95% CI 0.68-0.87). CONCLUSION: Hospitals may adopt robot-assisted surgery without significantly increasing the risk of major complications for patients early in the learning curve and with an expectation of increasing efficiency.

Association Between Geospatial Access to Trauma Center Care and Motor Vehicle Crash Mortality in the United States.

BACKGROUND: Motor vehicle crashes (MVCs) are a leading cause of preventable trauma death in the United States (US). Access to trauma center care is highly variable nationwide. The objective of this study was to measure the association between geospatial access to trauma center care and MVC mortality. METHODS: This was a population-based study of MVC-related deaths that occurred in 3,141 US counties (2017-2020). ACS and state-verified level I-III trauma centers were mapped. Geospatial network analysis estimated the ground transport time to the nearest trauma center from the population-weighted centroid for each county. In this way, the exposure was the predicted access time to trauma center care for each county population. Hierarchical negative binomial regression measured the risk-adjusted association between predicted access time and MVC mortality, adjusting for population demographics, rurality, access to trauma resources, and state traffic safety laws. RESULTS: We identified 92,398 crash fatalities over the four-year study period. Trauma centers mapped included 217 level I, 343 level II, and 495 level III trauma centers. The median county predicted access time was 47 min (IQR 26-71 min). Median county MVC mortality was 12.5 deaths/100,000 person-years (IQR 7.4-20.3 deaths/100,000 person-years). After risk-adjustment, longer predicted access times were significantly associated with higher rates of MVC mortality (>60 min vs. <15 min; MRR 1.36; 95%CI 1.31-1.40). This relationship was significantly more pronounced in urban/suburban vs. rural/wilderness counties (p for interaction, <0.001). County access to trauma center care explained 16% of observed state-level variation in MVC mortality. CONCLUSIONS: Geospatial access to trauma center care is significantly associated with MVC mortality and contributes meaningfully to between-state differences in road traffic deaths. Efforts to improve trauma system organization should prioritize access to trauma center care to minimize crash fatalities. LEVEL OF EVIDENCE: Level III, Epidemiological.

Firearm injuries in Missouri.

Firearm deaths continue to be a major public health problem, but the number of non-fatal firearm injuries and the characteristics of patients and injuries is not well known. The American College of Surgeons Committee on Trauma, with support from the National Collaborative on Gun Violence Research, leveraged an existing data system to capture lethal and non-lethal injuries, including patients treated and discharged from the emergency department and collect additional data on firearm injuries that present to trauma centers. In 2020, Missouri had the 4th highest firearm mortality rate in the country at 23.75/100,000 population compared to 13.58/100,000 for the US overall. We examined the characteristics of patients from Missouri with firearm injuries in this cross-sectional study. Of the overall 17,395 patients, 1,336 (7.7%) were treated at one of the 11 participating trauma centers in Missouri during the 12-month study period. Patients were mostly male and much more likely to be Black and uninsured than residents in the state as a whole. Nearly three-fourths of the injuries were due to assaults, and overall 7.7% died. Few patients received post-discharge services.

Factors influencing withdrawal of life-supporting treatment in cervical spinal cord injury: a large multicenter observational cohort study.

BACKGROUND: Traumatic spinal cord injury (SCI) leads to profound neurologic sequelae, and the provision of life-supporting treatment serves great importance among this patient population. The decision for withdrawal of life-supporting treatment (WLST) in complete traumatic SCI is complex with the lack of guidelines and limited understanding of practice patterns. We aimed to evaluate the individual and contextual factors associated with the decision for WLST and assess between-center differences in practice patterns across North American trauma centers for patients with complete cervical SCI. METHODS: This retrospective multicenter observational cohort study utilized data derived from the American College of Surgeons Trauma Quality Improvement Program database between 2017 and 2020. The study included adult patients (> 16 years) with complete cervical SCI. We constructed a multilevel mixed effect logistic regression model to adjust for patient, injury and hospital factors influencing WLST. Factors associated with WLST were estimated through odds ratios with 95% confidence intervals. Hospital variability was characterized using the median odds ratio. Unexplained residual variability was assessed through the proportional change in variation between models. RESULTS: We identified 5070 patients with complete cervical SCI treated across 477 hospitals, of which 960 (18.9%) had WLST. Patient-level factors associated with significantly increased likelihood of WLST were advanced age, male sex, white race, prior dementia, low presenting Glasgow Coma Scale score, having a pre-hospital cardiac arrest, SCI level of C3 or above, and concurrent severe injury to the head or thorax. Patient-level factors associated with significantly decreased likelihood of WLST included being racially Black or Asian. There was significant variability across hospitals in the likelihood for WLST while accounting for case-mix, hospital size, and teaching status (MOR 1.51 95% CI 1.22-1.75). CONCLUSIONS: A notable proportion of patients with complete cervical SCI undergo WLST during their in-hospital admission. We have highlighted several factors associated with this decision and identified considerable variability between hospitals. Further work to standardize WLST guidelines may improve equity of care provided to this patient population.

Firearm Injuries treated at Trauma Centers in the United States.

BACKGROUND: While firearm injuries and deaths continue to be a major public health problem, the number of non-fatal firearm injuries and the characteristics of patients is not well known. The American College of Surgeons (ACS) Committee on Trauma leveraged an existing data system to collect additional data on fatal and non-fatal firearm injuries presenting to trauma centers. This report provides an overview of this initiative and highlights the challenges associated with capturing actionable data on firearm-injured patients. METHODS: 128 trauma centers that are part of the ACS Trauma Quality Improvement Program (TQIP) collected data on individuals of any age arriving alive between March 1, 2021 and February 28, 2022 with a firearm injury. In addition to the standard data collected for TQIP, abstractors also extracted additional data specific to this study. We linked data from the Distressed Community Index (DCI) to patient records using zip code of residence. RESULTS: A total of 17,395 patients were included, with mean (SD) age of 30.2 (13.5) years, 82.5% were male and the majority were Black and non-Hispanic. The mean proportion of variables with missing data varied among trauma centers, with a mean of 20.7% missing data. Injuries occurred most commonly in homes (31.2%) or on the street (26.6%); 70.4% of injuries were due to assaults. Nearly one-third of patients were discharged from the ED, 25.9% were admitted directly to the operating room, 10.9% to the ICU; 5.9% died in the ED and 10.3% died overall during their course of care. Nearly two-thirds of patients lived in the two highest distressed categories of communities; only 7.5% lived in the least distressed quintile. CONCLUSIONS: Utilizing trauma center data can be a valuable tool to improve our knowledge of firearm injuries if clinical practices and documentation of patient risks and circumstances are standardized. LEVEL OF EVIDENCE: III Level, epidemiological.