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Background: End-of-life (EOL) care is associated with high resource utilization. Recognizing and effectively communicating that EOL is near promotes more patient-centered care, while decreasing futile interventions. We hypothesize that provider assessment of futility during the surgical intensive care unit (SICU) admission would result in higher rates of Do Not Resuscitate (DNR)., Methods: We performed a retrospective review of a prospective SICU registry of all deceased patients across a health system, 2018-2022. The registry included a subjective provider assessment of patient's expected survival. We employed multivariable logistic regression to adjust for clinical factors while assessing for association between code status at death and provider's survival assessment with attention to race-based differences., Results: 746 patients-105 (14.1%) traumatically injured and 641 (85.9%) non-traumatically injured-died over 4.5 years in the SICU (mortality rate 5.9%). 26.3% of these deaths were expected by the ICU provider. 40.9% of trauma patients were full code at the time of death, compared with 15.6% of non-traumatically injured patients. Expected death was associated with increased odds of DNR code status for non-traumatically injured patients (OR 1.8, 95% CI 1.03 to 3.18), but not for traumatically injured patients (OR 0.82, 95% CI 0.22 to 3.08). After adjusting for demographic and clinical characteristics, black patients were less likely to be DNR at the time of death (OR 0.49, 95% CI 0.32 to 0.75)., Conclusion: 20% of patients who died in our SICU had not declared a DNR status, with injured black patients more likely to remain full code at the time of death. Further evaluation of this cohort to optimize recognition and communication of EOL is needed to avoid unnecessary suffering., Level of Evidence: Level III/prognostic and epidemiological., Competing Interests: None declared., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Although timely access to trauma center (TC) care for injured patients is essential, the proliferation of new TCs does not always improve outcomes. Hospitals may seek TC accreditation for financial reasons, rather than to address community or geographic need. Introducing new TCs risks degrading case and payer mix at established TCs. We hypothesized that newly accredited TCs would see a disproportionate share of commercially insured patients., Study Design: We collected data from all accredited adult TCs in Pennsylvania using the state trauma registry from 1999 to 2018. As state policy regarding supplemental reimbursement for underinsured patients changed in 2004, we compared patient characteristics and payer mix between TCs established before and after 2004. We used multivariable logistic regression to assess the relationship between payer and presentation to a new versus established TC in recent years., Results: Over time, there was a 40% increase in the number of TCs from 23 to 38. Of 326 204 patients from 2010 to 2018, a total of 43 621 (13.4%) were treated at 15 new TCs. New TCs treated more blunt trauma and less severely injured patients (p<0.001). In multivariable analysis, patients presenting to new TCs were more likely to have Medicare (OR 2.0, 95% CI 1.9 to 2.1) and commercial insurance (OR 1.6, 95% CI 1.5 to 1.6) compared with Medicaid. Over time, fewer patients at established TCs and more patients at new TCs had private insurance., Conclusions: With the opening of new centers, payer mix changed unfavorably at established TCs. Trauma system development should consider community and regional needs, as well as impact on existing centers to ensure financial sustainability of TCs caring for vulnerable patients., Level of Evidence: Level III, prognostic/epidemiological., Competing Interests: None declared., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Many emergency general surgery (EGS) conditions can be managed operatively or nonoperatively, with outcomes that vary by diagnosis. We hypothesized that operative management would lead to higher in-hospital costs but to cost savings over time., Background: EGS conditions account for $28 billion in health care costs in the United States annually. Compared with scheduled surgery, patients who undergo emergency surgery are at increased risk of complications, readmissions, and death, with accompanying costs of care that are up to 50% higher than elective surgery. Our prior work demonstrated that operative management had variable impacts on clinical outcomes depending on the EGS condition., Methods: This was a nationwide, retrospective study using fee-for-service Medicare claims data. We included patients 65.5 years of age or older with a principal diagnosis for an EGS condition 7/1/2015-6/30/2018. EGS conditions were categorized as: colorectal, general abdominal, hepatopancreaticobiliary (HPB), intestinal obstruction, and upper gastrointestinal. We used near-far matching with a preference-based instrumental variable to adjust for confounding and selection bias. Outcomes included Medicare payments for the index hospitalization and at 30, 90, and 180 days., Results: Of 507,677 patients, 30.6% received an operation. For HPB conditions, costs for operative management were initially higher but became equivalent at 90 and 180 days. For all others, operative management was associated with higher inpatient costs, which persisted, though narrowed, over time. Out-of-pocket costs were nearly equivalent for operative and nonoperative management., Conclusions: Compared with nonoperative management, costs were higher or equivalent for operative management of EGS conditions through 180 days, which could impact decision-making for clinicians, patients, and health systems in situations where clinical outcomes are similar., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Urban firearm violence (UFV) is associated with inequities rooted in structural racism and socioeconomic disparities. Social vulnerability index (SVI) is a composite measure that encompasses both. We sought to understand the relationship between SVI and the incidence of UFV in Chicago using geospatial analysis for the first time., Materials and Methods: Firearm assaults in Chicago 2001-2019 were obtained from the Trace. Locations of incidents were geocoded using ArcGIS and overlaid with census tract vector files. These data were linked to 2018 SVI measures obtained from the Center for Disease Control and Prevention. Shooting rates were calculated by tabulating the total number of shootings per capita in each census tract. We used Poisson regression with robust error variance to estimate the incident rate of UFV in different levels of social vulnerability and Local Moran's I to evaluate spatial autocorrelation., Results: In total, 642 census tracts were analyzed. The median shooting rate was 2.6 per 1000 people (interquartile 0.77, 7.0). When compared to those census tracts with very low SVI, census tracts with low SVI had a 1.7-time increased incident rate of shootings (incidence rate ratio [IRR] 1.74, 95% CI 1.08, 2.81), tracts with moderate SVI had a 3.1-time increased incident rate (IRR 3.07, 95% CI 2.31, 4.10), and tracts with high SVI had a 7-time increased incident rate (IRR 7.03, 95% CI 5.45, 9.07)., Conclusions: In Chicago, social vulnerability has a significant association with rates of firearm violence, providing a focus point for policy intervention to address high rates of interpersonal violence in similar cities., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objective: This study aims to identify modifiable factors related to firearm homicide (FH)., Summary Background Data: Many socioeconomic, legislative and behavioral risk factors impact FH. Most studies have evaluated these risk factors in isolation, but they coexist in a complex and ever-changing American society. We hypothesized that both restrictive firearm laws and socioeconomic support would correlate with reduced FH rates., Methods: To perform our ecologic cross-sectional study, we queried the Centers for Disease Control (CDC) Wide-ranging ONline Data for Epidemiologic Research (WONDER) and Federal Bureau of Investigation (FBI) Uniform Crime Reporting (UCR) for 2013-2016 state FH data. We retrieved firearm access estimates from the RAND State-Level Firearm Ownership Database. Alcohol use and access to care data were captured from the CDC Behavioral Risk Factor Surveillance System (BRFSS). Detached youth rates, socioeconomic support data and poverty metrics were captured from US Census data for each state in each year. Firearm laws were obtained from the State Firearms Law Database. Variables with significant FH association were entered into a final multivariable panel linear regression with fixed effect for state., Results: A total of 49,610 FH occurred in 2013-2016 (median FH rate: 3.9:100,000, range: 0.07-11.2). In univariate analysis, increases in concealed carry limiting laws ( P =0.012), detached youth rates ( P <0.001), socioeconomic support ( P <0.001) and poverty rates ( P <0.001) correlated with decreased FH. Higher rates of heavy drinking ( P =0.036) and the presence of stand your ground doctrines ( P =0.045) were associated with increased FH. Background checks, handgun limiting laws, and weapon access were not correlated with FH. In multivariable regression, increased access to food benefits for those in poverty [β: -0.132, 95% confidence interval (CI): -0.182 to -0.082, P <0.001] and laws limiting concealed carry (β: -0.543, 95% CI: -0.942 to -0.144, P =0.008) were associated with decreased FH rates. Allowance of stand your ground was associated with more FHs (β: 1.52, 95% CI: 0.069-2.960, P <0.040)., Conclusions: The causes and potential solutions to FH are complex and closely tied to public policy. Our data suggests that certain types of socioeconomic support and firearm restrictive legislation should be emphasized in efforts to reduce firearm deaths in America., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Higher center-level operative volume is associated with lower mortality after complex elective surgeries, but this relationship has not been robustly demonstrated for operative trauma. We hypothesized that trauma centers in Pennsylvania with higher operative trauma volumes would have lower risk-adjusted mortality rates than lower volume institutions., Methods: We queried the Pennsylvania Trauma Outcomes Study database (2017-2019) for injured patients 18 years or older at Level I and II trauma centers who underwent an International Classification of Diseases, Tenth Revision (ICD-10), procedure code -defined operative procedure within 6 hours of admission. The primary exposure was tertile of center-level operative volume. The primary outcome of interest was inpatient mortality. We entered factors associated with mortality in univariate analysis (age, injury severity, mechanism, physiology) into multivariable logistic regression models with tertiles of volume accounting for center-level clustering. We conducted secondary analyses varying the form of the association between the volume and mortality to including dichotomous and fractional polynomial models., Results: We identified 3,650 patients at 29 centers meeting the inclusion criteria. Overall mortality was 15.9% (center-level range, 6.7-34.2%). Operative procedure types were cardiopulmonary (7.3%), vascular (20.1%), abdominopelvic (24.3%), and multiple (48.3%). The mean annual operative volume over the 3 years of data was 10 to 21 operations for low-volume centers, 22 to 47 for medium-volume centers, and 47 to 158 for high-volume centers. After controlling for patient demographics, physiology, and injury characteristics, there was no significant difference in mortality between highest and lowest tertile centers (odds ratio, 0.92; confidence interval, 0.57-1.49). Secondary analyses similarly demonstrated no relationship between center operative volume and mortality in key procedure subgroups., Conclusion: In a mature trauma system, we found no association between center-level operative volume and mortality for patients who required early operative intervention for trauma. Efforts to standardize the care of seriously injured patients in Pennsylvania may ensure that even lower-volume centers are prepared to generate satisfactory outcomes., Level of Evidence: Prognostic and Epidemiological; Level III., (Copyright © 2022 American Association for the Surgery of Trauma.)

Objective: We aimed to determine whether gentrification predicts the movement of shooting victims over time and if this process has decreased access to care., Background: Trauma centers remain fixed in space, but the populations they serve do not. Nationally, gentrification has displaced disadvantaged communities most at risk for violent injury, potentially decreasing access to care. This process has not been studied, but an increase of only 1 mile from a trauma center increases shooting mortality up to 22%., Methods: We performed a cross-sectional study utilizing Philadelphia Police Department (PPD) and Pennsylvania trauma systems outcome (PTOS) data 2006-2018. Shootings were mapped and grouped into census tracts. They were then cross-mapped with gentrification data and hospital location. PPD and PTOS shooting data were compared to ensure patients requiring trauma care were captured. Census tracts with ≥500 residents with income and median home values in the bottom 40th percentile of the metropolitan area were eligible to gentrify. Tracts were gentrified if residents ≥25 with a bachelor's degree increased and home price increased to the top third in the metropolitan area. Change in distribution of shootings and its relation to gentrification was our primary outcome while proximity of shootings to a trauma center was our secondary outcome., Results: Thirty-two percent (123/379) of eligible tracts gentrified and 31,165 shootings were captured in the PPD database. 9090 (29.2%) patients meeting trauma criteria were captured in PTOS with an increasing proportion over time. The proportion of shootings within gentrifying tracts significantly dropped 2006-2018 (40%-35%, P < 0.001) and increased in non-gentrifying tracts (52%-57%, P < 0.001). In evaluation of shooting densities, a predictable redistribution occurred 2006-2018 with incident density decreasing in gentrified areas and increasing in non-gentrified areas. Shootings within 1 mile of a trauma center increased overall, but proportional access decreased in gentrified areas., Conclusions: Shootings in Philadelphia predictably moved out of gentrified areas and concentrated in non-gentrified ones. In this case study of a national crisis, the pattern of change paradoxically resulted in an increased clustering of shootings around trauma centers in non-gentrified areas. Repetition of this work in other cities can guide future resource allocation and be used to improve access to trauma care., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Pulmonary complications are the most common adverse event after injury and second greatest cause of failure to rescue (death after pulmonary complications). It is not known whether readily accessible trauma center data can be used to stratify center-level performance for various complications. Performance variation between trauma centers would allow sharing of best practices among otherwise similar hospitals. We hypothesized that high-, average-, and low-performing centers for pulmonary complication and failure to rescue could be identified and that hospital factors associated with success and failure could be discovered., Methods: Pennsylvania state trauma registry data (2007-2015) were abstracted for pulmonary complications. Burns and age <17 were excluded. Multivariable logistic regression models were developed for pulmonary complication and failure to rescue, using demographics, comorbidities, and injuries/physiology. Expected event rates were compared with observed rates to identify outliers. Center-level variables associated with outcomes of interest were taken from the American Hospital Association Annual Survey Database and assessed for inclusion., Results: Included in the study were 283,121 patients (male [60%] blunt trauma [92%]). Of these patients, 3% (8,381 of 283,121) developed pulmonary complications (center-level range 0.18%-5.8%). The percentage of failure-to-rescue patients was 13.4% (1,120/8,381, center-level range 0.0%-22.6%). For pulmonary complications, 13 out of 27 centers were high performers (95% CI for O:E ratio <1) and 7 out of 27 were low (95% CI for an O:E ratio >1). For failure-to-rescue patients, 2 out of 27 centers were low performers and the remainder average. There was little concordance between performance for pulmonary complications and failure to rescue. Research programs, large non-teaching hospitals, those with advanced practice providers, and those with health maintenance organizations had reduced failure-to-rescue patients., Conclusion: Factors associated with complications were distinct from those affecting failure to rescue and center-level success in reducing complications often did not translate into success in preventing death once they occurred. Our data demonstrate that high- and low-performing centers and the factors driving success or failure are identifiable. This work serves as a guide for comparing practices and improving outcomes with readily available data., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Public health measures were instituted to reduce COVID-19 spread. A decrease in total emergency department volume followed, but the impact on injury is unknown. With lockdown and social distancing potentially increasing domicile discord, we hypothesized that intentional injury increased during COVID-19, driven primarily by an increase in penetrating trauma., Study Design: A retrospective review of acute adult patient care in an urban Level I trauma center assessed injury patterns. Presenting patient characteristics and diagnoses from 6 weeks pre to 10 weeks post statewide stay-at-home orders (March 16, 2020) were compared, as well as with 2015-2019. Subsets were defined by intentionality (intentional vs nonintentional) and mechanism of injury (blunt vs penetrating). Fisher exact and Wilcoxon tests were used to compare proportions and means., Results: There were 357 trauma patients that presented pre stay-at-home order and 480 that presented post stay-at-home order. Pre and post groups demonstrated differences in sex (35.6% vs 27.9% female; p = 0.02), age (47.4 ± 22.1 years vs 42 ± 20.3 years; p = 0.009), and race (1.4% vs 2.3% Asian; 63.3% vs 68.3% Black; 30.5% vs 22.3% White; and 4.8% vs 7.1% other; p = 0.03). Post stay-at-home order mechanism of injury revealed more intentional injury (p = 0.0008). Decreases in nonintentional trauma after adoption of social isolation paralleled declines in daily emergency department visits. Compared with earlier years, 2020 demonstrated a significantly greater proportion of intentional violent injury during the peripandemic months, especially from firearms., Conclusions: Unprecedented social isolation policies to address COVID-19 were associated with increased intentional injury, especially gun violence. Meanwhile, emergency department and nonintentional trauma visits decreased. Pandemic-related public health measures should embrace intentional injury prevention and management strategies., (Copyright © 2020 American College of Surgeons. All rights reserved.)

Background: Unplanned readmissions of surgical patients are associated with increased morbidity and mortality. "Fragmentation of care" (FOC) occurs when patients are readmitted to a different hospital than where they initially received care. FOC complicates accurate quantification of hospital readmission rates and is associated with worse outcomes in many surgical patient populations. However, few studies have evaluated the impact of FOC specifically on patients with traumatic injury., Materials and Methods: We performed a retrospective cohort study using the 2013 National Readmissions Database. Data on demographics, diagnosis, injury severity, readmissions, complications, and outcomes were collected. Patients readmitted to hospitals within 30 d after index admission were identified, and risk factors for readmission were discerned. Patients were stratified into groups readmitted to index versus nonindex hospital. Outcomes were compared between these groups., Results: A total of 333,188 patients with index admission for injury were identified; 34,197 (10.3%) were readmitted within 30 d of discharge. Of these, only 24,747 (72.4%) were readmitted to their index hospital for an FOC rate of 27.6%. There was no significant difference in outcomes between patients readmitted to index versus nonindex hospitals. Among all readmitted patients, 30-d mortality was associated only with burden of medical comorbidities and age., Conclusions: Single-institution readmission rates are not reflective of true readmission rates for trauma patients. FOC does not impact outcomes in trauma patients who are readmitted; however, age and number of comorbidities are associated with higher mortality in these patients. FOC rates are high in trauma patient populations and merit further investigation to determine potential etiologies and consequences., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Introduction: Cardiac complications (CC) after injury are rare but contribute disproportionately to mortality. Variability in rates of CC and failure to rescue (FTR) after CC (FTR-C) within trauma systems may suggest opportunities for improvement, but we have not yet demonstrated the ability to identify high and low performers. We examined center-level rates of CC and FTR-C in a mature trauma system with the hypothesis that high-performing centers for each of these outcomes could be identified., Methods: Using a statewide trauma registry from 2007-2015, we developed multivariable logistic regression models on CC and FTR-C including patient demographics, physiology, comorbidity, and injury data. Predicted probabilities of each outcome were summed to generate expected event rates, which were compared to observed event rates to generate centerlevel observed-to-expected (O:E) ratios. We measured internal consistency between CC and FTR-C for centers using Cronbach's alpha., Results: Cardiac complications occurred in 5,079/278,042 (1.8%; center-level range: 0.9-3.8%) of included patients (median age 55 (IQR 34-76), 84% Caucasian, 60% male, 92% blunt, median ISS 9 (IQR5-16)). Death after CC occurred in 982/5,097 patients for an FTR-C rate of 19.3% (center-level range: 7.8-30.4%). 10/27 centers were high-performers (95% confidence interval for O:E ratio <1) for CC and 2/27 centers were high-performers for FTR-C, but internal consistency between these metrics was poor (alpha = 0.31)., Conclusion: Rates of CC and FTR-C vary significantly between hospitals in mature trauma systems but high-performing centers can be identified. Inconsistent performance between metrics suggests unknown institutional factors underlie performance for CC and FTR., (Copyright © 2020. Published by Elsevier Ltd.)

Background: Many injured patients presenting to Level III/IV trauma centers will be transferred to Level I/II centers, but how these transfers influence benchmarking at Level III/IV centers has not been described. We hypothesized that the apparent observed to expected (O:E) mortality ratios at Level III/IV centers are influenced by the location at which mortality is measured in transferred patients., Methods: We conducted a retrospective study of adult patients presenting to Level III/IV trauma centers in Pennsylvania from 2008 to 2017. We used probabilistic matching to match patients transferred between centers. We used a risk-adjusted mortality model to estimate predicted mortality, which we compared with observed mortality at discharge from the Level III/IV center (O) or observed mortality at discharge from the Level III/IV center for nontransferred patients and at discharge from the Level I/II center for transferred patients (O)., Results: In total, 9,477 patients presented to 11 Level III/IV trauma centers over the study period (90% white; 49% female; 97% blunt mechanism; median Injury Severity Score, 8; interquartile range, 4-10). Of these, 4,238 (44%) were transferred to Level I/II centers, of which 3,586 (85%) were able to be matched. Expected mortality in the overall cohort was 332 (3.8%). A total of 332 (3.8%) patients died, of which 177 (53%) died at the initial Level III/IV centers (O). Including posttransfer mortality for transferred patients in addition to observed mortality in nontransferred patients (O) resulted in worse apparent O:E ratios for all centers and significant differences in O:E ratios for the overall cohort (O:E, 0.53; 95% confidence interval, 0.45-0.61 vs. O:E, 1.00, 95% confidence interval, 0.92-1.11; p < 0.001)., Conclusion: Apparent O:E mortality ratios at Level III/IV centers are influenced by the timing of measurement. To provide fair and accurate benchmarking and identify opportunities across the continuum of the trauma system, a system of shared attribution for outcomes of transferred patients should be devised.

Introduction: Trauma video review (TVR) for quality improvement and education in the United States has been described for nearly three decades. The most recent information on this practice indicated a declining prevalence. We hypothesized that TVR utilization has increased since most recent estimates., Methods: We conducted a survey of TVR practices at level I and level II US trauma centers. We distributed an electronic survey covering past, current, and future TVR utilization to the Eastern Association for the Surgery of Trauma membership., Results: 45.0% of US level I and level II trauma centers completed surveys. 71/249 centers (28.5%) had active TVR programs. The use of TVR did not differ between level I and level II centers (28.8% vs. 27.8%, p = 0.87). Respondents using TVR were overwhelmingly positive about its perception (median score 8, [IQR 6-9]; 10 = 'best') at their institutions., Conclusions: TVR use at Level I centers has increased over the past decade. Increased TVR utilization may form the basis for multicenter studies comparing processes of care during trauma resuscitation., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: Methadone is associated with QT prolongation and serious cardiac complications, but this has been primarily demonstrated in opioid dependent patients receiving moderate to high doses. This study investigates the effect of low-dose methadone on the QTc interval in a chronic pain population., Design and Subjects: We conducted a prospective cohort study in a chronic pain clinic including 82 patients receiving methadone and 102 patients receiving non-methadone opioid therapy., Methods: We analyzed automated QTc calculations from 12-lead electrocardiograms at baseline and during the subsequent 6 months. The primary outcome of interest was the incidence of QTc greater than 470 milliseconds or an increase from baseline of greater than 60 milliseconds., Results: The methadone group did not manifest an overall higher frequency of QTc > 470 milliseconds (6% for the methadone group vs 5% for controls, P = 0.722) or an increase in the QTc of > 60 milliseconds (4% for the methadone group vs 4% for controls, P = 0.94). In the first month after initiating methadone, patients demonstrated an increase in QTc compared to controls (5% for the methadone group vs 0% for the controls, P = 0.073) but the difference disappeared in the third and sixth months., Conclusion: Data from our chronic pain clinic support a potential association of QTc prolongation during the initiation of methadone, but this effect is small and short lived. We believe larger scale studies to further characterize the safety profile of low-dose methadone are warranted., (Wiley Periodicals, Inc.)