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Objective: To use updated 2021 weighted Pediatric Readiness Score (wPRS) data to identify a threshold level of trauma center emergency department (ED) pediatric readiness. Background: Most children in the United States receive initial trauma care at nonpediatric centers. The aim of the National Pediatric Readiness Project (NPRP) was to ensure that all EDs are prepared to provide quality care for children. Trauma centers reporting the highest quartile of wPRS on the 2013 national assessment have been shown to have lower mortality. Significant efforts have been invested to improve pediatric readiness in the past decade. Study Design: A retrospective cohort of trauma centers that completed the NPRP 2021 national assessment and contributed to the National Trauma Data Bank (NTDB) from 2019 to 2021 was analyzed. Center-specific observed-to-expected mortality estimates for children (0-15 y) were calculated using Pediatric Trauma Quality Improvement Program models. Deterministic linkage was used for transferred patients to account for wPRS at the initial receiving center. Centerspecific mortality odds ratios were then compared across quartiles of wPRS. Results: A total of 66,588 children from 630 centers with a median (interquartile range) wPRS of 79 (66-93) were analyzed. The average observed-to-expected odds of mortality [1.02 (0.97-1.06)] for centers in the highest quartile (wPRS=93) was lower than any of the lowest 3 wPRS quartiles [1.19 (1.14-1.23) (Q1), 1.29 (1.24-1.33) (Q2), and 1.28 (1.19-1.36) (Q3), all P< 0.05). The presence of a pediatric-specific quality improvement plan was the domain with the strongest independent association with mortality [standardized beta -0.095 (-0.146 to -0.044)]. Conclusion: Trauma centers should address gaps in pediatric readiness to include a pediatric-specific quality improvement plan and aim to achieve wPRS =93. [ABSTRACT FROM AUTHOR]

Objective: We used machine learning to identify the highest impact components of emergency department (ED) pediatric readiness for predicting in-hospital survival among children cared for in US trauma centers. Background: ED pediatric readiness is associated with improved short-term and long-term survival among injured children and part of the national verification criteria for US trauma centers. However, the components of ED pediatric readiness most predictive of survival are unknown. Methods: This was a retrospective cohort study of injured children below 18 years treated in 458 trauma centers from January 1, 2012, through December 31, 2017, matched to the 2013 National ED Pediatric Readiness Assessment and the American Hospital Association survey. We used machine learning to analyze 265 potential predictors of survival, including 152 ED readiness variables, 29 patient variables, and 84 ED-level and hospital-level variables. The primary outcome was in-hospital survival. Results: There were 274,756 injured children, including 4585 (1.7%) who died. Nine ED pediatric readiness components were associated with the greatest increase in survival: policy for mental health care (+8.8% change in survival), policy for patient assessment (+7.5%), specific respiratory equipment (+7.2%), policy for reduced-dose radiation imaging (+7.0%), physician competency evaluations (+4.9%), recording weight in kilograms (+3.2%), life support courses for nursing (+1.0%–2.5%), and policy on pediatric triage (+2.5%). There was a 268% improvement in survival when the 5 highest impact components were present. Conclusions: ED pediatric readiness components related to specific policies, personnel, and equipment were the strongest predictors of pediatric survival and worked synergistically when combined. [ABSTRACT FROM AUTHOR]

Background Targeted temperature management (TTM) for out-of-hospital cardiac arrest is associated with improved functional survival and is a class I recommendation in resuscitation guidelines. However, patterns of utilization of TTM and adherence to recommended TTM guidelines in contemporary practice are unknown. Methods and Results In a multicenter, prospective cohort of consecutive adults with non-traumatic out-of-hospital cardiac arrest in the Resuscitation Outcomes Consortium in 2012 to 2015, we identified all adults (≥18 years) who were potential candidates for TTM. Of 37 898 out-of-hospital cardiac arrest patients at 186 hospitals across 10 Resuscitation Outcomes Consortium sites, 8313 survived for ≥4 hours after hospital arrival, of which, 2878 (34.6%) received TTM. Mean age was 61.5 years and 36.3% were women. Median hospital rate of TTM use was 27% (interquartile range [IQR]: 14%, 45%), with an over 2-fold difference across sites after accounting for differences in presentation characteristics (median odds ratio, 2.10 [1.83-2.26]). Notably, TTM utilization decreased during the study period (57.5% [2012] to 26.5% [2015], P<0.001) including among shockable out-of-hospital cardiac arrest (73.4% to 46.3%, P<0.001). When administered, the median rate of deviation from one or more recommended practices was 60% (IQR: 40%, 78%). The median rate for delayed onset of TTM was 13% (IQR: 0%, 25%), varying by 70% for identical patients across 2 randomly chosen hospitals (median odds ratio 1.70 [1.39-1.97]). Similarly, the median rate for TTM <24 hours was 20% (IQR: 0%, 34%) and for achieved temperature <32°C was 18% (IQR: 0%, 39%), with marked variation across sites (median odds ratios of 1.44 [1.18-1.64] and 1.98 [1.62-2.31], respectively). Conclusions There has been a substantial decline in the utilization of TTM with significant variation in its real-world implementation. Further standardization of contemporary post-resuscitation practices, like TTM, is critical to ensure that their potential survival benefit is realized. [ABSTRACT FROM AUTHOR]

Objective: Among children transported by ambulance across the United States, we used machine learning models to develop a risk prediction tool for firearm injury using basic demographic information and home ZIP code matched to publicly available data sources., Methods: We included children and adolescents 0-17 years transported by ambulance to acute care hospitals in 47 states from January 1, 2014 through December 31, 2022. We used 96 predictors, including basic demographic information and neighborhood measures matched to home ZIP code from 5 data sources: EMS records, American Community Survey, Child Opportunity Index, County Health Rankings, and Social Vulnerability Index. We separated children into 0-10 years (preadolescent) and 11-17 years (adolescent) cohorts and used machine learning to develop high-specificity risk prediction models for each age group to minimize false positives., Results: There were 6,191,909 children transported by ambulance, including 21,625 (0.35%) with firearm injuries. Among children 0-10 years (n = 3,149,430 children, 2,840 [0.09%] with firearm injuries), the model had 95.1% specificity, 22.4% sensitivity, area under the curve 0.761, and positive predictive value 0.41% for identifying children with firearm injuries. Among adolescents 11-17 years (n = 3,042,479 children, 18,785 [0.62%] with firearm injuries), the model had 94.8% specificity, 39.0% sensitivity, area under the curve 0.818, and positive predictive value 4.47% for identifying patients with firearm injury. There were 7 high-yield predictors among children and 3 predictors among adolescents, with little overlap., Conclusions: Among pediatric patients transported by ambulance, basic demographic information and neighborhood measures can identify children and adolescents at elevated risk of firearm injuries, which may guide focused injury prevention resources and interventions., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To investigate the relationship between trauma center volume and outcome., Background: The Resuscitation Outcomes Consortium is a network of 11 centers and 60 hospitals conducting emergency care research. For many procedures, high-volume centers demonstrate superior outcomes versus low-volume centers. This remains controversial for trauma center outcomes., Methods: This study was a secondary analysis of prospectively collected data from the Resuscitation Outcomes Consortium multicenter out-of-hospital Hypertonic Saline Trial in patients with Glasgow Coma Scale score of 8 or less (traumatic brain injury) or systolic blood pressure of 90 or less and pulse of 110 or more (shock). Regression analyses evaluated associations between trauma volume and the following outcomes: 24-hour mortality, 28-day mortality, ventilator-free days, Multiple Organ Dysfunction Scale incidence, worst Multiple Organ Dysfunction Scale score, and poor 6-month Glasgow Outcome Scale-Extended score., Results: A total of 2070 patients were evaluated: 1251 in the traumatic brain injury cohort and 819 in the shock cohort. Overall, 24-hour and 28-day mortality was 16% and 25%, respectively. For every increase of 500 trauma center admissions, there was a 7% decreased odds of 24-hour and 28-day mortality for all patients. As trauma center volume increased, nonorgan dysfunction complications increased, ventilator-free days increased, and worst Multiple Organ Dysfunction Scale score decreased. The associations with higher trauma center volume were similar for the traumatic brain injury cohort, including better neurologic outcomes at 6 months, but not for the shock cohort., Conclusions: Increased trauma center volume was associated with increased survival, more ventilator-free days, and less severe organ failure. Trauma system planning and implementation should avoid unnecessary duplication of services.

Background: It remains unclear whether the American College of Surgeons Committee on Trauma (ACSCOT) "step 1" field physiologic criteria could be further restricted without substantially sacrificing sensitivity. We assessed whether more restrictive physiologic criteria would improve the specificity of this triage step without missing high-risk patients., Methods: We analyzed an out-of-hospital, consecutive patient, prospective cohort of injured adults >or=15 years collected from December 1, 2005, to February 28, 2007, by 237 emergency medical service agencies transporting to 207 acute care hospitals in 11 sites across the United States and Canada. Patients were included based on ACSCOT field decision scheme physiologic criteria systolic blood pressure 29 breaths/min, Glasgow Coma Scale score 2 days., Results: Of 7,127 injured persons, 6,259 had complete outcome information and were included in the analysis. There were 3,631 (58.0%) persons with death or LOS >2 days. Using only physiologic measures, the derived rule included advanced airway intervention, shock index >1.4, Glasgow Coma Scale <11, and pulse oximetry <93%. Rule validation demonstrated sensitivity 72% (95% confidence interval: 70%-74%) and specificity 69% (95% confidence interval: 67%-72%). Inclusion of demographic and mechanism variables did not significantly improve performance measures., Conclusions: We were unable to omit or further restrict any ACSCOT step 1 physiologic measures in a decision rule practical for field use without missing high-risk trauma patients.

Objective: Trauma centers improve outcomes compared with nontrauma centers, although the relative benefit of different levels of major trauma centers (Level I vs. Level II hospitals) remains unclear. We sought to determine whether there was a difference in the patient outcome in trauma victims taken to Level I versus Level II trauma centers., Methods: A multicenter, retrospective cohort analysis of all patients with trauma (>15 years), meeting State of Ohio trauma criteria, transported directly from the scene to a Level I or a Level II hospital (27 centers) between January 2003 and December 2006. Propensity score adjustment was used to adjust for nonrandom selection of hospital destination (I vs. II) and included age, emergency medical services (EMS) Glasgow Coma Score, comorbidities, EMS systolic blood pressure, injury type, injury severity, EMS procedures, emergency department procedures, gender, insurance status, and race. A propensity-adjusted multivariable logistic regression model was used to test the association between trauma center level and patient outcomes. Outcomes included in-hospital mortality and discharge destination (skilled nursing facility, rehabilitation center, home)., Results: A total of 18,103 patients were included in the analysis; 10,070 (56%) were transported to a Level I center. Patients taken to Level I centers had more severe injuries, more penetrating injuries, more complications, yet similar unadjusted mortality compared with Level II centers. In adjusted analyses, patients taken to Level I hospitals had improved survival compared with Level II centers (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.56-0.98). Similar results were seen when restricting the analyses to patients with serious injuries (Injury Severity Score > 15; EMS Glasgow Coma Score < 9). Patients treated at Level I hospitals were more likely to be discharged home (OR 1.14, 95% CI 1.05-1.25), or a rehabilitation center or skilled nursing facility (OR 1.39, 95% CI 1.27-1.52)., Conclusions: Patients taken to Level I centers had improved survival and better functional outcomes compared with injured persons taken to Level II hospitals.

Background: Injury is a major cause of death in adults. Although racial disparities in healthcare access and health outcomes are well documented for medical conditions, the influence of race on access to emergent care after injury has received little scrutiny., Objectives: We sought to determine whether race was associated with risk of in-hospital death after injury., Research Design: Data from the Healthcare Cost and Utilization Project (1998-2002) were used to estimate multivariate models of in-hospital mortality, controlling for age, race, gender, comorbid conditions, injury severity, primary payer, median income of zip code of residence, and hospital type. Additional multivariate models were estimated among stratified subsets of patients, including injury severity and hospital type., Subjects: Patients age 18-64 with a primary diagnosis of injury., Results: Relative to injured white patients, black and Asian patients had a higher risk of death [1.5% vs. 2.1% and 2.0%, multivariate odds ratios (OR) = 1.14 and 1.39]. Other racial/ethnic groups showed no significant mortality difference from white patients. In stratified analyses, we found large black-white mortality disparities among mild to moderately injured patients (OR = 1.40, 95% confidence interval: 1.18-1.66), whereas Asian-white disparities were concentrated among more severely injured patients (OR = 1.37, 95% confidence interval: 1.03-1.80)., Conclusions: Black and Asian patients have a higher risk of death after injury than white patients. These data raise important questions about access to quality trauma care for racial minority patients.

Background: Although injured persons presenting to nontertiary hospitals are routinely transferred for further care, it is unknown whether there is an outcome benefit associated with this practice. We sought to assess whether the transfer of injured patients from nontertiary hospital emergency departments (EDs) is associated with improved survival., Methods: This was a retrospective cohort analysis of all consecutive injured children and adults meeting state trauma criteria, presenting to 1 of 42 nontertiary hospital EDs (primarily rural) and requiring either admission or transfer (n = 10,176) from January 1998 through December 2003. Higher level of care transfer was defined as interhospital transfer from the ED to one of six Level I or II trauma centers. Propensity scores were used to adjust for the known nonrandom selection of patients for higher level of care transfer. The outcome measure was inhospital mortality., Results: There were 10,176 trauma patients who presented to nontertiary hospital EDs and were included in the analysis, of which 3,785 (37%) were transferred to a tertiary hospital from the ED. Transfer patients had higher unadjusted mortality (odds ratio [OR] 2.83, 95% confidence interval [CI] 2.06-3.89). After adjusting for the propensity to be transferred, transfer from the ED to a tertiary hospital was associated with a reduction in mortality (OR 0.67, 95% CI 0.48-0.94), which was strongest among patients transferred to Level I hospitals (OR 0.62, 95% CI 0.40-0.95). There was no measurable benefit for patients transferred to Level II hospitals (OR 0.82, 95% CI 0.47-1.43)., Conclusions: After adjusting for injury severity and the nonrandom selection of patients for transfer, trauma patients transferred from nontertiary EDs to major trauma centers had lower inhospital mortality than patients remaining in nontrauma hospitals. Recognition and early transfer of at-risk rural trauma patients may improve survival in a regionalized trauma system.

Objectives: To assess: (1) the relative importance of prehospital physiological measures in identifying high-risk children; (2) whether different age-based criteria should be used for each prehospital physiological measure; and (3) outcome-based appropriate ranges of physiological measures in injured children., Methods: This was a retrospective cohort analysis of injured children 0 to 14 years transported by emergency medical services to 48 statewide hospitals from January 1, 1998, through December 31, 2003. We analyzed prehospital physiological measures, including Glasgow Coma Scale score (GCS), systolic blood pressure (SBP), respiratory rate (RR), heart rate, shock index (heart rate/SBP), and airway intervention. "High-risk" children were defined as those with in-hospital mortality, major nonorthopedic surgery, intensive care unit stay greater than or equal to 2 days, or Injury Severity Score greater than or equal to 16. Specific age groups included 0 to 2 years, 3 to 5 years, 6 to 10 years, and 11 to 14 years., Results: A total of 3877 injured children were included in the analysis, of which 1111 (29%) were high risk. Prehospital GCS was the variable of greatest importance in identifying high-risk children, followed by (in order) airway intervention, RR, heart rate, SBP, and shock index. Age modified the effect of prehospital RR (P = 0.0046), heart rate (P = 0.01), and SBP (P = 0.02). There was a linear relationship between GCS and outcome that was consistent across all ages. Specific age-based ranges of other physiological measures were identified for high-risk children., Conclusions: Prehospital GCS and respiratory compromise were the most important physiological measures in identifying high-risk injured children. Age-specific criteria should be considered for RR, heart rate, and SBP.

Background: Our goal was to use a hospital population-based data set that was a sample of all injured patients admitted to a hospital in the United States to develop universal measures of outcome and processes of care., Methods: Patients with a primary discharge diagnosis of injury (ICD-9 800 to 959) in the HCUP/Nationwide Inpatient Sample for the years 1995 to 2000 were used to estimate the annual number of hospitalized injured patients. Using census data, we calculated age- and sex- adjusted average annual incidence rates for four census regions in the United States: Northeast, Midwest, South and West. Outcomes measured were annual rates per million populations of hospitalization rate, death rate, and potentially ineffective care (PIC) rate defined as >28 days of hospitalization ending in death. Length of stay (LOS) was calculated as total number of days annually hospitalized for injury for census regions per million populations., Results: Incidence rates per million populations and 95% confidence intervals for rate of hospitalizations for injury were: Northeast, 5596 (5338-5853); Midwest, 5516 (5316-5716); South, 5639 (5410-5869); West, 5307 (5071-5543). Incidence rates per million populations and 95% confidence intervals for rate of in-hospital deaths were: Northeast, 129 (119-139); Midwest, 131 (122-139); South, 141 (129-152); West, 114 (106-123). Incidence rates per million populations and 95% confidence intervals for rate of PIC were: Northeast, 11 (10-13); Midwest, 5 (4-5); South, 6 (5-7); West, 4 (3-4). Incidence rates per million populations and 95% confidence intervals for hospital days were: Northeast, 34 (32-36); Midwest, 30 (28-31); South, 30 (29-32); West, 26 (24-27)., Conclusion: Regional differences in outcomes and processes of care for hospitalized injured patients exist and may be influenced by hospital characteristics and region of the country. Research to identify the factors that cause these hospital and regional variations is needed. These observations suggest that to develop a uniform standard for quality of care, it will be essential to have valid and robust hospital population-based measures.