Trauma Center Designation Research Articles

An Educational Outreach Program: A Trauma System's 5-Year Experience.

The American College of Surgeons Committee on Trauma requires Level I and II trauma centers to provide educational outreach to lower-level facilities. Although outreach is a required part of any trauma system, very little is published on the resources required for a successful program. The purpose of this article is to provide a comprehensive roadmap of the required components to achieve a successful trauma outreach program. This project describes the development and implementation of an educational outreach program from January 2016 to December 2020 that has grown from 27 facilities within one western state to 49 facilities across 14 different states. Program components measured include the number and attendance of trauma courses offered, including the Trauma Nursing Core Course (TNCC), Advanced Trauma Life Support (ATLS), Rural Trauma Team Development Course (RTTDC), the number of trauma meetings and webinars provided, total trauma center designation and reviews, total states reached, and total trauma center collaborations. From 2016 to 2020, the program more than doubled the number of TNCC and ATLS courses, maintained the number of RTTDC offered, and observed attendance rate increases of 33% and 11% for TNCC and ATLS courses, respectively. Outreach leadership attended 44 trauma meetings and educational webinars using virtual platform technology, nearly doubling the trauma center outreach with expansion across 14 states resulting in important changes in practice. With administrative support, effective leadership, and technology, outreach programs can serve as important resources for statewide trauma systems.

Blood product availability in the Washington state trauma system.

Early transfusion can prolong life in injured patients awaiting definitive hemorrhage control. We conducted a community resources assessment of blood product availability at hospitals within the Washington State (WA) Regional Trauma System, with the expectation that a minority of Level IV and V centers would have blood products routinely available for use in resuscitation. We designed a questionnaire soliciting information on routinely available unit quantities of red blood cells (RBC), plasma, platelets, cryoprecipitate, and/or whole blood and submitted this questionnaire electronically to the 82 WA designated trauma centers (Levels I-V). Non-responders were contacted directly by telephone. The study was conducted in September and October 2021. US 2020 census data were used to correlate results with local population densities. First-round contact netted responses from 57 (70%) centers; the remaining centers provided information via telephone, for a 100% final response. Packed RBC were available in 79 of the 82 centers (96%; range 6-220 units); plasma, 62 centers (76%, range 1-100 units); platelets, 40 centers (49%, range 1-8units); cryoprecipitate, 45 centers (55%, range 1-20 units). Whole blood was only available at the Level I center. Three Level V centers, located in 2 of the 8 WA state trauma regions, reported no routine blood availability. The two trauma regions affected represent 12% of the state's population and more than a third of its geographic area. Within the WA regional trauma system, blood products are wide, if unevenly, available. Large urban/rural disparities in availability exist that should be explored.

Disparity in Transport of Critically Injured Patients to Trauma Centers: Analysis of the National Emergency Medical Services Information System (NEMSIS).

Patient morbidity and mortality decrease when injured patients meeting CDC Field Triage Criteria (FTC) are transported by emergency medical services (EMS) directly to designated trauma centers (TCs). This study aimed to identify potential disparities in the transport of critically injured patients to TCs by EMS. We identified all patients in the National EMS Information System (NEMSIS) database in the National Association of EMS State Officials East region from January 1, 2018, to December 31, 2019, with a final prehospital acuity of critical or emergent by EMS. The cohort was stratified into patients transported to TCs or non-TCs. Analyses consisted of descriptive epidemiology, comparisons, and multivariable logistic regression analysis to measure the association of demographic features, vital signs, and CDC FTC designation by EMS with transport to a TC. A total of 670,264 patients were identified as sustaining an injury, of which 94,250 (14%) were critically injured. Of those 94,250 critically injured, 56.0% (52,747) were transported to TCs. Among all critically injured women (n = 41,522), 50.4% were transported to TCs compared with 60.4% of critically injured men (n = 52,728, p < 0.001). In a multivariable logistic regression model, critically injured women were 19% less likely to be taken to a TC compared with critically injured men (OR 0.81, 95% CI 0.71-0.93, p = 0.003). Critically injured female patients are less likely to be transported to TCs when compared with their male counterparts. Performance improvement processes that assess EMS compliance with field triage guidelines should explicitly evaluate for sex-based disparities. Further studies are warranted.

Influence of Hospital Characteristics on Hospital Transfer Destinations for Patients With Stroke.

Patients with stroke are frequently transferred between hospitals. This may have implications on the quality of care received by patients; however, it is not well understood how the characteristics of sending and receiving hospitals affect the likelihood of a transfer event. Our objective was to identify hospital characteristics associated with sending and receiving patients with stroke. Using a comprehensive statewide administrative dataset, including all 78 Massachusetts hospitals, we identified all transfers of patients with ischemic stroke between October 2007 and September 2015 for this observational study. Hospital variables included reputation (US News and World Report ranking), capability (stroke center status, annual stroke volume, and trauma center designation), and institutional affiliation. We included network variables to control for the structure of hospital-to-hospital transfers. We used relational event modeling to account for complex temporal and relational dependencies associated with transfers. This method decomposes a series of patient transfers into a sequence of decisions characterized by transfer initiations and destinations, modeling them using a discrete-choice framework. Among 73 114 ischemic stroke admissions there were 7189 (9.8%) transfers during the study period. After accounting for travel time between hospitals and structural network characteristics, factors associated with increased likelihood of being a receiving hospital (in descending order of relative effect size) included shared hospital affiliation (5.8× higher), teaching hospital status (4.2× higher), stroke center status (4.3× and 3.8× higher when of the same or higher status), and hospitals of the same or higher reputational ranking (1.5× higher). After accounting for distance and structural network characteristics, in descending order of importance, shared hospital affiliation, hospital capabilities, and hospital reputation were important factor in determining transfer destination of patients with stroke. This study provides a starting point for future research exploring how relational coordination between hospitals may ensure optimized allocation of patients with stroke for maximal patient benefit.

Association of Trauma Center Designation With Postdischarge Survival Among Older Adults With Injuries

Trauma centers improve outcomes for young patients with serious injuries. However, most injury-related hospital admissions and deaths occur in older adults, and it is not clear whether trauma center care provides the same benefit in this population. To examine whether 30- and 365-day mortality of injured older adults is associated with the treating hospital's trauma center level. This prospective, population-based cohort study used Medicare claims data from January 1, 2013, to December 31, 2016, for all fee-for-service Medicare beneficiaries 66 years or older with inpatient admission for traumatic injury in 2014 to 2015. Data analysis was performed from January 1 to June 31, 2021. Preinjury health was measured using 2013 claims, and outcomes were measured through 2016. The population was stratified by anatomical injury pattern. Propensity scores for level I trauma center treatment were estimated using the Abbreviated Injury Scale, age, and residential proximity to trauma center and then used to match beneficiaries from each trauma level (I, II, III, and IV/non-trauma centers) by injury type. Admitting hospital's trauma center level. Case fatality rates (CFRs) at 30 and 365 days after injury, estimated in the matched sample using multivariable, hierarchical logistic regression models. A total of 433 169 Medicare beneficiaries (mean [SD] age, 82.9 [8.3] years; 68.4% female; 91.5% White) were included in the analysis. A total of 206 275 (47.6%) were admitted to non-trauma centers and 161 492 (37.3%) to level I or II trauma centers. Patients with isolated extremity fracture had the fewest deaths (365-day CFR ranged from 16.1% [95% CI, 11.2%-22.4%] to 17.4% [95% CI, 11.8%-24.6%] by trauma center status). Patients with both hip fracture and traumatic brain injury had the most deaths (365-day CFRs ranged from 33.4% [95% CI, 25.8%-42.1%] to 35.8% [95% CI, 28.9%-43.5%]). These findings suggest that older adults do not benefit from existing trauma center care, which is designed with younger patients in mind. There is a critical need to improve trauma care practices to address common injury mechanisms and types of injury in older adults.

Global Survey of Demand-Side Factors and Incentives that Influence Advanced Trauma Life Support (ATLS) Promulgation.

We aimed to identify and describe demand-side factors that have been used to support ATLS global promulgation, as well as current gaps in demand-side incentives. We performed a cross-sectional survey about demand-side factors that influence the uptake and promulgation of ATLS and other trauma-related CME courses. The survey was sent to each of the four global ATLS region chiefs and 80 ATLS country directors. Responses were described and qualitative data were analyzed using a content analysis framework. Representatives from 30 countries and each region chief responded to the survey (40% response rate). Twenty of 30 country directors (66%) reported that there were some form of ATLS verification requirements. ATLS completion, not current verification, was often the benchmark. Individual healthcare systems were the most common agency to require ATLS verification (37% of countries) followed by medical/surgical accreditation boards (33%), governments (23%), training programs (27%), and professional societies (17%). Multiple credentialing frameworks were reported including making ATLS verification a requirement for: emergency unit or trauma center designation (40%), contract renewal or promotion (37%); professional licensing (37%); training program graduation (37%); and increases in remuneration (3%). Unique demand-side incentives were reported including expansion of ATLS to non-physician cadre credentialing and use of subsidies. ATLS region chiefs and country directors reported a variety of demand-side incentives that may facilitate the promulgation of ATLS. Actionable steps include: (i) shift incentivization from ATLS course completion to maintenance of verification; (ii) develop an incentive toolkit of best practices to support implementation; and (iii) engage leadership stakeholders to use demand-side incentives to improve the training and capabilities of the providers they oversee to care for the injured.

Can ionized calcium levels and platelet counts used for estimating the prognosis of pediatric trauma patients admitted to the emergency surgery intensive care?

Injury is the leading cause of death for pediatric population older than 1 year of age and 95% of those deaths are from the low- and middle-income countries. Most of those injured pediatric patients are treated in general hospitals. In designated trauma centers, the outcomes of severely injured patients are better. Scoring systems used frequently in intensive care units (ICUs) to make triage easier and to estimate prognosis. However, some of the scores may require additional expensive and sometimes time consuming tests. The purpose of the present study was to compare the usefulness of several scoring systems with initial ionized calcium levels and platelet counts to predict prognosis of pediatric trauma patients admitted to the emergency surgery department. This retrospective study was performed at a tertiary university hospital. The patients' ages, genders, trauma etiologies, types of trauma, time of trauma, transport place (primary or secondary), duration of stay in the ICU and in the hospital, mortality rates, initial ionized calcium levels (Ca+2), initial platelet counts, and data of several trauma scores (GCS, RTS, ISS, TRISS, and PTS) were analyzed. One hundred and fourteen pediatric trauma patients were admitted to the ICU. The mean age was 77.8±54 months. Most of them were male, falls were the primary mechanism of injury, and head trauma was the most common pattern of injury. The mortality rate was 15.8%, and the admission values for Ca+2, platelet counts, GCS, RTS, TRISS, and PTS had been found higher for patients who survived, while ISS scores were higher for those who had died. It was found that pediatric patients admitted to the ICU were younger than 10 years, of whom most of them were male. Falls were the most common mechanism of injury, and head trauma was present in most of the pediatric patients admitted to the ICU. Initial Ca+2 levels and platelet counts can be used along with the trauma scoring systems in predicting mortality and overall survey regarding pediatric trauma patients.

Pediatric traumatic brain injury: Resource utilization and outcomes at adult versus pediatric trauma centers

IntroductionTraumatic brain injury is the leading cause of trauma-related death in children. We hypothesized that children with isolated traumatic brain injury would experience differential outcomes when treated at pediatric versus adult or combined trauma centers. MethodsAfter institutional review board approval, the 2015 National Trauma Data Bank was queried for children up to age 16 years with isolated traumatic brain injury. Demographics and clinical outcomes were collected. Univariable and multivariable analyses were conducted to assess for predictors of in-hospital mortality and complications. Kaplan–Meier survival analysis was conducted. ResultsA total of 3,766 children with isolated traumatic brain injury were identified; 1,060 (28%) were treated at pediatric trauma centers, 1,909 (51%) at adult trauma centers, and 797 (21%) at combined trauma centers. Subjects were 5 years old (median, interquartile range 1–12 years), 63% male, and 64% white. Higher blood pressure and lower injury severity score were associated with reduced mortality (P < .05). Increasing injury severity score was associated with higher mortality by multivariable logistic regression (odds ratio 1.57, P < .0001). There were no survival differences among hospital types (P = .88). ConclusionOutcomes for children with isolated traumatic brain injury appear equal across different types of designated trauma centers. These findings may have implications for prehospital transport and triage guidelines.

An Administrative Burden: Identifying Designated Trauma Centers in Administrative Data

An Administrative Burden: Identifying Designated Trauma Centers in Administrative Data

Impact of Trauma Center Designation Level on the Survival of Trauma Patients Transported by Police in the United States

Background: Police involvement in trauma management and transport is increasing in the US. Little is known about prehospital triage criteria and transport patterns used by Police Officers. In this study, we examined the impact of trauma designation level on the survival of trauma patients transported to trauma centers by police. Methods: We used the National Trauma Data Bank (NTDB) 2017 dataset in this retrospective observational study. Adult trauma patients transported by Police to Level I, II and III trauma centers were included. We performed a univariate analysis followed by a bivariate analysis. Finally, we carried out a multivariable logistic regression analysis adjusting for confounders to assess the impact of trauma level designation on outcomes of patients transported by Police. Results: A total of 2,788 patients were included. The majority of the patients were males (84.6%) between the ages of 16 and 55 with half of them being African American. Most had a mild GCS (13–15) (89.5%) and only 17.4% were recorded to have severe traumatic injuries with ISS ≥ 16. The most common trauma type was blunt trauma (61.4%) followed by penetrating injuries (32.2%) and burns (1.5%). Around half of injuries were the result of assault (49.4%) and 43.0% were unintentional. Head and neck injuries were most common (40.8%) followed by extremities (27.4%) and torso injuries (25.0%). Approximately half of the patients were admitted to floor bed/observation unit/step-down unit (50.7%) while 18.9% and 19.8% went to the Operating Room or Intensive Care Unit respectively. Overall survival to hospital discharge was 93.2%. Survival was 91.6% in Level I, 98.2% in level II and 98.7% in Level III centers. After adjusting for significant confounders, survival to hospital discharge was similar for patients transported by police to level II and III trauma centers in comparison to those transported to level I (OR = 0.866 95%CI (0.321–2.333); p = 0.776). Conclusion: Transport of trauma patients by police to trauma centers of different designation levels was not associated with survival in this study. Survival was also similar to other trauma studies. As such, trauma patients may be safely transported by Police to closest trauma designated center without affecting outcomes.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions

Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood. To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes. This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021. Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality). The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes. Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: β = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = -0.50 [95% CI, -1.13 to 0.12]; P = .27). In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

The impact of delayed management of fall-related hip fracture management on health outcomes for African American older adults.

Black hip fracture patients experience worse health outcomes than otherwise similar White patients, but causes of these disparities are not known. We sought to determine if delays in hip fracture surgery and/or hospital structures contribute to racial disparities in hip fracture outcomes. Using 2006 to 2016 Trauma Quality Program Public Use Files, we identified hip fracture patients with primary mechanisms of fall from standing and determined surgical treatment category (no surgery, surgery within 24 hours after arrival, surgery 24-48 hours after arrival, surgery more than 48 hours after arrival) as well as hospital structure characteristics (trauma center designation, teaching status, profit status, bed size). We used generalized structural equation models to conduct path analyses and determine if hip fracture treatment and hospital characteristics mediated the relationship between race (non-Hispanic Black/non-Hispanic White) and outcomes (complications, length of stay, disposition). Non-Hispanic Black patients were more likely than non-Hispanic White patients to receive treatment at an academic medical center (49.1% vs. 28.0%), at a hospital with >600 inpatient beds (39.5% vs. 25.3%), and at a level I or II trauma center (86.8% vs. 77.7%); were more likely to go without hip fracture repair surgery (22.8% vs. 21.4%); and were more likely to have delayed surgery >48 hours after hospital arrival (15.5% vs. 10.6%). Path analysis suggests hip fracture treatment group and hospital characteristics mediate the relationship with complications, length of stay, and disposition. Non-Hispanic Black patients with fall-related hip fracture are more likely to experience delays in care, complications, and longer inpatient stays. Hospital characteristics contribute to increased risk of complications and longer length of stay, both as independent determinants of outcomes and as determinants of delays in hip fracture surgery. Prognostic and epidemiologic, level III.

Clinical Deterioration and Neurocritical Care Utilization in Pediatric Patients With Glasgow Coma Scale Score of 9-13 After Traumatic Brain Injury: Associations With Patient and Injury Characteristics.

To define the clinical characteristics of hospitalized children with moderate traumatic brain injury and identify factors associated with deterioration to severe traumatic brain injury. Retrospective cohort study. Tertiary Children's Hospital with Level 1 Trauma Center designation. Inpatient children less than 18 years old with an International Classification of Diseases code for traumatic brain injury and an admission Glasgow Coma Scale score of 9-13. We queried the National Trauma Data Bank for our institutional data and identified 177 patients with moderate traumatic brain injury from 2010 to 2017. These patients were then linked to the electronic health record to obtain baseline and injury characteristics, laboratory data, serial Glasgow Coma Scale scores, CT findings, and neurocritical care interventions. Clinical deterioration was defined as greater than or equal to 2 recorded values of Glasgow Coma Scale scores less than or equal to 8 during the first 48 hours of hospitalization. Thirty-seven patients experienced deterioration. Children who deteriorated were more likely to require intubation (73% vs 26%), have generalized edema, subdural hematoma, or contusion on CT scan (30% vs 8%, 57% vs 37%, 35% vs 16%, respectively), receive hypertonic saline (38% vs 7%), undergo intracranial pressure monitoring (24% vs 0%), were more likely to be transferred to inpatient rehabilitation following hospital discharge (32% vs 5%), and incur greater costs of care ($25,568 vs $10,724) (all p < 0.01). There was no mortality in this cohort. Multivariable regression demonstrated that a higher Injury Severity Score, a higher initial international normalized ratio, and a lower admission Glasgow Coma Scale score were associated with deterioration to severe traumatic brain injury in the first 48 hours (p < 0.05 for all). A substantial subset of children (21%) presenting with moderate traumatic brain injury at a Level 1 pediatric trauma center experienced deterioration in the first 48 hours, requiring additional resource utilization associated with increased cost of care. Deterioration was independently associated with an increased international normalized ratio higher Injury Severity Score, and a lower admission Glasgow Coma Scale score.

Use of angioembolization in pediatric polytrauma patients: WITH BLUNT SPLENIC INJURYAngioembolization in Pediatric Blunt Splenic Injury

Background/PurposeWe sought to analyze the use of angioembolization (AE) after pediatric splenic injuries at adult and pediatric trauma centers (ATCs/PTCs). MethodsThe National Trauma Data Bank (2010–2015) was queried for patients (<18 years) who experienced blunt splenic trauma. Multivariate logistic regression was used to determine the association of AE with splenectomy. Propensity score matching was used to explore the relationship between trauma center designation and AE utilization. Results14,027 encounters met inclusion criteria. 514 (3.7%) patients underwent AE. When compared to PTCs, patients were older, had a higher ISS, and more often presented in shock at ATCs (p<0.001 for all). Regression models demonstrated no difference in mortality between cohorts. Odds of splenectomy were lower for patients undergoing AE (OR 0.16 [CI: 0.08–0.31]), however this effect was mostly driven by utilization at ATCs. Using a 1:1 propensity score matching model, patients treated at ATCs were 4 times more likely to undergo AE and 7 times more likely to require a splenectomy compared to PTCs (p<0.001). Over 6 years, PTCs performed only 27 splenectomies and 23 AEs (1.1% and 0.9%, respectively). ConclusionsAE was associated with improved splenic salvage at ATCs in select patients but appeared overutilized when compared to outcomes at PTCs. PTCs accomplished a higher splenic salvage rate with a lower AE utilization. Level of evidenceIII – Retrospective cohort study.

A Leg to Stand on: Trauma Center Designation and Association with Rate of Limb Salvage in Patients Suffering Severe Lower Extremity Injury

Mangled extremities are one of the most difficult injuries for trauma surgeons to manage. We compare limb salvage rates for a limb-threatening lower extremity injuries managed at Level I vs Level II trauma centers (TCs). We identified all adult patients with a limb-threatening injury who underwent primary amputation or limb salvage (LS) using the American College of Surgeons (ACS) Trauma Quality Improvement Program database at ACS Level I vs II TCs between 2007 and 2017. A limb-threatening injury was defined as an open tibial fracture with concurrent arterial injury (Gustilo type IIIc). Multivariable analysis and propensity score matching were performed to minimize confounding by indication. There were 712 records for analysis; 391 (54.9%) LS performed and 321 (45.1%) underwent amputation. The rate of LS was statistically higher among patients treated at Level I TCs vs those treated at Level II TCs (47.4% vs 34.8%; p= 0.01). Patients with penetrating injuries (13% vs 9.5%; p= 0.046) and tibial/peroneal artery injury (72.9% vs 50.4%; p < 0.001), as opposed to popliteal artery injury (30.8% vs 58.8%; p < 0.001), were more likely to have LS. The risk-adjusted odds of LS was 3.13 times higher at Level I TCs vs Level II TCs (95% CI, 1.59 to 6.34; p= 0.001). Limb salvage rates were significantly higher at Level I TCs compared with Level II TCs (53.0% vs 34.8%; p= 0.004), even after propensity matching. In patients with a mangled extremity, limb salvage rates are 50% higher at Level I TCs compared with Level II TCs, independent of case mix and injury severity.

Trauma Center Outcomes After Transition From Level 2 to Level 1: A National Trauma Data Bank Analysis

BackgroundPrevious US-based studies have shown that a trauma center designation of level 1 is associated with improved patient outcomes. However, most studies are cross-sectional, focus on volume-related issues and are direct comparisons between levels. This study investigates the change in patient characteristics when individual trauma centers transition from level 2 to level 1 and whether the patients have similar outcomes during the initial period of the transition. Study DesignWe performed a retrospective cohort study that analyzed hospital and patient records included in the National Trauma Data Bank from 2007 to 2016. Patient characteristics were compared before and after their hospitals transitioned their trauma level. Mortality; complications including acute kidney injury, acute respiratory distress syndrome, cardiac arrest with CPR, deep surgical site infection, deep vein thrombosis, extremity compartment syndrome, surgical site infection, osteomyelitis, pulmonary embolism, and so on; ICU admission; ventilation use; unplanned returns to the OR; unplanned ICU transfers; unplanned intubations; and lengths of stay were obtained following propensity score matching, comparing posttransition years with the last pretransition year. ResultsSixteen trauma centers transitioned from level 2 to level 1 between 2007 and 2016. One was excluded due to missing data. After transition, patient characteristics showed differences in the distribution of race, comorbidities, insurance status, injury severity scores, injury mechanisms, and injury type. After propensity score matching, patients treated in a trauma center after transition from level 2 to 1 required significantly fewer ICU admissions and had lower complication rates. However, significantly more unplanned intubations, unplanned returns to the OR, unplanned ICU transfers, ventilation use, surgical site infections, pneumonia, and urinary tract infections and higher mortality were reported after the transition. ConclusionsTrauma centers that transitioned from level 2 to level 1 had lower overall complications, with fewer patients requiring ICU admission. However, higher mortality and more surgical site infections, pneumonia, urinary tract infections, unplanned intubations, and unplanned ICU transfers were reported after the transition. These findings may have significant implications in the planning of trauma systems for administrators and healthcare leaders.

Impact of the SARS-COV-2 outbreak on epidemiology and management of major traumain France: a registry-based study (the COVITRAUMA study)

BackgroundEmerging evidence suggests that the reallocation of health care resources during the COVID-19 pandemic negatively impacts health care system. This study describes the epidemiology and the outcome of major trauma patients admitted to centers in France during the first wave of the COVID-19 outbreak.MethodsThis retrospective observational study included all consecutive trauma patients aged 15 years and older admitted into 15 centers contributing to the TraumaBase® registry during the first wave of the SARS-CoV-2 pandemic in France. This COVID-19 trauma cohort was compared to historical cohorts (2017–2019).ResultsOver a 4 years-study period, 5762 patients were admitted between the first week of February and mid-June. This cohort was split between patients admitted during the first 2020 pandemic wave in France (pandemic period, 1314 patients) and those admitted during the corresponding period in the three previous years (2017–2019, 4448 patients). Trauma patient demographics changed substantially during the pandemic especially during the lockdown period, with an observed reduction in both the absolute numbers and proportion exposed to road traffic accidents and subsequently admitted to traumacenters (348 annually 2017–2019 [55.4% of trauma admissions] vs 143 [36.8%] in 2020 p < 0.005). The in-hospital observed mortality and predicted mortality during the pandemic period were not different compared to the non-pandemic years.ConclusionsDuring this first wave of COVID-19 in France, and more specifically during lockdown there was a significant reduction of patients admitted to designated trauma centers. Despite the reallocation and reorganization of medical resources this reduction prevented the saturation of the trauma rescue chain and has allowed maintaining a high quality of care for trauma patients.

CT Imaging of The Head In Pediatric Mild Traumatic Brain Injury: Association With Pediatric Hospital Classification And Trauma Center Designation In Maryland

CT Imaging of The Head In Pediatric Mild Traumatic Brain Injury: Association With Pediatric Hospital Classification And Trauma Center Designation In Maryland

Abstract P124: Stroke Patient Transfer Destination is Influenced by Hospital Affiliation

Background: Acute ischemic stroke (AIS) patients are frequently transferred between hospitals, however it is not clear whether these transfers are optimized with respect to proximity and quality of the destination hospital. Our primary object was to identify hospital characteristics associated with sending and receiving AIS patients. Methods: Using a comprehensive statewide dataset, we identified all AIS patient transfers occurring between all 78 Massachusetts (MA) hospitals from 2007 and 2015. Hospital variables included hospital quality reputation (US News &amp; World Report), hospital capabilities (stroke center status, annual stroke volume, and trauma center designation), and institutional affiliations (same vs. not). We also included network variables to control for the structure of hospital-to-hospital transfers. We used relational event modeling to account for complex temporal and relational dependencies associated with patient transfers. This method decomposes events into a decision to transfer, and if so, the receiving hospital destination, and models them using a discrete-choice framework. Results: Among 73,114 AIS admissions in MA during the 8-year study period, there were 7,189 (9.8%) transfers. After accounting for travel time between hospitals and structural network characteristics, factors associated with increased likelihood of being a receiving hospital included teaching hospital status, hospitals of the same or higher quality, the same or higher stroke center status, and the same hospital affiliation (Table). Conclusion: Patients experiencing AIS in MA are frequently transferred between hospitals. After accounting for multiple relevant hospital characteristics, hospital affiliation remains an important factor in determining transfer destination. While there may be some benefits to hospital affiliation, stroke systems of care should be designed to maximize patient benefit and leverage interfacility transfer accordingly.

Comparison and interpretability of machine learning models to predict severity of chest injury.

ObjectiveTrauma quality improvement programs and registries improve care and outcomes for injured patients. Designated trauma centers calculate injury scores using dedicated trauma registrars; however, many injuries arrive at nontrauma centers, leaving a substantial amount of data uncaptured. We propose automated methods to identify severe chest injury using machine learning (ML) and natural language processing (NLP) methods from the electronic health record (EHR) for quality reporting.Materials and MethodsA level I trauma center was queried for patients presenting after injury between 2014 and 2018. Prediction modeling was performed to classify severe chest injury using a reference dataset labeled by certified registrars. Clinical documents from trauma encounters were processed into concept unique identifiers for inputs to ML models: logistic regression with elastic net (EN) regularization, extreme gradient boosted (XGB) machines, and convolutional neural networks (CNN). The optimal model was identified by examining predictive and face validity metrics using global explanations.ResultsOf 8952 encounters, 542 (6.1%) had a severe chest injury. CNN and EN had the highest discrimination, with an area under the receiver operating characteristic curve of 0.93 and calibration slopes between 0.88 and 0.97. CNN had better performance across risk thresholds with fewer discordant cases. Examination of global explanations demonstrated the CNN model had better face validity, with top features including “contusion of lung” and “hemopneumothorax.”DiscussionThe CNN model featured optimal discrimination, calibration, and clinically relevant features selected.ConclusionNLP and ML methods to populate trauma registries for quality analyses are feasible.