Association between Trauma Center Type and Mortality for Injured Children with Severe Traumatic Brain Injury.

BACKGROUND: There is conflicting evidence regarding the relationship between trauma center type and mortality for children with traumatic brain injuries. Identification of mortality differences following brain injury across differing trauma center types may result in actionable quality improvement initiatives to standardize care for these children. METHODS: We utilized Trauma Quality Improvement Program data from 2017-2020 to identify children with severe traumatic brain injury managed at level I and II state- or American College of Surgeon-verified trauma centers. We used a random intercept multilevel logistic regression model to assess the relationship between exposure (trauma center type either adult, pediatric or mixed) and outcome (in-hospital mortality). Several secondary analyses were performed to assess the influence of trauma center volume, age strata and traumatic brain injury heterogeneity. RESULTS: There were 10,105 patients identified across 512 trauma centers. Crude mortality was 25.2%, 36.2% and 28.9% for pediatric, adult, and mixed trauma centers respectively. After adjustment for confounders, odds of mortality were higher for children managed at adult trauma centers (OR 1.67; 95% CI: 1.30 - 2.13) compared to pediatric trauma centers. Male sex, self-pay insurance status, and interfacility transfers, motor vehicle, pedestrian/ cyclist and firearm injury mechanisms, presence of concomitant abdomen, lower extremity, or chest injuries, midline shift >5 mm within 24 hours, presence of age-adjusted hypotension and either pupil asymmetry or non-reactivity were all associated with a greater odds of death. Adjustment for trauma volume and subgroup analysis using a homogenous traumatic brain injury subgroup did not change the demonstrated associations. CONCLUSIONS: Our results suggest mortality was higher at adult trauma centers compared to mixed and pediatric trauma centers for children with traumatic brain injuries. Importantly, there exists the potential for unmeasured confounding. We aim for these findings to direct continuing quality improvement initiatives to improve outcomes for brain injured children. LEVEL OF EVIDENCE: III; Type of study: Prognostic/ epidemiological.

The Trauma Quality Improvement Program: pilot study and initial demonstration of feasibility.

OBJECTIVE: The American College of Surgeons Committee on Trauma has created a "Trauma Quality Improvement Program" (TQIP) that uses the existing infrastructure of Committee on Trauma programs. As the first step toward full implementation of TQIP, a pilot study was conducted in 23 American College of Surgeons verified or state designated Level I and II trauma centers. This study details the feasibility and acceptance of TQIP among the participating centers. METHODS: Data from the National Trauma Data Bank for patients admitted to pilot study hospitals during 2007 were used (15,801 patients). A multivariable logistic regression model was developed to estimate risk-adjusted mortality in aggregate and on three prespecified subgroups (1: blunt multisystem, 2: penetrating truncal, and 3: blunt single-system injury). Benchmark reports were developed with each center's risk adjusted mortality (expressed as an observed-to-expected [O/E] mortality ratio and 90% confidence interval [CI]) and crude complication rates available for comparison. Reports were deidentified with only the recipient having access to their performance relative to their peers. Feedback from individual centers regarding the utility of the reports was collected by survey. RESULTS: Overall crude mortality was 7.7% and in cohorts 1 to 3 was 16.4%, 12.4%, and 5.1%, respectively. In the aggregate risk-adjusted analysis, three trauma centers were low outliers (O/E and 90% CI <1) and two centers were high outliers (O/E and 90% CI >1) with the remaining 18 centers demonstrating average mortality. Challenges identified were in benchmarking mortality after penetrating injury due to small sample size and in the limited capture of complications. Ninety-two percent of survey respondents found the report clear and understandable, and 90% thought that the report was useful. Sixty-three percent of respondents will be taking action based on the report. CONCLUSIONS: Using the National Trauma Data Bank infrastructure to provide risk-adjusted benchmarking of trauma center mortality is feasible and perceived as useful. There are differences in O/E ratios across similarly verified or designated centers. Substantial work is required to allow for morbidity benchmarking.

The impact of short prehospital times on trauma center performance benchmarking: An ecologic study.

BACKGROUND: Emergency medical service (EMS) prehospital times vary between regions, yet the impact of local prehospital times on trauma center (TC) performance is unknown. To inform external benchmarking efforts, we explored the impact of EMS prehospital times on the risk-adjusted rate of emergency department (ED) death and overall hospital mortality at urban TCs across the United States. METHODS: We used a novel ecologic study design, linking EMS data from the National EMS Information System to TCs participating in the American College of Surgeons' Trauma Quality Improvement Program (TQIP) by destination zip code. This approach provided EMS times for populations of injured patients transported to TQIP centers. We defined the exposure of interest as the 90th percentile total prehospital time (PHT) for each TC. TCs were then stratified by PHT quartile. Analyses were limited to adult patients with severe blunt or penetrating trauma, transported directly by land to urban TQIP centers. Random-intercept multilevel modeling was used to evaluate the risk-adjusted relationship between PHT quartile and the outcomes of ED death and overall hospital mortality. RESULTS: During the study period, 119,740 patients met inclusion criteria at 113 TCs. ED death occurred in 1% of patients, and overall mortality was 7.2%. Across all centers, the median PHT was 61 minutes (interquartile range, 53-71 minutes). After risk adjustment, TCs in regions with the shortest quartile of PHTs (<53 minutes) had significantly greater odds of ED death compared with those with the longest PHTs (odds ratio, 2.00; 95% confidence interval, 1.43-2.78). However, there was no association between PHT and overall TC mortality. CONCLUSION: At urban TCs, local EMS prehospital times are a significant predictor of ED death. However, no relationship exists between prehospital time and overall TC risk-adjusted mortality. Therefore, there is no evidence for the inclusion of EMS prehospital time in external benchmarking analyses.