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The firearm mortality rate in West Virginia (WV) increased over the past four years and is currently 50% higher than the national rate. These alarming statistics, combined with the urban-to-rural shift in firearm injuries, prompted this 10-year epidemiologic overview. To the best of the authors' knowledge, the current study stands alone as the only report of its kind on firearm injuries in the rural setting of southern WV. Firearm injuries were common in White males within the age range of 20–49 years. Assault, which is typically identified as an urban problem, was found to be the most common injury in the study population. In our data series, injury severity score was the strongest predictor of mortality, followed by self-inflicted cause of injury and trauma to the neck/head region. [ABSTRACT FROM AUTHOR]

Introduction: A Level I trauma center routinely faced challenges with meeting data submission deadlines and frequently struggled with a backlog of cases that limited opportunities for concurrent performance improvement. To provide a validated algorithm through which registry workload could be evaluated, the study institution designed a scientific model that predicted the amount of time required for chart abstraction on a patient-by-patient basis. Methods: As part of this quality improvement endeavor, registrars documented the amount of time required to complete each chart. A total of 600 patients' data were included by randomly selecting 150 patients from each of the 4 trauma registrars. Given that no previous study has examined the association of patient-related factors with chart abstraction time, study variables utilized to construct this predictive model were determined by the trauma program manager and the lead trauma registrar. Results: Multiple linear regression demonstrated that inhospital mortality; transfer from a referring facility; hospital stay; ventilator days; and number of complications, specialty consults, injuries, blood products, and procedures were significant predictors of chart abstraction time. The equation for the regression line for the multivariate regression was as follows: Y = 38.95 + 31.28 x mortality + 15.33 x referring facility + 4.68 x complications+3.55 x hospital stay + 3.33 x consults + 2.83 x diagnoses + 2.00 x ventilator days + 1.78 x blood products + 1.09 x procedures. Conclusions: The merit of this prediction model is that it is based on patient-related variables and predicts time on a patient-by-patient basis. This innovative tool can be utilized by other trauma centers to evaluate registry productivity and identify opportunities for improvement retrospectively. [ABSTRACT FROM AUTHOR]

The article discusses a retrospective 2017-2018 study on the impact of trauma nurse practitioners (TNP) on the rate of nonsurgical admissions in a trauma center. Results showed the 1.17 shorter days in average hospital length of stay in the TNP group which translated to savings of about 876,330 dollars in hospital charges. Also noted is the TNP model' success in significantly reducing the rate of nonsurgical services (NSS).

B Learning Objectives: b Burnout Syndrome (BOS) is a commonly recognized barrier in maintaining a healthy work environment. This study endeavored to evaluate the incidence, perception, and availability of resources for trauma practitioners in the state of West Virginia (WV). B Conclusions: b Approximately one-third of the surveyed WV trauma practitioners reported experiencing BOS. [Extracted from the article]