Evaluating Staffing Guidelines Using Trauma Volume by Season, Day, and Time of Day at a Level 1 Trauma Center in Rural Appalachia.

Background Trauma is regarded as randomly occurring, but patterns exist for trauma volume which are useful in staffing guidelines and resource allocation. Literature on trauma admissions volume has been centered around geographically/climatically diverse centers and has often not considered many different temporal factors at once. Additionally, studies on trauma volume and staffing centered around rural or southern Trauma 1 centers were largely absent in the literature. Based on this, a study on our Trauma 1 center was deemed appropriate. Objective The objective of this study was to determine significant trends in trauma admissions and use this information to assess current staffing. This assessment was conducted through a retrospective analysis of patients admitted to the emergency department at our center. Methodology The retrospective data analysis study was conducted using data obtained locally and then subsequently uploaded onto the National Trauma Data Bank (NTDB). Patients included all trauma activations and consults to the trauma team above the age of 18. We analyzed the data by season, day, and time of admission to identify trends. Chi-square analysis was used to establish significance in comparing groups (day of the week, hour of day, and season of the year). Factors such as Injury Severity Score (ISS), Glasgow Coma Scale (GCS), and length of stay (hospital days) were used to determine patterns of trauma severity. Results A total of 15,418 patients (8,307 males, 7,111 females) were analyzed in the dataset. The mean ISS was 8.14, and the mean GCS was 14.22. Weekends had significantly greater trauma volume than weekdays (< 0.05). Motor vehicle collision (MVC), motorcycle, bicycle, and all-terrain vehicle (ATV) traumas were all significantly greater in summer. Bicycle and ATV trauma were significantly lowest in winter (< 0.05). Admissions began to rise at 7 am and peaked at 5 pm. ISS, GCS, and hospital days did not significantly differ based on all groups assessed. Variation in trauma peak time across days of the week was insignificant. Our study discovered key findings in the form of increased trauma patient volume in summer, weekends, and between the hours of 1 and 9 pm. Our project found that the current staffing presents a mismatch in terms of addressing periods of high trauma. Staffing is lower on weekends, and there are conflicting administrative tasks scheduled during peak trauma hours (1-7 pm). This could be addressed by adjusting shift schedules to align better with periods of high trauma, such as increasing the workforce on weekends and decreasing it on weekdays. During summer months, adding additional float shift staff may help to better address the peak trauma volume. Conclusions Currently, there is evidence to suggest that high trauma times correspond with times of low staffing. Based on our study, there was evidence to show that low staffing periods corresponded with high trauma times. This volume-to-staffing mismatch may contribute to underlying problems such as long wait times, overworked providers, and ED overcrowding. Future studies may choose to focus on quality differences and wait times, aiming to quantify the effect of the mismatch of resources on patient volume.