1. Utilizing data from this retrospective analysis, participants will be able to apply this scoring system in their own practice to aid in predicting risk of death or discharge to hospice in trauma patients. 2. Participants will be able to utilize this study's approach to allow for earlier palliative care involvement for improved patient outcomes. Our palliative scoring system was developed to assist in earlier palliative interventions. Based on retrospective analysis of trauma data at the largest trauma network in Pennsylvania, the creation of a standardized scoring system allows us to identify patients who are at risk of death or discharge to hospice. The incidence of geriatric trauma continues to rise across the United States. Current TQIP guidelines recommends goals of care discussions with geriatric trauma patients within 72 hours of admission. Studies show palliative care involvement within 6 days of hospital admission has reduced patient readmission rates and inpatient mortality. Our goal was to create a scoring system predicting risk of death or discharge to hospice in geriatric trauma patients. We aimed to demonstrate improved outcomes with earlier palliative intervention. Our institutional trauma database was queried for patients >64 years of age admitted to the trauma service between 2018 and 2023. Univariate analysis identified admission characteristics including demographics, physiologic parameters, identifying seniors at risk score (ISAR) and injury characteristics and their association with discharge to hospice or death. Multivariate analysis identified risk adjusted predictors of the composite outcome, with the resultant regression model used to develop a scoring system. C-statistic was used as a measure of the model's predictive capability. During the study period, 9,552 patients were evaluated with n=476 (4.7%) dying or discharging to hospice and n=9,076 (95.3%) surviving. After univariate analysis of the overall cohort, 3,938 patients had complete data for all significant predictors (n=245 death/hospice and n=3,693 alive at discharge). Multivariate analysis was used to determine risk adjusted predictors of death or hospice discharge. Internal validation using bootstrapping with 500 sample-replicated models revealed a bias-corrected c-statistic of 0.857, indicating very little optimism-based attenuation from the original model and further supporting our model findings. A scoring system consisting of demographics, exam elements and injury characteristics can reliably predict risk of death or discharge to hospice at our trauma center with a high degree of discrimination. Given this data, it can open the door to further extrapolate this scoring system to include underrepresented populations as well. Surgical Palliative Care / Models of Palliative Care Delivery [ABSTRACT FROM AUTHOR]