BACKGROUND: Geriatric trauma patients (GTPs) represent a high-risk population for needing post-acute care, such as skilled nursing facilities (SNFs) and long-term acute care hospitals (LTACs), due to a combination of traumatic injuries and baseline functional health. As there is currently no well-established tool for predicting these needs, we aimed to create a scoring tool that predicts disposition to SNFs/LTACs in GTPs. METHODS: The adult 2017 Trauma Quality Improvement Program database was divided at random into two equal sized sets (derivation and validation sets) of GTPs >65 years old. First, multiple logistic regression models were created to determine risk factors for discharge to a SNF/LTAC in admitted GTPs. Second, the weighted average and relative impact of each independent predictor was used to derive a DEPARTS (Discharge of Elderly Patients After Recent Trauma to SNF/LTAC) score. We then validated the score using the area under the receiver-operating curve (AROC). RESULTS: Of 66 479 patients in the derivation set, 36 944 (55.6%) were discharged to a SNF/LTAC. Number of comorbidities, fall mechanism, spinal cord injury, long bone fracture, and major surgery were each independent predictors for discharge to SNF/LTAC, and a DEPARTS score was derived with scores ranging from 0 to 19. The AROC for this was .74. In the validation set, 66 477 patients also had a SNF/LTAC discharge rate of 55.7%, and the AROC was .74. DISCUSSION: The DEPARTS score is a good predictor of SNF/LTAC discharge for GTPs. Future prospective studies are warranted to validate its accuracy and clinical utility in preventing delays in discharge.
BACKGROUND:Geriatric traumapatients (GTPs) represent a high-risk population for needing post-acute care, such as skilled nursing facilities (SNFs) and long-term acute care hospitals (LTACs), due to a combination of traumatic injuries and baseline functional health. As there is currently no well-established tool for predicting these needs, we aimed to create a scoring tool that predicts disposition to SNFs/LTACs in GTPs. METHODS: The adult 2017 Trauma Quality Improvement Program database was divided at random into two equal sized sets (derivation and validation sets) of GTPs >65 years old. First, multiple logistic regression models were created to determine risk factors for discharge to a SNF/LTAC in admitted GTPs. Second, the weighted average and relative impact of each independent predictor was used to derive a DEPARTS (Discharge of Elderly Patients After Recent Trauma to SNF/LTAC) score. We then validated the score using the area under the receiver-operating curve (AROC). RESULTS: Of 66 479 patients in the derivation set, 36 944 (55.6%) were discharged to a SNF/LTAC. Number of comorbidities, fall mechanism, spinal cord injury, long bone fracture, and major surgery were each independent predictors for discharge to SNF/LTAC, and a DEPARTS score was derived with scores ranging from 0 to 19. The AROC for this was .74. In the validation set, 66 477 patients also had a SNF/LTAC discharge rate of 55.7%, and the AROC was .74. DISCUSSION: The DEPARTS score is a good predictor of SNF/LTAC discharge for GTPs. Future prospective studies are warranted to validate its accuracy and clinical utility in preventing delays in discharge.