The DEPARTS Score: A Novel Tool for Predicting Discharge Disposition in Geriatric Trauma Patients.
geriatrics
long-term acute care hospital
scoring tool
skilled nursing facility
trauma
Journal
The American surgeon
ISSN: 1555-9823
Titre abrégé: Am Surg
Pays: United States
ID NLM: 0370522
Informations de publication
Date de publication:
Mar 2023
Mar 2023
Historique:
pubmed:
10
7
2021
medline:
14
2
2023
entrez:
9
7
2021
Statut:
ppublish
Résumé
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. 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 ( 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. 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.
Sections du résumé
BACKGROUND
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
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 (
RESULTS
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
CONCLUSIONS
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.
Identifiants
pubmed: 34240654
doi: 10.1177/00031348211029843
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM