Paper Session
- Date:
- Time: -
- Track: Research
- Location: Grand Hall G-H
- CME/CE: 1.0
Developed by the Research Committee
Moderator: Thomas N. Robinson, MD
Learning Objectives: (1) describe a model which could accurately identify delirium in the ED using data from the electronic health record; (2) discuss the use of machine learning (ML) techniques to improve prediction of aspiration through acoustic analysis of pre- and post- swallow phonation; (3) review the effect of BC/WC-GeriOnc training versus enhanced usual care on SDM; (4) compare long-term GC use in LORA by DMARD status.
| Phenotypes of Delirium Among Elders in the Emergency Department (P24) Scott M. Dresden, MD, MS |
| Acoustic Analysis-Based Machine Learning Approaches to Screening for Aspiration Risk in Older Adults with Swallowing Dysfunction (P25) Anaïs Rameau, MD |
| Cluster Randomized Controlled Pilot Trial of the Best Case/Worst Case-Geriatric Oncology (BC/WC-GeriOnc) Communication Tool: Effects on Shared Decision Making (SDM) (P26) Melisa L. Wong, MD, MAS, AGSF |
| Association Between In-Hospital Rehabilitation and Days Alive and at Home Following Critical Illness in Older Adults (B161) Snigdha Jain, MD, MHS |