Delayed discharge in geriatric units is a health and economic issue. There is no algorithm to automatically measure the appropriateness of admissions or hospital days. 30% of the days of hospitalization in acute geriatric units (AGU) are not appropriate. Waiting for a transfer to a follow-up care and rehabilitation unit (SSR) is the main risk factor for inappropriate days. The purpose of this project is to develop an algorithm using natural language processing to predict the appropriateness of an admission to UGA, or a day at UGA.
Age range
75 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission in AGU
Timeframe: 15 days
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission for one day in AGU
Timeframe: one day