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.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
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