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.
Study Type
OBSERVATIONAL
Enrollment
300
CHU Amiens Picardie
Amiens, Picardie, France
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission in AGU
AGU is acute geriatric units
Time frame: 15 days
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission for one day in AGU
AGU is acute geriatric units
Time frame: one day
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