Detecting Delayed Discharge in Acute Geriatric Unit Using Natural Language Processing (COLATERAL)

Centre Hospitalier Universitaire, Amiens

Status: Enrolling

Conditions: Geriatric; Older; Electronic Health Record; Language

Study type: Observational

Funder types: Other

Identifiers

NCT04965480

PI2021_843_0153

Details and patient eligibility

About

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.

Enrollment: 300 estimated patients

Sex: All

Ages: 75+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• age : >75 years
• patient hospitalized in an AGU

Exclusion criteria

• refusal to participate