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

February 9, 2023 updated by: Centre Hospitalier Universitaire, Amiens
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 Overview

Status

Recruiting

Conditions

Study Type

Observational

Enrollment (Anticipated)

300

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

75 years and older (OLDER_ADULT)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients aged >75 years, hospitalized in AGU in Amiens University Hopsital

Description

Inclusion Criteria:

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

Exclusion Criteria:

  • refusal to participate

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission in AGU
Time Frame: 15 days
AGU is acute geriatric units
15 days
Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission for one day in AGU
Time Frame: one day
AGU is acute geriatric units
one day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Centre Hospitalier Universitaire, Amiens

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

July 1, 2021

Primary Completion (ANTICIPATED)

September 1, 2023

Study Completion (ANTICIPATED)

July 1, 2024

Study Registration Dates

First Submitted

July 8, 2021

First Submitted That Met QC Criteria

July 8, 2021

First Posted (ACTUAL)

July 16, 2021

Study Record Updates

Last Update Posted (ACTUAL)

February 10, 2023

Last Update Submitted That Met QC Criteria

February 9, 2023

Last Verified

February 1, 2023

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • PI2021_843_0153

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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