NCT04965480

Brief Summary

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.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
300

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jul 2021

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

July 1, 2021

Completed
7 days until next milestone

First Submitted

Initial submission to the registry

July 8, 2021

Completed
8 days until next milestone

First Posted

Study publicly available on registry

July 16, 2021

Completed
2.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

September 1, 2023

Completed
10 months until next milestone

Study Completion

Last participant's last visit for all outcomes

July 1, 2024

Completed
Last Updated

February 10, 2023

Status Verified

February 1, 2023

Enrollment Period

2.2 years

First QC Date

July 8, 2021

Last Update Submit

February 9, 2023

Conditions

LanguageGeriatricOlderElectronic Health Record

Keywords

Natural Language Processappropriate stayacute geriatric unitolderElectronic Health Record.

Outcome Measures

Primary Outcomes (2)

  • Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission in AGU

    AGU is acute geriatric units

    15 days

  • Concordance between Appropriateness Evaluation Protocol algorithm prediction result and real admission for one day in AGU

    AGU is acute geriatric units

    one day

Eligibility Criteria

Age75 Years+
Sexall
Healthy VolunteersNo
Age GroupsOlder Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

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

You may qualify if:

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

You may not qualify if:

  • refusal to participate

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

CHU Amiens Picardie

Amiens, Picardie, 80054, France

RECRUITING

MeSH Terms

Conditions

Language

Condition Hierarchy (Ancestors)

CommunicationBehavior

Central Study Contacts

Guillaume Deschasse, MD

CONTACT

03 22 45 57 20Deschasse.Guillaume@chu-amiens.fr

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

July 8, 2021

First Posted

July 16, 2021

Study Start

July 1, 2021

Primary Completion

September 1, 2023

Study Completion

July 1, 2024

Last Updated

February 10, 2023

Record last verified: 2023-02

Data Sharing

IPD Sharing
Will not share

Locations

FR(1)