Detecting Delayed Discharge in Acute Geriatric Unit Using Natural Language Processing

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT04965480

Acronym

COLATERAL

Enrollment

102

Registered

2021-07-16

Start date

2021-08-01

Completion date

2022-04-07

Last updated

2026-06-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Electronic Health Record, Geriatric, Language, Older

Keywords

Natural Language Process, appropriate stay, acute geriatric unit, older, Electronic Health Record.

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.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

75 Years to No maximum

Healthy volunteers

Inclusion criteria

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

Exclusion criteria

* refusal to participate

Design outcomes

Primary

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

Countries

France

Outcome results