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Effect of an ML Electronic Alert Management System to Reduce the Use of ED Visits and Hospitalizations

NCT05221697 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 800

Last updated 2023-08-30

No results posted yet for this study

Summary

Development, validation and impact of an alert management system using social workers' observations and machine learning algorithms to predict 7-to-14-day alerts for the risk of Emergency Department (ED) Visit and unplanned hospitalization.

Multi-center trial implementation of electronic Home Care Aides-reported outcomes measure system among patients, frail adults \>= 65 years living at home and receiving assistance from home care aides (HCA).

Conditions

  • Emergencies

Interventions

DEVICE

PRESAGE CARE

Participants in this arm will be followed by HCA and might benefit from Nurse health interventions

Sponsors & Collaborators

  • Assistance Publique Hopitaux De Marseille

    collaborator OTHER

  • Assistance Publique - Hôpitaux de Paris

    collaborator OTHER

  • University Hospital, Lille

    collaborator OTHER

  • Presage

    lead INDUSTRY

Study Design

Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-09-01
Primary Completion
2021-12-31
Completion
2024-06-30

Countries

  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05221697 on ClinicalTrials.gov