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Predictive Tracking of Patient Flow in the Emergency Services During the Virus Winter Epidemics

Completed
Conditions
Bronchiolitis
Disease Outbreaks
Child
Elderly
Acute Renal Failure
Interventions
Other: data retrieval
Registration Number
NCT02858531
Lead Sponsor
Centre Hospitalier Universitaire de Saint Etienne
Brief Summary

Epidemics and infectious diseases in general, punctuate much of the activity of an emergency service. The impact of winter infections is particularly important to vulnerable populations such as infant during bronchiolitis epidemics and the elderly during seasonal influenza. Each year, these epidemic phenomena lead to disorganization of emergency services and healthcare teams by lack of anticipation and organizational measures in particular to manage the approval of emergency services for the most vulnerable populations requiring hospitalization.

For 2 years, the pediatric emergency department of St Etienne University Hospital has a decision support tool for the periods of winter epidemics. Through a retrospective analysis of Passages of Emergency summary, this tool provides an estimate of infants with bronchiolitis flow day to day, and the availability in real time of an abnormally high flow of patients to pediatric emergencies. These data can help to affirm that the epidemic begins in this hospital.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
760000
Inclusion Criteria
  • child < 24 months with bronchiolitis
  • elderly < 60 years with acute renal failure or breathing problem
Exclusion Criteria
  • refuse of transmission of their data

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
patients < 24 months or 60 years with bronchiolitis or ARFdata retrievalARF = Acute Renal Failure
Primary Outcome Measures
NameTimeMethod
build a predictive toolat inclusion

a tool with different levels of alerts of the influx of people aged to emergencies during winter epidemics.

Variables in the model : activity database in emergency services, computer data, virology database and average length of stay.

Secondary Outcome Measures
NameTimeMethod
Comparison virological databases with clinical diagnosis of patientsat inclusion
Difference between the estimated date and the effective date of the activity peak on the average length of stay of patients in the hospital of Saint Etienneat inclusion
Difference between the estimated date and the effective date of the activity peak on the average length of stay of patients in the other hospitalsat inclusion
Percentage of elderly staying more than 10 hours in the emergency services.at inclusion

Trial Locations

Locations (11)

CH de Valence (adult emergency service)

πŸ‡«πŸ‡·

Valence, France

CHU de Lyon HFME (pediatric service)

πŸ‡«πŸ‡·

Lyon, France

CHU de Lyon (laboratory of virology)

πŸ‡«πŸ‡·

Lyon, France

CHU de Grenoble (pediatric service)

πŸ‡«πŸ‡·

Grenoble, France

CHU de Saint Etienne (adult emergency service)

πŸ‡«πŸ‡·

Saint Etienne, France

CHU de Saint Etienne (Pediatric service)

πŸ‡«πŸ‡·

Saint Etienne, France

CH de Valence (pediatric service)

πŸ‡«πŸ‡·

Valence, France

CH de Villefranche (adult emergency service)

πŸ‡«πŸ‡·

Villefranche Sur Saone, France

CH de Villefranche (pediatric service)

πŸ‡«πŸ‡·

Villefranche Sur Saone, France

CHU de Grenoble (adult emergency service)

πŸ‡«πŸ‡·

Grenoble, France

CHU de Lyon (adult emergency service)

πŸ‡«πŸ‡·

Lyon, France

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