Optimization of Medical Time in the Emergency Department: Impact of an AI-Based System on Prescription Entry
YGénHIAL
1 other identifier
interventional
770
1 country
1
Brief Summary
Drug-related iatrogenesis is a major public health issue, accounting for a significant proportion of adverse events and hospitalizations in emergency departments. Optimizing prescription management in this context is critical to improve both patient safety and physician efficiency This study aims to evaluate the impact of the POSOS AI-driven device on the medical time required for prescription management in polymedicated patients admitted to emergency departments. The main objective is to establish whether the use of POSOS can reduce transcription time compared to standard electronic management.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jan 2026
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
November 17, 2025
CompletedFirst Posted
Study publicly available on registry
December 31, 2025
CompletedStudy Start
First participant enrolled
January 1, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
January 1, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
January 1, 2027
January 8, 2026
January 1, 2026
1 year
November 17, 2025
January 6, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Medical time required for the transcription of prescriptions
Medical time required for the transcription of prescriptions for at-risk polymedicated patients at emergency admission. This is measured by the duration needed to transcribe prescriptions into the structured electronic health record by physicians, assessed by direct observation with a stopwatch
Day 1
Secondary Outcomes (9)
Number of drug-related problems (DRPs) identified per patient
day 1
Proportion and type of transcription errors (medication name or dosage)
day 1
Identification of DRPs by subtype and severity
day 1
Rate of reconciled medication histories and structured documentation
day 1
Time delays between triage, anamnesis, and diagnosis
day 1
- +4 more secondary outcomes
Study Arms (2)
Standard prescription
ACTIVE COMPARATORStandard prescription management
PoSOS
EXPERIMENTALPOSOS-assisted prescription management
Interventions
Prescription management supported by POSOS device (OCR+AI) for structured data entry and clinical decision support
Prescription management using current hospital-standard databases and tools
Eligibility Criteria
You may qualify if:
- Age ≥18 years
- Admission to emergency department at a participating center
- Polymedicated patients with prescriptions including ≥8 medication lines (including those for long-term illnesses)
- Signed informed consent
You may not qualify if:
- Patient under legal protection/judicial measures (guardianship/custody)
- Lack of signed informed consent
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University Hospital, Bordeauxcollaborator
- University Hospital, Strasbourg, Francecollaborator
- Clinique de l'Estréecollaborator
- CHU Aix-en-Provencecollaborator
- Centre Hospitalier Universitaire, Amienslead
- Centre Hospitalier Public du Cotentincollaborator
Study Sites (1)
CHU Amiens
Amiens, 80480, France
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
November 17, 2025
First Posted
December 31, 2025
Study Start
January 1, 2026
Primary Completion (Estimated)
January 1, 2027
Study Completion (Estimated)
January 1, 2027
Last Updated
January 8, 2026
Record last verified: 2026-01
Data Sharing
- IPD Sharing
- Will not share