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Not yet recruiting NCT07312019

Optimization of Medical Time in the Emergency Department: Impact of an AI-Based System on Prescription Entry

No phase Interventional Drug-related Iatrogenesis Emergency Department Artificial Intelligence Clinical Decision Support

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: current hospital-standard databases, Posos.
Who it may be relevant to
Registry conditions: Drug-related Iatrogenesis, Emergency Department, Artificial Intelligence, Clinical Decision Support. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
France
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Overview

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.

Interventions

  • Other current hospital-standard databases
    Prescription management using current hospital-standard databases and tools
  • Device Posos
    Prescription management supported by POSOS device (OCR+AI) for structured data entry and clinical decision support

Primary outcome measures

  • Medical time required for the transcription of prescriptions [Time frame: Day 1]
Secondary outcome measures (9)
  • Number of drug-related problems (DRPs) identified per patient [Time frame: day 1]
  • Proportion and type of transcription errors (medication name or dosage) [Time frame: day 1]
  • Identification of DRPs by subtype and severity [Time frame: day 1]
  • Rate of reconciled medication histories and structured documentation [Time frame: day 1]
  • Time delays between triage, anamnesis, and diagnosis [Time frame: day 1]
  • Length of emergency department stay and downstream hospitalizations [Time frame: day 1]
  • Readmission rates [Time frame: at 3 months]
  • Overall survival [Time frame: at 6 months]
  • Mapping of DRPs by subtype and severity [Time frame: day 1]

Eligibility criteria

Inclusion criteria

  • 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

Exclusion criteria

  • Patient under legal protection/judicial measures (guardianship/custody)
  • Lack of signed informed consent

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Other

Study locations

France · 1 center
  • CHU Amiens — Amiens

Identifiers

NCT: NCT07312019 · PI2024_843_0120

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗