Optimization of Medical Time in the Emergency Department: Impact of an AI-Based System on Prescription Entry
Overview
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Enrollment
- 770
- Locations
- 1
- Primary Endpoint
- Medical time required for the transcription of prescriptions
Overview
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.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Other
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
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
Outcomes
Primary Outcomes
Medical time required for the transcription of prescriptions
Time Frame: Day 1
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
Secondary Outcomes
- Number of drug-related problems (DRPs) identified per patient(day 1)
- Identification of DRPs by subtype and severity(day 1)
- Rate of reconciled medication histories and structured documentation(day 1)
- Proportion and type of transcription errors (medication name or dosage)(day 1)
- Readmission rates(at 3 months)
- Mapping of DRPs by subtype and severity(day 1)
- Time delays between triage, anamnesis, and diagnosis(day 1)
- Length of emergency department stay and downstream hospitalizations(day 1)
- Overall survival(at 6 months)