Artificial Intelligence, Clinical Decision Support, Drug-related Iatrogenesis, Emergency Department, Medication, Prescription, Reconciliation, Transcription
Conditions
Keywords
Drug-related iatrogenesis, emergency department, artificial intelligence, clinical decision support, randomized trial, medication, reconciliation, prescription, transcription
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.
Interventions
OTHERcurrent hospital-standard databases
Prescription management using current hospital-standard databases and tools
DEVICEPosos
Prescription management supported by POSOS device (OCR+AI) for structured data entry and clinical decision support
Sponsors
Centre Hospitalier Public du Cotentin
University Hospital, Bordeaux
University Hospital, Strasbourg, France
Clinique de l'Estrée
CHU Aix-en-Provence
Centre Hospitalier Universitaire, Amiens
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Medical time required for the transcription of prescriptions | 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
| Measure | Time frame |
|---|---|
| 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 |
| Number of drug-related problems (DRPs) identified per patient | day 1 |
| Readmission rates | at 3 months |
| Overall survival | at 6 months |
| Mapping of DRPs by subtype and severity | day 1 |
| Length of emergency department stay and downstream hospitalizations | day 1 |
Countries
France
Contacts
Primary ContactAurélien Mary, Pr
Outcome results
None listed