Impact of the automation of inpatient bed management to reduce the emergency service waiting time

Faiza Ajmi (1) , Faten Ajmi (1) , Sarah Ben Othman (1) , Hayfa Zgaya (1) , Gregoire Smith (2) , Jean-Marie Renard (2) , Slim Hammadi (1)

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
2 CHU Lille - Direction de la recherche et de l’innovation

The patient waiting time to be transferred for hospitalization is the time that the patient waits between the decision to hospitalize and the actual admission to an inpatient hospital bed. One of the difficulties encountered in qualifying waiting time for inpatient bed is the inability of hospital information systems to measure it. Hospitals in France have a specialized bed allocation team. This team must manage the bed allocation problem between different hospital departments using phone communication to assign patients to the adapted service. This kind of communication represents a lengthy additional workload in which effectiveness is uncertain. This paper presents a new approach to automate bed management in downstream service. For that, we have implemented algorithms based on artificial intelligent integrated in an inpatient web platform using IoT-Beacons, which is implemented to improve and facilitate the exchange of availability information of downstream beds within the Lille university hospital center (LUHC).

Mots clés: Inpatient bed management; patient pathway optimization; artificial intelligent for healthcare; hospital management

Domaines: Modélisation et simulation

Faiza Ajmi, Faten Ajmi, Sarah Ben Othman, Hayfa Zgaya, Gregoire Smith, et al.. Impact of the automation of inpatient bed management to reduce the emergency service waiting time. MedInfo, Oct 2021, Virtual, France. ⟨hal-03462812⟩