Abstract: Techniques are described that employ a multifactorial, machine-learning based system and prioritization framework for optimizing patient placement to beds at a medical facility. In one embodiment, a computer-implemented is provided that comprises receiving, by a system operatively coupled to a processor, a patient placement request requesting placement of a patient to a hospital bed of the healthcare facility, wherein the request is associated with information identifying a medical service for the patient and a bed type. The method further comprises, selecting, by the system, a placement prioritization model from a set of placement prioritization models based on the medical service and the bed type, and employing, by the system, the prioritization model and state information regarding a current state of the healthcare facility to determine a prioritization score reflective of a priority level of the patient placement request.

Abstract: Techniques are described that employ a multifactorial, machine-learning based system and prioritization framework for optimizing patient placement to beds at a medical facility. In one embodiment, a computer-implemented is provided that comprises receiving, by a system operatively coupled to a processor, a patient placement request requesting placement of a patient to a hospital bed of the healthcare facility, wherein the request is associated with information identifying a medical service for the patient and a bed type. The method further comprises, selecting, by the system, a placement prioritization model from a set of placement prioritization models based on the medical service and the bed type, and employing, by the system, the prioritization model and state information regarding a current state of the healthcare facility to determine a prioritization score reflective of a priority level of the patient placement request.