The healthcare sector is faced with great financial pressure and consequently, many hospitals are looking for ways to balance out their budgets without compromising on quality. A better organisation of logistics services, particularly the transport of patients and equipment, can boost efficiency levels and reduce costs. In fact, the logistics costs of hospitals sometimes add up to more than 30% of their overall expenses. Moreover, nursing staff spend, on average, 10% of their time on logistics.
The Internet of Things and intelligent systems supporting decision-making allow us to automatically assign the most suitable staff member to a transport task based on all the available information (e.g. the location of staff and patients, how busy the hospital is at any given time, the staff competencies, the patient’s physical condition, the pick-up location etc.). In this demo you will see how a self-learning planner, the MASSIF platform, can use this information to autonomously discover why certain transports did not make it within the specified deadlines. This knowledge can subsequently be used to automatically optimise the transport schedule, which also gives hospital staff a better insight into the pitfalls of their work processes and overall organisation.