Emergency departments (EDs) are vital components of healthcare systems. However, they are under increasing pressure due to limited resources, demographic changes, and growing demand for healthcare services. Improving the operational efficiency of EDs is crucial for managing the pressures they face. Predictive modeling, supported by advances in hospital information systems and the development of artificial […]
The Blockchain potential in enabling and boosting business process innovation in the Healthcare industry is a hot topic. However, the realization of such a potential is hampered by two hindrances. First, healthcare business processes are inherently complex. This implies additional difficulties in managing and innovating them. Second, the digitalization trend has entailed relevant changes in […]
This work reports preliminary outcomes from the project LINFA, whose aim is to develop a technological, information and organizational system to support the procurement process of medicines and medical devices within healthcare organizations. Such system integrates simulation and optimization algorithms and forecasting models along with advanced logistic practices and traceability technologies by exploiting the increasing […]
In recent years, the widespread adoption of Hospital Information Systems is enabling hospitals to measure and record an ever-growing volume and variety of patient and process-related data. In such context, analytics are emerging as suitable tools and methods for extracting and analyzing such data and for providing useful insights to assist decision-making. The Emergency Department […]
This work aims to improve the accuracy of the waiting times prediction in ED, by incorporating queue variables enabled by process mining that capture the crowding of the activities inside the ED. By undertaking process mining, it is possible to gain insights into the hospital processes extracting the entire patient-flow and the queueing-related information (e.g., […]