Curriculum
Computer Science for Societal Challenges and Innovation, XXXIX series
Grant sponsor
PRIN2022
Supervisor

Massimiliano De Leoni
Co-supervisor
s
TBD
Contact
munazzah.siddique@studenti.unipd.it

Project description
Emergency Departments (EDs) play a pivotal role in healthcare. An integrated data-driven simulation model employing process mining and business process modeling aims to enhance the understanding of patient flow, identify inefficiencies, and to optimize operational processes within the ED. Hospital staff could be hesitant to trust recommendations from models that are not understandable. So, the optimized resource configuration be compared with the original setup simulating different unforeseen scenarios, such as changes in patient flow and poor quality data. However, the quality of the data can significantly impact the quality of the model, is one of the main challenges to deal. The timestamps problem that need to be repaired since they are imprecise or does not have a sufficient level of granularity or in some cases could also be missing. Address the challenge to evaluate the accuracy of process models, ensuring they can produce observed process executions while maintaining precision complying the healthcare protocols and regulations. Additionally to classic conformance checking measures, will be evaluated the suitability of our model using the metrics, which considers several perspectives. We posed particular attention in reducing waiting times, finding an optimal number of resources and a better allocation of them.