Mariana Lascas de Paiva Trindade is a PhD Fast Track student in Engineering and Management at Instituto Superior Técnico - University of Lisbon (IST-UL), conducting her research at CEGIST. She holds a BSc in Industrial Engineering and Management from Instituto Superior Técnico, completed in 2024, and is currently completing her MSc in Industrial Engineering and Management, with a specialisation in Operations and Logistics. As part of her master’s studies, she spent a semester at the Technical University of Denmark. Alongside her studies, Mariana is also an invited teaching assistant at the Department of Engineering and Management of IST-UL, where she has supported the courses Business Analytics, Fundamentals of Operations Research, and Decision Support Models. Her research addresses the organisational complexity of healthcare systems, an interest sparked by an undergraduate project developed in partnership with the private healthcare provider CUF on the logistics of the operating theatre supply chain. She is currently undertaking doctoral coursework while developing her master’s thesis, under the supervision of Professor Miguel Alves Pereira and Professor Mónica Duarte Oliveira, as a seed project for her doctoral research. This work uses the Portuguese trauma network as a case study to begin investigating patient referral networks, combining conceptual system analysis with the exploration of public data, the identification of relevant variables, and the assessment of modelling possibilities. Building on this work, her doctoral research, additionally supervised by Professor José Rui Figueira, focuses on the redesign and planning of patient referral networks through an integrated decision framework combining problem structuring, predictive analytics, simulation, and multicriteria decision analysis, using urgent care systems in Portugal as its main application context. Her work aims to support the design of more coordinated and analytically grounded referral policies, contributing to better-informed decisions in the organisation and planning of urgent care systems.

Keywords: Patient referral networks | Healthcare Systems | Operations Research