ORAHS2025
Abstract Submission

94. When Every Minute Counts: Predictive Modeling and Simulation in Organ Donation Management

Invited abstract in session HD-4: Poster session 2, stream Sessions.

Thursday, 13:30-14:00
Room: St Olavs, Kunnskapssenteret KA12

Authors (first author is the speaker)

1. Arianna Freda
Università degli Studi Roma Tre
2. Maurizio Naldi
GEPLI, LUMSA University
3. Gaia Nicosia
Università Roma Tre
4. Andrea Pacifici
Dip. di Ingegneria Civile e Ingegneria Informatica, Università di Roma Tor Vergata
5. Gianfranco Teti
Lazio Regional Transplant Center, San Camillo-Forlanini Hospital
6. Mariano Feccia
Lazio Regional Transplant Center, San Camillo-Forlanini Hospital

Abstract

Organ transplantation is a life-saving procedure that replaces a damaged organ in a patient. Its success depends not only on medical expertise, but also on how efficiently and quickly the organ donation process is managed, as delays can lead to organ degradation and reduced transplant success rates.
Using real-world data from the Regional Transplant Center of Lazio (Italy), we model the organ donation process, quantifying the duration and cost of each activity.
We propose a simulation-based framework to explore and optimize the entire process, focusing on the trade-off between time efficiency and cost-effectiveness.
Specifically, Monte Carlo simulations are performed to evaluate alternative management policies that govern activity scheduling, particularly in relation to consent acquisition—one of the most critical and uncertain steps in the process.
To further support decision-making under uncertainty, we introduce a predictive model that estimates the probability of obtaining family consent. By incorporating consent prediction into the simulation process, we enable more informed assessments of each policy’s effectiveness under varying conditions. Overall, our results provide a decision support system that helps decision-makers at the Transplant Center select the most appropriate strategy for each case, while minimizing delays and avoiding unnecessary costs.

Keywords

Status: accepted

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