Modelling and simulating the organ donation process using bootstrap and event-driven process chain representation

Transplants improve the quality of life and extend lifespan by replacing damaged organs. The duration of the donor management process must be evaluated and shortened to prevent organ degradation. In this paper, we propose an event-process-chain (EPC) model for the donor management process and conduct a Monte Carlo event-driven simulation to assess its overall duration. We give a rigorous description of the current procedure, to be used as a baseline to re-organize the process. Monte Carlo simulation parameters are based on a measurement campaign where the durations of all the activities in the donor management process have been observed. Due to the low number of donors, we employ a bootstrap approach to generate activity times. We evaluate the overall process completion time and identify the most critical activities. The standard deviation of the completion time is just 11.5% of the mean value. Instrumental tests (encompassing diagnostic and analytical procedures) turn out to be the activities to focus on to shorten the completion time significantly. In order to achieve lower organ degradation, policy guidelines should then address the time of execution (e.g. as to consent acquisition) and the duration of those tests.

Authors

Institutions

Publication Details

Journal
Journal of Simulation
Published
2025-04-04
DOI
https://doi.org/10.1080/17477778.2025.2486709
Citations
1
Primary Topic
Organ Donation and Transplantation
Type
article
Field-Weighted Citation Impact
1.88
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling and simulating the organ donation process using bootstrap and event-driven process chain representation

Gaia Nicosia, Maurizio Naldi, Mariano Feccia, Andrea Pacifici et al.
1 citations
Journal of Simulation
Organ Donation and Transplantation
1.88
article

Modelling and simulating the organ donation process using bootstrap and event-driven process chain representation

Gaia Nicosia, Maurizio Naldi, Mariano Feccia, Andrea Pacifici, Arianna Freda
article en
1 citations

Abstract

Transplants improve the quality of life and extend lifespan by replacing damaged organs. The duration of the donor management process must be evaluated and shortened to prevent organ degradation. In this paper, we propose an event-process-chain (EPC) model for the donor management process and conduct a Monte Carlo event-driven simulation to assess its overall duration. We give a rigorous description of the current procedure, to be used as a baseline to re-organize the process. Monte Carlo simulation parameters are based on a measurement campaign where the durations of all the activities in the donor management process have been observed. Due to the low number of donors, we employ a bootstrap approach to generate activity times. We evaluate the overall process completion time and identify the most critical activities. The standard deviation of the completion time is just 11.5% of the mean value. Instrumental tests (encompassing diagnostic and analytical procedures) turn out to be the activities to focus on to shorten the completion time significantly. In order to achieve lower organ degradation, policy guidelines should then address the time of execution (e.g. as to consent acquisition) and the duration of those tests.

Journal of SimulationVol. 20(2)
University of Rome Tor Vergata (IT), Roma Tre University (IT), Libera Università Maria SS. Assunta (IT), Nini Hospital (LB)
Openalex Percentile: Top 17%
Organ Donation and Transplantation
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.