ESTRO 2025 - Abstract Book

S2398

Interdisciplinary – Other

ESTRO 2025

3561

Digital Poster Analysis of the patient record workflow in a high-volume academic radiotherapy department Julien Defrance 1 , Jérémie Boulanger 2 , Thomas Lacornerie 3 , Xavier Mirabel 3 , David Pasquier 3,2 1 ILIS - UFR3S, University of Lille, Lille, France. 2 University of Lille, CNRS, Centrale Lille, UMR 9189, CRIStAL, Lille, France. 3 Academic Department of Radiation Oncology, Centre O. Lambret, Lille, France Purpose/Objective This study aims to describe and quantify the patient files workflow from simulation to treatment completion or drop-out at the Oscar Lambret Center, Lille, France. By analyzing three years of data from RtFlow® and Mosaiq®, it maps the time allocated to each step of radiotherapy treatment preparation. Additionally, it seeks to identify the causes of treatment drop-outs and develop predictive models for these events. To the best of our knowledge, no similar work has been found in literature. Material/Methods Data from patient files (RtFlow® by Surgiqual & Mosaiq® by Elekta) were combined and analyzed, covering the period from January 2021 to December 2023. The workflow was modeled using Markov chains to capture transitions between preparation steps. Statistical comparisons were made to assess treatment drop-outs, interruptions, and time spent at each step. The analysis was conducted across all patients and stratified by treated location and treatment type. Predictive models, including neural networks, random forests, and logistic regression, were developed to anticipate treatment drop-outs and interruptions. Results The analysis included 8,564 patients, leading to a total of 10,593 treatments over the study period. We were able to model the patient record pathway (Fig.1).

Significant variations in time spent at different steps of radiotherapy preparation were observed. Notable differences based on the type of cancer were found. Patients with metastatic cancers had shorter preparation times due to the urgent need for palliative care. Conversely, patients with prostate cancer treated with curative intent experienced longer preparation times, reflecting the non-urgent nature of these indications. The longest steps in the process were the volume contouring and dosimetric validation steps, in particular in patients requiring complex treatment plans, highlighting key areas where workflow improvements could significantly reduce overall preparation time. Further analysis revealed differences in drop-out risk across cancer types (Fig.2). For example,