214. Predictability models for waiting time for radiotherapy treatment. (December 2018)

• Record Type: Journal Article
• Authors: Rao, M.; Strolin, S.; Ungania, S.; Bruzzaniti, V.; Sanguineti, G.; Strigari, L.
• Is Part Of: Physica medica. Volume 56(2018)Supplement 2
• Page Start: 192
• Page End: 193
• Publication Date: 2018-12
• Subjects: Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2018.04.225
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Purpose: This work deal with the waiting time that patient that receive radiotherapy treatments pass in the queue[1], in order to organize treatment processes effectively and efficiently and to ensure both the patient health and to facilities work optimization[2, 3] . Methods: Data belong to patients undergoing radiotherapy related to an observation period of 2 years were extrapolated from the record and verified system and classified into 8 macro categories. A simulation on the waiting time estimation was performed for all patients in the dataset. Our system considers: a priority assignment system coded by our institute staff; a characterization of machines and of their operation and maintenance; the historical data about patients and treatments; some different methods for calculating waiting time. Have been tested: a deterministic model, a Hidden Markov Model (HMM) to estimate the component not explained by the above parameters and a model based on a Support Vector Machine (SVM). Results: The first results demonstrate an average accuracy (forecast – real waiting time, measured on historical data) around 5–10 days. Conclusions: The implications of waiting list for radiotherapy treatment include perceived lower cancer control rates and patient suffering. The model represents a tool for effectively managing the capacity in a radiotherapy department to optimize the waiting lists for treatment.