Radiotherapy department supported by an optimization algorithm for scheduling patient appointments.

IF 2.2 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Chavez Marcela, Gonzalez Silvia, Ruiz Alvaro, Duflot Patrick, Nicolas Jansen, Izidor Mlakar, Umut Arioz, Valentino Safran, Kolh Philippe, Van Gasteren Marteyn
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引用次数: 0

Abstract

Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Each day, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, considering the availability of human and material resources, such as healthcare professionals and linear accelerators. With the increasing number of patients suffering from different types of cancers, manually establishing schedules following each patient's treatment protocols has become an extremely difficult and time-consuming task. We propose an optimization algorithm that automatically schedules and generates patient appointments. The model can rearrange fixed appointments to accommodate urgent cases, enabling hospitals to schedule appointments more efficiently. It respects the different treatment protocols and should increase staff and patient satisfaction. The optimization algorithm can be connected to a mobile application allowing patients to accept or refuse appointment changes for rescheduling radiotherapy treatments.

放疗科室采用优化算法进行患者预约调度。
及时给予放射治疗(RT)是治疗癌症最有效的方法之一。每天,大型医院的放射治疗部门必须考虑到医疗保健专业人员和线性加速器等人力和物力资源的可用性,规划无数次放射治疗。随着患有不同类型癌症的患者数量的增加,按照每个患者的治疗方案手动建立时间表已成为一项极其困难和耗时的任务。我们提出了一种优化算法,可以自动安排和生成患者预约。该模型可以重新安排固定的预约,以适应紧急病例,使医院能够更有效地安排预约。它尊重不同的治疗方案,并应提高工作人员和患者的满意度。优化算法可以连接到移动应用程序,允许患者接受或拒绝重新安排放疗治疗的预约更改。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Health Informatics Journal
Health Informatics Journal HEALTH CARE SCIENCES & SERVICES-MEDICAL INFORMATICS
CiteScore
7.80
自引率
6.70%
发文量
80
审稿时长
6 months
期刊介绍: Health Informatics Journal is an international peer-reviewed journal. All papers submitted to Health Informatics Journal are subject to peer review by members of a carefully appointed editorial board. The journal operates a conventional single-blind reviewing policy in which the reviewer’s name is always concealed from the submitting author.
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