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Technology Resource Planning in Radiation Oncology: Application of a Needs-Based Analytic Framework to Radiosurgery Planning in Ontario

机译:放射肿瘤学中的技术资源规划:基于需求的分析框架在安大略省放射外科规划中的应用

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AbstractThe authors demonstrate through the example of single brain metastases in Ontario that it is feasible to perform explicit needs-based resource planning in radiation oncology. Purpose: With the emergence of radiosurgery as a new radiotherapeutic technique, health care decision makers are required to allocate capital radiotherapy resources to meet both current and future radiosurgery requirements. The goal of this article is to demonstrate the feasibility of applying an explicit, needs-based model to resource planning in radiation oncology. Methods: Using an analytic model that relates radiosurgery need to population size, epidemiology, level of service planned, and productivity, the current radiosurgical need for single brain metastases in Ontario was estimated. The model was populated using Ontario-specific data where possible and supplemented with information from the published literature. Multiway sensitivity analyses were performed to calculate the minimum and maximum technology requirements. Results: The calculated number of full-time radiosurgical units required to treat patients with single brain metastases in Ontario was 5.9. Sensitivity analyses performed varying both level of service planned and productivity yielded a range of requirements from 2.5 to 12.2 full-time radiosurgery units. Conclusion: We have shown through the example of single brain metastases in Ontario that it is feasible to perform explicit, needs-based resource planning in radiation oncology. As the availability of new specialized technology increases, health care decision makers may use this approach to ensure the needs of their population are met while maximizing productivity and minimizing opportunity cost.
机译:摘要作者通过安大略省单脑转移瘤的例子证明,在放射肿瘤学中进行基于需求的明确资源规划是可行的。目的:随着放射外科作为一种新的放射治疗技术的出现,医疗保健决策者需要分配基本的放射治疗资源以满足当前和未来的放射外科需求。本文的目的是演示将明确的基于需求的模型应用于放射肿瘤学资源规划的可行性。方法:使用将放射外科需求与人口规模,流行病学,计划的服务水平和生产率相关联的分析模型,对安大略省目前对单脑转移的放射外科需求进行了估算。在可能的情况下,使用安大略省特定的数据填充该模型,并用已发表文献中的信息进行补充。进行了多路灵敏度分析,以计算最小和最大技术要求。结果:在安大略省,治疗单脑转移患者所需的专职放射外科治疗单位数量为5.9。进行的敏感性分析改变了计划的服务水平和生产率,产生了从2.5到12.2的专职放射外科治疗单位的一系列要求。结论:我们通过安大略省单脑转移瘤的例子表明,在放射肿瘤学中进行明确的,基于需求的资源规划是可行的。随着新专业技术的可用性增加,医疗保健决策者可以使用这种方法来确保满足其人口的需求,同时最大程度地提高生产力并最小化机会成本。

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