ArticleJournal of oncology practice2012
Technology resource planning in radiation oncology: application of a needs-based analytic framework to radiosurgery planning in Ontario.
Article in Journal of oncology practice, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Forecasting maldistribution of human resources for healthcare and patients in Japan: a utilization-based approach.BMC health services research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWith 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.
methodsUsing 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.
resultsThe 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.
conclusionWe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.