Literature DB >> 14524490

Capacity and demand models for radiotherapy treatment machines.

S J Thomas1.   

Abstract

Models to predict the number of linear accelerators (linacs) required usually assume that capacity needs to equal demand. Queuing theory shows that capacity needs to exceed mean demand, to avoid the build-up of waiting times. A model has been developed, using Monte-Carlo modelling, to calculate the percentage of spare capacity required to keep waiting times to treatment short. For a matched pair of linacs, in a department that closes on bank holidays and compensates for category 1 patients by treating twice before or after the break, about 10% spare capacity is required to ensure that 86% of patients are able to start radiotherapy within a week of completing the treatment planning process. If a machine is booked as a single (unmatched machine), an additional 3% spare capacity is needed. If all bank holidays in the year are worked, then about 3% less is needed.

Entities:  

Mesh:

Year:  2003        PMID: 14524490     DOI: 10.1016/s0936-6555(03)00065-7

Source DB:  PubMed          Journal:  Clin Oncol (R Coll Radiol)        ISSN: 0936-6555            Impact factor:   4.126


  5 in total

Review 1.  Operations research for resource planning and -use in radiotherapy: a literature review.

Authors:  Bruno Vieira; Erwin W Hans; Corine van Vliet-Vroegindeweij; Jeroen van de Kamer; Wim van Harten
Journal:  BMC Med Inform Decis Mak       Date:  2016-11-25       Impact factor: 2.796

2.  Modelling the throughput capacity of a single-accelerator multitreatment room proton therapy centre.

Authors:  A H Aitkenhead; D Bugg; C G Rowbottom; E Smith; R I Mackay
Journal:  Br J Radiol       Date:  2012-12       Impact factor: 3.039

3.  Resource planning principles for the radiotherapy process using simulations applied to a longer vacation period use case.

Authors:  Jesper Lindberg; Mrugaja Gurjar; Paul Holmström; Stefan Hallberg; Thomas Björk-Eriksson; Caroline E Olsson
Journal:  Tech Innov Patient Support Radiat Oncol       Date:  2021-10-16

4.  More from less: Study on increasing throughput of COVID-19 screening and testing facility at an apex tertiary care hospital in New Delhi using discrete-event simulation software.

Authors:  Naveen R Gowda; Amitesh Khare; H Vikas; Angel R Singh; D K Sharma; Ramya Poulose; Dhayal C John
Journal:  Digit Health       Date:  2021-09-27

5.  Using queuing theory and simulation model to optimize hospital pharmacy performance.

Authors:  Mohammadkarim Bahadori; Seyed Mohsen Mohammadnejhad; Ramin Ravangard; Ehsan Teymourzadeh
Journal:  Iran Red Crescent Med J       Date:  2014-03-05       Impact factor: 0.611

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.