Open AccessRadiation therapy staffing model 2014
Author(s) -
Smith Leigh J.,
Kearvell Rachel,
Arnold Anthony J.,
Choma Kevina,
Cooper Aniko,
Young Michael R.,
Matthews Donna L.,
Hilder Bronwyn,
Howson Debbie,
Fox Katherine,
Churcher Katheryn
Publication year - 2016
Publication title -
journal of medical radiation sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 18
eISSN - 2051-3909
pISSN - 2051-3895
DOI - 10.1002/jmrs.198
Subject(s) - staffing , workforce , flexibility (engineering) , service delivery framework , medical physics , radiation treatment planning , service (business) , schedule , radiation oncology , radiation therapist , operations management , medicine , radiation therapy , computer science , business , nursing , surgery , engineering , management , marketing , economics , operating system , economic growth
In 2001, the Radiation Therapy Advisory Panel ( RTAP ) of the Australian Society of Medical Imaging and Radiation Therapy ( ASMIRT ) (formerly known as Australian Institute of Radiography) published a model for radiation therapist staffing in Australian radiation oncology departments. Between 2012–2013, the model was reviewed to ensure it reflected current radiation therapy practice, technology, and to facilitate forward planning of the radiation therapy workforce. Method Twenty‐four sites from all states participated and provided data on megavoltage simulation, planning and treatment delivery. For simulation and planning activity, the length of time to complete was collected against relevant Medicare Benefits Schedule ( MBS ) items. For treatment delivery, time to complete activities was collected against a common set of activities. Modelling assumptions are clearly identified in the methodology. Results A new model was developed retaining the essential model parameter of full‐time equivalent ( FTE ) radiation therapists ( RT s) per linear accelerator operating hour as in the 2001 model but based on contemporary practice and data. The model also includes significant refinements that improve the model's overall utility and flexibility for both workforce planning purposes and for individual services to use the model according to their own organisational needs and service delivery profiles. Conclusion The ASMIRT believes that the 2014 RT staffing model provides the utility and flexibility for radiation oncology services to best plan RT staffing establishments according to their needs and reflecting the diversity between services and within the sector. It should also provide a robust and valid basis for governments and service planners to use as a guide in workforce planning into the future.