PURPOSE: The specialty of radiation oncology has experienced significant workforce planning challenges in many countries. Our purpose was to develop and validate a workforce-planning model that would forecast the balance between supply of, and demand for, radiation oncologists in Canada over a minimum 10-year time frame, to identify the model parameters that most influenced this balance, and to suggest how this model may be applicable to other countries. METHODS: A forward calculation model was created and populated with data obtained from national sources. Validation was confirmed using a historical prospective approach. RESULTS: Under baseline assumptions, the model predicts a short-term surplus of RO trainees followed by a projected deficit in 2020. Sensitivity analyses showed that access to radiotherapy (proportion of incident cases referred), individual RO workload, average age of retirement and resident training intake most influenced balance of supply and demand. Within plausible ranges of these parameters, substantial shortages or excess of graduates is possible, underscoring the need for ongoing monitoring. CONCLUSIONS: Workforce planning in radiation oncology is possible using a projection calculation model based on current system characteristics and modifiable parameters that influence projections. The workload projections should inform policy decision making regarding growth of the specialty and training program resident intake required to meet oncology health services needs. The methods used are applicable to workforce planning for radiation oncology in other countries and for other comparable medical specialties.
PURPOSE: The specialty of radiation oncology has experienced significant workforce planning challenges in many countries. Our purpose was to develop and validate a workforce-planning model that would forecast the balance between supply of, and demand for, radiation oncologists in Canada over a minimum 10-year time frame, to identify the model parameters that most influenced this balance, and to suggest how this model may be applicable to other countries. METHODS: A forward calculation model was created and populated with data obtained from national sources. Validation was confirmed using a historical prospective approach. RESULTS: Under baseline assumptions, the model predicts a short-term surplus of RO trainees followed by a projected deficit in 2020. Sensitivity analyses showed that access to radiotherapy (proportion of incident cases referred), individual RO workload, average age of retirement and resident training intake most influenced balance of supply and demand. Within plausible ranges of these parameters, substantial shortages or excess of graduates is possible, underscoring the need for ongoing monitoring. CONCLUSIONS: Workforce planning in radiation oncology is possible using a projection calculation model based on current system characteristics and modifiable parameters that influence projections. The workload projections should inform policy decision making regarding growth of the specialty and training program resident intake required to meet oncology health services needs. The methods used are applicable to workforce planning for radiation oncology in other countries and for other comparable medical specialties.
Authors: A Rodríguez; M Arenas; P C Lara; J López-Torrecilla; M Algara; A Conde; H Pérez-Montero; J L Muñoz; P Peleteiro; M J Pérez-Calatayud; J Contreras; C Ferrer Journal: Clin Transl Oncol Date: 2019-04-03 Impact factor: 3.405
Authors: T Sebastian Haupt; Todd Dow; Mike Smyth; J Thomas Toguri; Alysha Roberts; K L Raju; David Bowes Journal: J Cancer Educ Date: 2020-04 Impact factor: 2.037
Authors: Che Hsuan David Wu; Nauman Malik; Michael Kim; Teri Stuckless; Ross Halperin; Jean Archambault; Robert Thompson; Jolie Ringash; Michael Brundage; Shaun K Loewen Journal: Adv Radiat Oncol Date: 2022-02-06
Authors: Shaun Loewen; Michael Brundage; Keith Tankel; Alysa Fairchild; Theresa Trotter; Ericka Wiebe; Paris Ann Ingledew; Teri Stuckless; Don Yee Journal: Can Med Educ J Date: 2012-03-31