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. 2020 Nov 17:16:58-64.
doi: 10.1016/j.tipsro.2020.10.003. eCollection 2020 Dec.

Cautiously optimistic: A survey of radiation oncology professionals' perceptions of automation in radiotherapy planning

Vikneswary Batumalai  1   2   3 , Michael G Jameson  1   2   3 , Odette King  1 , Rhiannon Walker  1 , Chelsea Slater  1 , Kylie Dundas  1   2   3 , Glen Dinsdale  1 , Andrew Wallis  1 , Cesar Ochoa  1 , Rohan Gray  1 , Phil Vial  1   4 , Shalini K Vinod  1   2   3
Affiliations

Cautiously optimistic: A survey of radiation oncology professionals' perceptions of automation in radiotherapy planning

Vikneswary Batumalai et al. Tech Innov Patient Support Radiat Oncol. .

Abstract

Introduction: While there is evidence to show the positive effects of automation, the impact on radiation oncology professionals has been poorly considered. This study examined radiation oncology professionals' perceptions of automation in radiotherapy planning.

Method: An online survey link was sent to the chief radiation therapists (RT) of all Australian radiotherapy centres to be forwarded to RTs, medical physicists (MP) and radiation oncologists (RO) within their institution. The survey was open from May-July 2019.

Results: Participants were 204 RTs, 84 MPs and 37 ROs (response rates ∼10% of the overall radiation oncology workforce). Respondents felt automation resulted in improvement in consistency in planning (90%), productivity (88%), quality of planning (57%), and staff focus on patient care (49%). When asked about perceived impact of automation, the responses were; will change the primary tasks of certain jobs (66%), will allow staff to do the remaining components of their job more effectively (51%), will eliminate jobs (20%), and will not have an impact on jobs (6%). 27% of respondents believe automation will reduce job satisfaction. 71% of respondents strongly agree/agree that automation will cause a loss of skills, while only 25% strongly agree/agree that the training and education tools in their department are sufficient.

Conclusion: Although the effect of automation is perceived positively, there are some concerns on loss of skillsets and the lack of training to maintain this. These results highlight the need for continued education to ensure that skills and knowledge are not lost with automation.

Keywords: Artificial intelligence; Automation; Education; Perception; Radiation oncology; Survey; Treatment planning.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
(a) Current level of planning tasks automation, (b) planned level of planning tasks automation in the next 2 years. Abbreviations: QA – quality assurance; R&V – record and verify; OAR – organ at risk.
Fig. 2
Fig. 2
(a) Empowerment to drive decisions about implementing automation, (b) opinion on the importance of automating planning processes. Abbreviations: RT – radiation therapist; MP – medical physicist; RO – radiation oncologist; Gen Z – Generation Z; Gen Y – Generation Y; Gen X – Generation X; Baby Boom – Baby Boomers.
Fig. 3
Fig. 3
(a) automation will provide only positive benefits for your department; (b) your department is already too over-reliant on automation; (c) automation will cause a loss of understanding of general underlying principles of radiotherapy; (d) current staff training and educational tools provided by your department are sufficient to ensure staff do not lose understanding of general underlying principles of radiotherapy. Abbreviations: RT – radiation therapist; MP – medical physicist; RO – radiation oncologist.
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