TY - JOUR
T1 - Professional implications of introducing artificial intelligence in healthcare
T2 - An evaluation using radiation medicine as a testing ground
AU - Gillan, Caitlin
AU - Milne, Emily
AU - Harnett, Nicole
AU - Purdie, Thomas G.
AU - Jaffray, David A.
AU - Hodges, Brian
N1 - Funding Information:
The authors would like to acknowledge the clinical staff in the Radiation Medicine Program at the Princess Margaret Cancer Centre for their willingness to participate in this study and sharing their perspectives on AI.
Publisher Copyright:
© 2018 Cambridge University Press.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Aim This study will evaluate radiation medicine professionals' perceptions of clinical and professional risks and benefits, and the evolving roles and responsibilities with artificial intelligence (AI).Methods Radiation oncologists (ROs), medical physicists (MPs), treatment planners (TP-RTTs) and treatment delivery radiation therapists (TD-RTTs) at a cancer centre in preliminary stages of implementing an AI-enabled treatment planning system were invited to participate in uniprofessional focus groups. Semi-structured scripts addressed the perceptions of AI, including thoughts regarding changing roles and competencies. Sessions were audiorecorded, transcribed and coded thematically through consensus-building.Results A total of 24 participants (four ROs, five MPs, seven TP-RTTs and eight TD-RTTs) were engaged in four focus groups of 58 minutes average duration (range 54-61 minutes). Emergent themes addressed AI's impact on quality of care, changing professional tasks and changing competency requirements. Time-consuming repetitive tasks such as delineating targets, generating treatment plans and quality assurance were thought conducive to offloading to AI. Outcomes data and adaptive planning would be incorporated into clinical decision-making. Changing workload would necessitate changing skills, prioritising plan evaluation over generation and increasing interprofessional communication. All groups discussed AI reducing the need for TP-RTTs, though displacement was thought more likely than replacement.Conclusions It is important to consider how professionals perceive AI to be proactive in informing change, as gains in quality and efficiency will require new workflows, skills and education.
AB - Aim This study will evaluate radiation medicine professionals' perceptions of clinical and professional risks and benefits, and the evolving roles and responsibilities with artificial intelligence (AI).Methods Radiation oncologists (ROs), medical physicists (MPs), treatment planners (TP-RTTs) and treatment delivery radiation therapists (TD-RTTs) at a cancer centre in preliminary stages of implementing an AI-enabled treatment planning system were invited to participate in uniprofessional focus groups. Semi-structured scripts addressed the perceptions of AI, including thoughts regarding changing roles and competencies. Sessions were audiorecorded, transcribed and coded thematically through consensus-building.Results A total of 24 participants (four ROs, five MPs, seven TP-RTTs and eight TD-RTTs) were engaged in four focus groups of 58 minutes average duration (range 54-61 minutes). Emergent themes addressed AI's impact on quality of care, changing professional tasks and changing competency requirements. Time-consuming repetitive tasks such as delineating targets, generating treatment plans and quality assurance were thought conducive to offloading to AI. Outcomes data and adaptive planning would be incorporated into clinical decision-making. Changing workload would necessitate changing skills, prioritising plan evaluation over generation and increasing interprofessional communication. All groups discussed AI reducing the need for TP-RTTs, though displacement was thought more likely than replacement.Conclusions It is important to consider how professionals perceive AI to be proactive in informing change, as gains in quality and efficiency will require new workflows, skills and education.
KW - artificial intelligence
KW - competency
KW - education, practice
KW - professional
KW - treatment planning
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U2 - 10.1017/S1460396918000468
DO - 10.1017/S1460396918000468
M3 - Article
AN - SCOPUS:85055009595
SN - 1460-3969
VL - 18
SP - 52
EP - 54
JO - Journal of Radiotherapy in Practice
JF - Journal of Radiotherapy in Practice
IS - 1
ER -