Patient Satisfaction after the Redesign of a Chemotherapy Booking Process

Aristizabal, Ruben; Chow, Vincent S.; French, J Briefer; Khurshed, Fareeza; McGahan, Colleen; Puterman, Martin L.; Runzer, Nancy; Santibáñez, Pablo; Tyldesley, Scott

doi:10.12927/hcq.2013.23021

Cited by 2 publications

(1 citation statement)

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“…Some publications also discuss the potential of AI for augmenting health care administration. One recent example was a scheduling program developed by a research team at the BC Cancer Agency, which was able to schedule daily chemotherapy appointments more efficiently and effectively than staff members, resulting in improved efficiencies and increased patient satisfaction [3]. The intent of this article is not to describe all the potential clinical applications of AI and will use selected examples to illustrate key points.…”

Section: Introductionmentioning

confidence: 99%

Preparing for Artificial Intelligence: Systems-Level Implications for the Medical Imaging and Radiation Therapy Professions

French

Chen

2019

Journal of Medical Imaging and Radiation Sciences

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Innovations in artificial intelligence (AI) are driving a new industrial revolution, and as a result, the medical radiation sciences is experiencing transformational, open, beneficial, yet disruptive changes. Many studies have already been published on specific frontline examples where AI will improve cancer care, but discussions of how AI will change the medical radiation sciences and its associated professions at the systems level have been comparatively sparse. In this article, the system-level implications of AI on the medical radiation sciences are discussed, and recommendations are made on how professionals in this field may need to adapt in preparation for a future where AI will be an integral part of the health care system at all levels.

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Section: Introductionmentioning

confidence: 99%