Medical science and technology continue to advance, creating new possibilities for tailored and better targeted treatment for patients. In radio-therapy, advances in imaging, for example the launch of MR-Linacs, expands the potential use of radiation treatment to more cancer types and enables lower-margin planning, online adaptive treatment and hypo-fractionation – a treatment plan where the planned radiation dose is delivered in five treatment sessions, so-called fractions, or less.
Aging populations and more treatment options will lead to increasing costs for healthcare systems. As a result, there is a clear trend in all markets, regardless of reimbursement system or financing model, to align economic incentives with quality of care and to focus on cost efficiency and productivity. This benefits cost-efficient treatments such as radiotherapy, and within radiotherapy more productive treatment plans such as hypo-fractionation
More treatment options and workflow complexity across most healthcare disciplines increase the need for digital decision support for clinicians, and workflow management tools for clinics. In addition, oncology and radio-therapy are data-intensive disciplines that are well-suited to reap the benefits of AI-supported automation tools and big-data analysis. Tying data
from different workflows together into integrated solutions will benefit both precision and productivity in cancer care.