Patient Flow and Management in Radiation Oncology: A Lean Healthcare, Risk Management, Digitalization, and Artificial Intelligence Perspective
DOI:
https://doi.org/10.22399/ijhemas.23Keywords:
Radiation oncology, patient flow, clinical management, ean healthcareAbstract
Abstract
Radiotherapy is one of the essential components of cancer treatment, utilized for curative, adjuvant, neoadjuvant, and palliative purposes. Evidence-based models demonstrate that external beam radiotherapy may be indicated at least once during a patient's lifetime in approximately 52% of cancer cases. While technological advancements such as IMRT, VMAT, IGRT, SRS, SBRT, and adaptive radiotherapy have improved treatment accuracy, they have also rendered processes increasingly dependent on additional personnel, devices, software, and quality control components. Patient flow in radiation oncology represents an interdependent process chain comprising multidisciplinary evaluation, CT simulation, immobilization, target and organ-at-risk contouring, planning, quality assurance, treatment delivery, and follow-up. The objective of this study is to summarize and evaluate this patient flow and clinical management process from the perspectives of Lean Healthcare, Six Sigma, Value Stream Mapping, Queueing Theory, FMEA, digitalization, and artificial intelligence. The literature indicates that process standardization, risk-based quality management, capacity planning, and digital integration can provide significant contributions to patient waiting times, resource utilization, and patient safety. Furthermore, while artificial intelligence offers major opportunities, particularly in auto-contouring and treatment planning, it requires human supervision, validation, data security, and continuous quality assurance.
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