Chemotherapy Appointment Scheduling

Addressing Uncertainty and Fairness
Erscheinungsjahr 2026
ISBN: 978-3-032-11551-5
Verlag: Springer

Buch, Englisch, 71 Seiten, Format (B × H): 173 mm x 246 mm, Gewicht: 338 g

Reihe: Synthesis Lectures on Operations Research and Applications

This book discusses how analytics can handle uncertainty and fairness issues in scheduling chemotherapy treatments.  Specifically, the authors explore the complexities of chemotherapy scheduling, showing how analytics can be used to create fairer and more efficient chemotherapy schedules. By addressing uncertainty in infusion times and balancing the needs of both patient and staff, the book offers novel insights, practical models, and actionable solutions for healthcare professionals aiming to improve patient care in chemotherapy clinics.  Readers will gain a deep understanding of the unique challenges in scheduling chemotherapy treatments, with a focus on handling uncertainty in treatment durations, coordinating clinic resources, and ensuring fairness among patients. This book uses real data from chemotherapy clinics to develop models and generate solutions representing fair and efficient schedules. Alongside methodological knowledge, readers will acquire managerial insights that can directly enhance the scheduling processes in real-world oncology settings.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Gul, Serhat

Karsu, Özlem

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Pflege Krankenpflege
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Onkologie, Krebsforschung
• Wirtschaftswissenschaften Volkswirtschaftslehre Gesundheitsökonomie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Krankenhausmanagement, Praxismanagement

Inhaltsverzeichnis

Introduction: Background Information on Chemotherapy Delivery.- Chemotherapy Scheduling.- Uncertainty in Chemotherapy Scheduling.- Fairness in Chemotherapy Scheduling.- Case Study.- Conclusion and Future Directions.

Über Autor(innen)

Serhat Gul, Ph.D., is an Associate Professor in the Department of Industrial University at TED University.  He completed his Ph.D. and M.Sc. in Industrial Engineering at Arizona State University in 2010 and 2007, respectively, and earned his B.Sc. in Industrial Engineering from Sabanci University in 2006. He has been a faculty member at TED University in Ankara, Turkey, since 2014. In 2023-2024, he served as a visiting assistant professor at the Isenberg School of Management, University of Massachusetts Amherst. Dr. Gül's primary research interests lie in stochastic optimization and its applications to healthcare delivery systems.

Özlem Karsu, Ph.D., is an Associate Professor in the Department of Industrial Engineering at Bilkent University and a visiting scholar at the Technical University of Munich for the 2025–2026 academic year. She received her B.S and M.S. degrees from the Industrial Engineering Department of the Middle East Technical University, in 2008 and 2010, respectively. She received her Ph.D. degree in Operational Research from the London School of Economics in 2014.  Dr. Karsu’s research lies in the domains of inequity-averse optimization and multicriteria decision making. She aims to help decision makers to address equity (fairness) concerns through operations research tools.