Novel Approaches to Radiotherapy Planning and Scheduling in the NHS

Lead Research Organisation: Coventry University
Department Name: Engineering and Computing


The problem of efficient radiotherapy planning and resource management In oncology departments, In terms of both manpower and the availability of equipment, has been recognised as a key to their smooth running. The various activities, starting from patient referral through to the delivery of the appropriate treatment, form a complex system, for which generating a high quality planning and scheduling solution is a challenging real-world problem that significantly impacts on healthcare staff and patients.This ambitious research proposal concerns both the generation of possible radiotherapy treatments, for patients and the scheduling of resources. This is a joint research proposal between two research groups from the University of Nottingham and Coventry University with expertise from differing but complementary disciplines. Two large hospitals, Nottingham City Hospital and the UHCW NHS Trust in Coventry, which are both providing radiotherapy treatment to a large population throughout their respective regions, are acting as collaborators on the project. They will provide real-world data and expertise in the domain of radiotherapy treatment. The proposed research requires a multidisciplinary effort, aiming at combining different operational research and artificial intelligence disciplines within a complex real-world medical environment.A successful outcome to the proposed research would significantly improve the efficiency and the quality of radiotherapy treatment in the UK. It could lead to a reduction of waiting time and waiting lists for treatments, a reduction of stress levels in patients and improved consistency in terms of dose delivery. Most Important of all, it has a definite potential to increase the survival rate of cancer patients


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Description Different approaches to scheduling of radiotherapy pretreatment and treatment appointments were developed considering various medical and scheduling constraints and different objectives, such as minimisation of number of patients who do not meet their waiting time targets, minimisation of usage of overtime slots, minimisation of machines idle time, and so on. Motivated by heuristics developed for production scheduling problems, novel heuristics-based methods were developed for four unites that comprised the whole radiotherapy process. Another approach was based on genetic algorithms (GAs) which optimised the whole radiotherapy process .
Different experiments were carried out to analyse the performance of the two radiotherapy scheduling approaches. It was shown that both approaches created schedules of good performance with respect to waiting times and percentages of late patients of different categories.
Exploitation Route Radiotherapy scheduling problems can be adapted and modified for other problems of patient scheduling, in particular those where meeting the waiting time targets is of interest.
Further on, the developed models and approaches can be applied to a variety of scheduling problems which are characterised by the presence of multiple resource types, dynamic arrivals of tasks/activities/jobs to be scheduled, different importance of tasks/activities/jobs, various types of uncertainties that are inherent in real-world scheduling and multiple criteria to measure the quality of schedules.
Sectors Healthcare,Manufacturing, including Industrial Biotechology

Description The hospitals expressed a high level of interest in the results achieved throughout the project. They were provided with a prototype software package for radiotherapy scheduling.
Description Nottingham City Hospital 
Organisation Nottingham City Hospital
Country United Kingdom 
Sector Hospitals 
Start Year 2006
Description Walsgrave General Hospital 
Organisation University Hospitals Coventry and Warwickshire NHS Trust
Department Walsgrave General Hospital
Country United Kingdom 
Sector Hospitals 
PI Contribution Development of new scheduling models and of prototype decision support systems for scheduling of radiotherapy patients. A successful outcome of the research can potentially lead to (a) an increased ability to respond to greater complexities of treatments within the operational resource constraints and thereby improving the quality of treatments, (b) increased patient throughput, reducing waiting time and waiting lists for treatments, (c) smoother operation of radiotherapy clinics, thus reducing stress levels in patients and improving consistency in terms of dose delivery, and (d) most of all, a potential increase in the survival rate of cancer patients by reducing the waiting time for radiotherapy treatments.
Collaborator Contribution Radiologists in the Arden cancer Centre in the University Hospitals Coventry and Warwickshire NHS Trust provided us with their expertise in patients scheduling and patient data which were used in our developed prototype systems for scheduling of radiotherapy patients.
Impact Outputs of this research include a number of novel radiotherapy patients scheduling optimisation models disseminated to medical, operational research and computer science audience. They are published in 1 international peer reviewed journals, 2 reviewed chapters in edited books and 9 papers in proceedings of international conferences. Two prototype decision support systems for scheduling of radiotherapy patients are developed.
Start Year 2006