Algorithms for scheduling of chemotherapy plans

Sevinç, Süleyman; Şanlı, Ulus Ali; Göker, Erdem

doi:10.1016/j.compbiomed.2013.10.012

Cited by 40 publications

(22 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, they assigned a nurse to each group of patients and chairs, and determined treatment start times based on an IP model. Sevinc et al [9] also considered a twophase approach. They assumed that laboratory tests are conducted a day before the infusion.…”

Section: Literature Reviewmentioning

confidence: 99%

Chemotherapy appointment scheduling under uncertainty by considering workload balance among nurses

Gül¹

2021

Pamukkale J Eng Sci

View full text Add to dashboard Cite

Balancing nurse workload while scheduling outpatient chemotherapy appointments under uncertainty is a challenging problem. In this study, a two-stage stochastic mixed-integer programming model is proposed for setting appointment times of patients and assigning patients to chairs and nurses without distorting the workload balance among nurses. The uncertainty in pre-medication and infusion durations is considered. The objective function of the model minimizes the expected weighted sum of patient waiting time and nurse overtime. Computational experiments are conducted based on data from an outpatient chemotherapy unit of a large hospital. The trade-off between the two competing criteria of the study is investigated. The relationship between the numbers of chairs and nurses in the clinic with the performance measures is examined. The benefit of considering uncertainty is assessed by calculating the value of stochastic solution Belirsizlik varken ayaktan kemoterapi randevularının çizelgelenmesi esnasında hemşirelerin iş yükünü dengelemek zor bir problemdir. Bu çalışmada, hastaların randevu vakitlerinin belirlenmesini ve hemşirelerin kendi aralarındaki iş yükü dengesini bozmadan hastaların koltuklara ve hemşirelere atanmasını sağlayan iki aşamalı stokastik karışık tamsayılı programlama modeli tasarlanmıştır. Çalışmada premedikasyon ve infüzyon sürelerindeki belirsizlik dikkate alınmıştır. Modelin amaç fonksiyonu, hastaların bekleme süreleri ve hemşirelerin fazla mesai sürelerinin ağırlıklandırılmış toplamının beklenen değerini enküçüklemektedir. Büyük bir hastanenin ayaktan kemoterapi ünitesinden elde edilmiş veriler kullanılarak bilgisayısal deneyler yapılmıştır. Çalışmada gözetilen iki rakip ölçüt arasındaki denge incelenmiştir. Klinikte bulunan koltuk ve hemşire sayısı ile performans ölçütleri arasındaki ilişki irdelenmiştir. Stokastik çözüm değeri hesaplanarak, belirsizliği dikkate alarak çözüm bulmanın faydası ölçülmüştür.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Chemotherapy appointment scheduling under uncertainty by considering workload balance among nurses

Gül¹

2021

Pamukkale J Eng Sci

View full text Add to dashboard Cite

show abstract

“…They validated the model solutions with a simulation study. Two heuristics were developed to assign patients to the infusion chairs by Sevinc, Ali Sanli, and Goker (2013). They decomposed the problem into two phases.…”

Section: Literature Reviewmentioning

confidence: 99%

A stochastic programming approach for chemotherapy appointment scheduling

Demir

Gül

Çelik

2020

Naval Research Logistics

View full text Add to dashboard Cite

Chemotherapy appointment scheduling is a challenging problem due to the uncertainty in premedication and infusion durations. In this paper, we formulate a two‐stage stochastic mixed integer programming model for the chemotherapy appointment scheduling problem under limited availability of nurses and infusion chairs. The objective is to minimize the expected weighted sum of nurse overtime, chair idle time, and patient waiting time. The computational burden to solve real‐life instances of this problem to optimality is significantly high, even in the deterministic case. To overcome this burden, we incorporate valid bounds and symmetry breaking constraints. Progressive hedging algorithm is implemented in order to solve the improved formulation heuristically. We enhance the algorithm through a penalty update method, cycle detection and variable fixing mechanisms, and a linear approximation of the objective function. Using numerical experiments based on real data from a major oncology hospital, we compare our solution approach with several scheduling heuristics from the relevant literature, generate managerial insights related to the impact of the number of nurses and chairs on appointment schedules, and estimate the value of stochastic solution to assess the significance of considering uncertainty.

show abstract

“…However, in real-life scenarios, patients differ in their status, and of course, some patients ought to have priority over others. Sevinc, Sanli, and Goker [14] proposed a two-phase algorithm to solve the chemotherapy scheduling problem to assign patients to minimise their overall wait times. Condotta and Shakhlevich [15] discussed a multilevel model to determine the appointment days for patients to minimise their overall wait times and the nurses' workloads.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving the Operations Performance of a Chemotherapy Clinic: A Two-Phase Approach

Alabdulkarim¹

2018

SAJIE

View full text Add to dashboard Cite

The increasing number of cancer patients, coupled with the development and use of new, efficient medications, has increased the demand for cancer service care. Outpatient chemotherapy clinics (OCCs) are complex facilities, due to the large variability in treatment durations resulting from different cancer types and chemotherapy protocols under limited resources. In this paper we address the operations planning problem encountered by OCCs, of optimally assigning the first days of treatment for a set of new patients in tandem with the presence of existing patients. We propose a two-phase approach to optimise the start days of a set of new patients. In the first stage, a system dynamics (SD) simulation model, adapted from the literature, is used to find the critical days for the new patients -i.e., the upper bounds by which patients must begin treatment. The optimal start days are then determined using a new mixed-integer programming (MIP) model. The results show that the optimal start days can be effectively prioritised and evaluated using simulation and mathematical programming.

show abstract

Algorithms for scheduling of chemotherapy plans

Cited by 40 publications

References 22 publications

Chemotherapy appointment scheduling under uncertainty by considering workload balance among nurses

Chemotherapy appointment scheduling under uncertainty by considering workload balance among nurses

A stochastic programming approach for chemotherapy appointment scheduling

Improving the Operations Performance of a Chemotherapy Clinic: A Two-Phase Approach

Contact Info

Product

Resources

About