Planning oncologists of ambulatory care units

Sadki, Abdellah; Xie, Xiaolan; Chauvin, Franck

doi:10.1016/j.dss.2012.10.020

Cited by 22 publications

(8 citation statements)

References 16 publications

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“…All assumptions except (A6) et (A7) are similar to those of our previous works [23,21,22] and we do not repeat justifications presented in our previous relevant publications. Assumption (A6) on the availability of oncologists is only introduced for simplicity of the presentation and may be relaxed later.…”

Section: Assumptionsmentioning

confidence: 74%

“…One direct extension to this work is to consider separate morning and afternoon shifts where physicians' availability may be restricted to only one shift (see [23]). The proposed method in this paper based on global sequences and target sequences is fully compatible with this extension as it is possible to offer separate global sequences for each shift.…”

Section: Discussionmentioning

confidence: 99%

“…This paper is most closely related to the series of work started with [23] that proposed a linear programming model and a three-stage heuristic for optimizing the medical planning, i.e. the work schedule of oncologists.…”

Section: Literature Reviewmentioning

confidence: 99%

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Daily outpatient chemotherapy appointment scheduling with random deferrals

2018

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In this paper we propose a heuristic approach that computes the order in which patients will be treated in an ambulatory chemotherapy center. Each patient follows an individual treatment plan that fixes dates for series of drug injections separated by recovery periods. The daily care process has three steps: consultation with the oncologist, drug preparation in the pharmacy and drug injection in medical beds. The facility closes after the last injection. As drug injection varying considerably in duration -from 15 minutes to 6 hours -bad schedules lead to excessive overtime. In addition, after the consultation the oncologist may decide to cancel the injection because of a weak patient's health condition. In the current setting of the chemotherapy facility we work with, First Come First Served policy controls the care process. In this study, we propose to compute a common priority list of patients for consultation and injection phases. A unique list of patients is a simple tool used by nurses to manage the flow of patients and to react to uncertain events. A GRASP algorithm is developed to compute optimized list of patients in few seconds as the operating planning context requires. Two objectives are considered; the closing time and the overworking time of the facility. Numerical experiments show that our GRASP is able to quickly reach near optimal solutions and that list of patients policy performance is comparable to more complex scheduling policies. Benchmark data sets are built based on historical data of the French chemotherapy facility, ICL in Saint-Étienne.

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Section: Assumptionsmentioning

confidence: 74%

Section: Discussionmentioning

confidence: 99%

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Daily outpatient chemotherapy appointment scheduling with random deferrals

2018

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“…Mathematical programming is applied to improve scheduling process in chemotherapy clinics. Sadki et al [32] developed an integer programming model to control oncologist and chemotherapy appointments with the objective of minimizing a weighted combination of patient waiting time and makespan (clinic total working time). They assumed that nurses have enough capacity and considered only the treatment stage.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-stage appointment scheduling for outpatient chemotherapy unit: a case study

et al. 2021

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This paper deals with a multi stage hybrid flow-shop problem (HFSP) that arises in a privately Chemotherapy clinic. It aims to optimize the makespan of the daily chemotherapy activity. Each patient must respect the cyclic nature of chemotherapy treatment plans made by his referent oncologist while taking into account the high variability in resource requirements (treatment time, nurse time, pharmacy time). The problem requires the assignment of chemotherapy patients to oncologists, pharmacists, chemotherapy beds or chairs and nurses over a 1-day period. We provided a Mixed Integer Program (MIP) to model this issue, which can be considered as a five-stage hybrid flow-shop scheduling problem with additional resources, dedicated machines, and no-wait constraints. Since this problem is known to be NP-hard, we provided a lower bound expression and developed an approximated solving algorithm: a tabu search inspired metaheuristic based on a constructive heuristic that can quickly reach satisfying results. To assess the empirical performance of the proposed approach, we conducted experiments on randomly generated instances based on real-world data of a Tunisian private clinic: Clinique Ennasr. Computational experiments show the efficiency of the proposed procedures: The mathematical model provided optimal solutions in reasonable computational time only for small instances (up to 10 patients). Meta-heuristic’s results demonstrate, also, that the proposed approach offers good results in terms of solution quality and computational times with an average relative gap to the MIP solution equal to 3.13% and to the lower bound equal to 5.37% for small instances (up to 15 patients). The same gap to the lower bound increases to 25% for medium and large size instances (20-50 patients).

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“…Santibañez et al [8] proposed a simulation-based optimisation model to assign new patients to start days to minimise the nursing workload. Sadki, Xie, and Chauvin [9] developed a MIP model to plan the working times of oncologists in an oncology center. Woodall et al [10] proposed a MIP model to produce weekly and monthly schedules for nurses.…”

Section: Literature Reviewmentioning

confidence: 99%

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

Alabdulkarim¹

2018

SAJIE

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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.

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Planning oncologists of ambulatory care units

Cited by 22 publications

References 16 publications

Daily outpatient chemotherapy appointment scheduling with random deferrals

Daily outpatient chemotherapy appointment scheduling with random deferrals

Multi-stage appointment scheduling for outpatient chemotherapy unit: a case study

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

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