Solving operational problems in outpatient chemotherapy clinics using mathematical programming and simulation

Heshmat, Mahmoud; Eltawil, Amr B.

doi:10.1007/s10479-019-03500-y

Cited by 16 publications

(7 citation statements)

References 28 publications

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“…In Hesmat and Eltawil (2019) a MIP model is proposed to provide the best appointment scheduling for patients, considering the availability of nurses and pharmacists.…”

Section: Literature Reviewmentioning

confidence: 99%

Master chemotherapy planning and clinicians rostering in a hospital outpatient cancer centre

Carello

Landa

Tànfani

et al. 2021

Cent Eur J Oper Res

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In the past years, the number of patients in need of chemotherapy treatments has been constantly increasing. Chemotherapy treatments must be carefully planned to provide a suitable and timely care. They are often provided within an outpatient setting. Clinicians and nurses staff must face the increasing demand for chemotherapy treatment with limited resources, such as exam rooms, beds, and seats. In this work, we consider a cancer centre shared among different oncologist specialties, as suggested by the Organisation of European Cancer Institutes. We focus on the oncologist visit that each patient must undergo before the drug infusion, to check if the patient's conditions are compatible with the drug infusion. We consider the problem of planning the weekly assignment of consultation rooms to cancer pathologies, referred to as Master Chemotherapy Planning. Further, we jointly address the problem of selecting a clinician with suitable skills to cover each consultation room in the weekly schedule, given the cliniciansávailability over a month. Several criteria are considered, such as the number of visits in overtime, the amount of met demand and the clinicians' workload. The problem is formulated as a lexicographic multiobjective optimisation problem B Paolo Landa

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“…In Hesmat and Eltawil (2019) a MIP model is proposed to provide the best appointment scheduling for patients, considering the availability of nurses and pharmacists.…”

Section: Literature Reviewmentioning

confidence: 99%

Master chemotherapy planning and clinicians rostering in a hospital outpatient cancer centre

Carello

Landa

Tànfani

et al. 2021

Cent Eur J Oper Res

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“…Once the process has been completed, and a new method of appointment scheduling has been obtained, the simulation will be used to corroborate that the desired level of balanced workload can be achieved, as well as to compare it with the existing method and verify that the new method is more efficient. In [16], in the context of a centre to which patients come for chemotherapy, the problem of minimising delays in patient treatments and the total working time of the centre is addressed. Specifically, the aim is to find the optimal starting day of treatment for each patient so that their chemotherapy cycle is completed as soon as possible, as well as for the centre's professionals to achieve this goal with as few working hours as possible.…”

Section: Literature Reviewmentioning

confidence: 99%

Effective Optimisation of the Patient Circuits of an Oncology Day Hospital: Mathematical Programming Models and Case Study

et al. 2021

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In this paper, we first use the information we have on the patients of an oncology day hospital to distribute the treatment schedules they have in each of the visits to this centre. To do this, we propose a deterministic mathematical programming model in such a way that we minimise the duration of the waiting room stays of the total set of patients and taking into account the restrictions of the circuit. Secondly, we will look for a solution to the same problem under a stochastic approach. This model will explicitly consider the existing uncertainty in terms of the different times involved in the circuit, and this model also allows the reorganisation of the schedules of medical appointments with oncologists. The models are complemented by a tool that solves the problem of assigning nurses to patients. The work is motivated by the particular characteristics of a real hospital and the models are used and compared with data from this case.

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“…Thus, in addition to the requirements defined in Section 2, the solution scheduling has to guarantee that (i) each patient is assisted by exactly one nurse (Turkcan et al 2012); (ii) each nurse can assist from 1 to k patients for each time slot (Turkcan et al 2012); (iii) treatments cannot exceed the maximum quantity of drugs available for each day (Heshmat and Eltawil 2021); (iv) treatments cannot be scheduled at the latest available time slot, since some drugs might require a long time to be prepared (Huggins et al 2014); registrations with the highest priorities should be scheduled before other registrations (Dodaro et al 2018).…”

Section: Extended Ctsmentioning

confidence: 99%

“…Moreover, we consider a planning horizon of one week other than the daily actually employed in the hospital. Then, we enrich the problem and the related ASP encoding considering features often employed in other hospitals, considered in related papers (Turkcan et al 2012;Turkcan et al 2012;Heshmat and Eltawil 2021;Huggins et al 2014;Dodaro et al 2018), and/or desired by the S. Martino Hospital, i.e., we explicitly consider the availability of nurses and drugs or a limit to the starting time of treatments (Section 3.2). Both encoding are evaluated on real data of the San Martino Hospital (Section 4): results using the state-of-the-art ASP solver CLINGO (Gebser et al 2012) show that ASP is an effective solving methodology for solving all these variants of the presented CTS problem.…”

Section: Introductionmentioning

confidence: 99%

An ASP-based Solution to the Chemotherapy Treatment Scheduling problem

Dodaro¹,

Galatà²,

Grioni³

et al. 2021

Preprint

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The problem of scheduling chemotherapy treatments in oncology clinics is a complex problem, given that the solution has to satisfy (as much as possible) several requirements such as the cyclic nature of chemotherapy treatment plans, maintaining a constant number of patients, and the availability of resources, e.g., treatment time, nurses, and drugs. At the same time, realizing a satisfying schedule is of upmost importance for obtaining the best health outcomes.In this paper we first consider a specific instance of the problem which is employed in the San Martino Hospital in Genova, Italy, and present a solution to the problem based on Answer Set Programming (ASP). Then, we enrich the problem and the related ASP encoding considering further features often employed in other hospitals, desirable also in S. Martino, and/or considered in related papers. Results of an experimental analysis, conducted on the real data provided by the San Martino Hospital, show that ASP is an effective solving methodology also for this important scheduling problem. Under consideration for acceptance in TPLP.

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Solving operational problems in outpatient chemotherapy clinics using mathematical programming and simulation

Cited by 16 publications

References 28 publications

Master chemotherapy planning and clinicians rostering in a hospital outpatient cancer centre

Master chemotherapy planning and clinicians rostering in a hospital outpatient cancer centre

Effective Optimisation of the Patient Circuits of an Oncology Day Hospital: Mathematical Programming Models and Case Study

An ASP-based Solution to the Chemotherapy Treatment Scheduling problem

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