Improving patient-care services at an oncology clinic using a flexible and adaptive scheduling procedure

Hooshangi-Tabrizi, Pedram; Contreras, Ivan; Bhuiyan, Nadia; Batist, Gerald

doi:10.1016/j.eswa.2020.113267

Cited by 16 publications

(13 citation statements)

References 21 publications

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“…In practice, for example, chair and nurse utilization can be as low as 52% and 60%, respectively [14]. And total overtime can be as high as 39 hours over 20 days [15], which is equivalent to 7.8 timeslots per day in our model.…”

Section: Fixed-template Scheduling Heuristicmentioning

confidence: 99%

Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration

Hesaraki

Dellaert

Kok

2022

Health Care Manag Sci

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In this paper, we use a fixed template of slots for the online scheduling of appointments. The template is a link between planning the service capacity at a tactical level and online scheduling at an operational level. We develop a detailed heuristic for the case of drug administration appointments in outpatient chemotherapy. However, the approach can be applied to online scheduling in other application areas as well. The desired scheduling principles are incorporated into the cost coefficients of the objective function of a binary integer program for booking appointments in the template, as requests arrive. The day and time of appointments are decided simultaneously, rather than sequentially, where optimal solutions may be eliminated from the search. The service that we consider in this paper is an example to show the versatility of a fixed template online scheduling model. It requires two types of resource, one of which is exclusively assigned for the whole appointment duration, and the other is shared among multiple appointments after setting up the service. There is high heterogeneity among appointments on a day of this service. The appointments may range from fifteen minutes to more than eight hours. A fixed template gives a pattern for the scheduling of possibly required steps before the service. Instead of maximizing the fill-rate of the template, the objective of our heuristic is to have high performance in multiple indicators pertaining to various stakeholders (patients, nurses, and the clinic). By simulation, we illustrate the performance of the fixed template model for the key indicators.

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Section: Fixed-template Scheduling Heuristicmentioning

confidence: 99%

Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration

Hesaraki

Dellaert

Kok

2022

Health Care Manag Sci

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“…The scholars in this area have built upon optimization studies that preceded their work to develop more comprehensive optimization models. Most deterministic optimization models are integer [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ] or mixed integer programming [ 7 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ]. In mixed integer models, some of the decision variables (but not all) all required to have integer values.…”

Section: Literature Reviewmentioning

confidence: 99%

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling

Hadid

Elomri

Padmanabhan

et al. 2022

IJERPH

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Outpatient Chemotherapy Appointment (OCA) planning and scheduling is a process of distributing appointments to available days and times to be handled by various resources through a multi-stage process. Proper OCAs planning and scheduling results in minimizing the length of stay of patients and staff overtime. The integrated consideration of the available capacity, resources planning, scheduling policy, drug preparation requirements, and resources-to-patients assignment can improve the Outpatient Chemotherapy Process’s (OCP’s) overall performance due to interdependencies. However, developing a comprehensive and stochastic decision support system in the OCP environment is complex. Thus, the multi-stages of OCP, stochastic durations, probability of uncertain events occurrence, patterns of patient arrivals, acuity levels of nurses, demand variety, and complex patient pathways are rarely addressed together. Therefore, this paper proposes a clustering and stochastic optimization methodology to handle the various challenges of OCA planning and scheduling. A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. The experimental results indicate the positive effect of clustering similar appointments on the performance measures and the computational time. The developed cluster-based stochastic optimization approaches showed superior performance compared with baseline and sequencing heuristics using data from a real Outpatient Chemotherapy Center (OCC).

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“…Accordingly, researchers in conjunction with decision-makers have worked on health management (as a pivotal issue in many political and social debates) in different regions and countries across the world to select an optimal form for the usage of healthcare resources [ 43 ]. To do so, they have applied novel decision-making tools to allocate and productive usage of resources [ 44 ] since the quality of the provided services to patients is highly dependent on the available resources. Among required resources, human resources are the most important factor in providing services [ 45 , 46 ].…”

Section: Problem Descriptionmentioning

confidence: 99%

A Hybrid Genetic Algorithm for Nurse Scheduling Problem considering the Fatigue Factor

Amindoust

Asadpour

Shirmohammadi

2021

Journal of Healthcare Engineering

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Nowadays and due to the pandemic of COVID-19, nurses are working under the highest pressure benevolently all over the world. This urgent situation can cause more fatigue for nurses who are responsible for taking care of COVID-19 patients 24 hours a day. Therefore, nurse scheduling should be modified with respect to this new situation. The purpose of the present research is to propose a new mathematical model for Nurse Scheduling Problem (NSP) considering the fatigue factor. To solve the proposed model, a hybrid Genetic Algorithm (GA) has been developed to provide a nurse schedule for all three shifts of a day. To validate the proposed approach, a randomly generated problem has been solved. In addition, to show the applicability of the proposed approach in real situations, the model has been solved for a real case study, a department in one of the hospitals in Esfahan, Iran, where COVID-19 patients are hospitalized. Consequently, a nurse schedule for May has been provided applying the proposed model, and the results approve its superiority in comparison with the manual schedule that is currently used in the department. To the best of our knowledge, it is the first study in which the proposed model takes the fatigue of nurses into account and provides a schedule based on it.

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Improving patient-care services at an oncology clinic using a flexible and adaptive scheduling procedure

Cited by 16 publications

References 21 publications

Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration

Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling

A Hybrid Genetic Algorithm for Nurse Scheduling Problem considering the Fatigue Factor

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