Appointment and patient scheduling in chemotherapy: a case study in Chilean hospitals

Ramos, Camila; Cataldo, Alejandro; Ferrer, Juan Carlos

doi:10.1007/s10479-018-3085-7

Cited by 10 publications

(8 citation statements)

References 35 publications

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“…Because they play such a significant role in hospitals, the research of queuing systems has often focused on the busy period and waiting time. A queuing system is typically defined as a patient entering a queue, being served at a service point by a server (doctor), and then exiting the row [ 44 ]. A stochastic process, a type of embedded Markov chain, governs the state-to-state transitions.…”

Section: Results and Analysismentioning

confidence: 99%

Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review

Ala

Chen

2022

Journal of Healthcare Engineering

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This paper provides a comprehensive review of Appointment Scheduling (AS) in healthcare service while we propose appointment scheduling problems and various applications and solution approaches in healthcare systems. For this purpose, more than 150 scientific papers are critically reviewed. The literature and the articles are categorized based on several problem specifications, i.e., the flow of patients, patient preferences, and random arrival time and service. Several methods have been proposed to shorten the patient waiting time resulting in the shortest idle times in healthcare centers. Among existing modeling such as simulation models, mathematical optimization techniques, Markov chain, and artificial intelligence are the most practical approaches to optimizing or improving patient satisfaction in healthcare centers. In this study, various criteria are selected for structuring the recent literature dealing with outpatient scheduling problems at the strategic, tactical, or operational levels. Based on the review papers, some new overviews, problem settings, and hybrid modeling approaches are highlighted.

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Section: Results and Analysismentioning

confidence: 99%

Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review

Ala

Chen

2022

Journal of Healthcare Engineering

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“…Ramos et al. (2020), on the other hand, minimize the amount of overtime use of each chair while Liang and Turkcan (2016) specify two objectives, one of which is to minimize patient waiting time and the other to minimize nurses overtime. Hahn‐Goldberg et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(2014) and Ramos et al. (2020) include drug preparation times among the decisions made by the model. More recently, Hesaraki et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The complexity of this problem grows constantly, mainly because demand is increasing faster than the resources available to meet it. The challenge is especially daunting when it comes to serving the needs of patients who require emergency services and critical care (Lara et al., 2016; Landa et al., 2018; González et al., 2019; Andresen et al., 2020; Marquinez et al., 2021), or high‐cost, high‐complexity treatments such as dialysis (Kandakoglu et al., 2020) or cancer therapy (Sauré et al., 2012; Ramos et al., 2020; Maschler and Raidl, 2020). Ensuring treatment is prompt and effective goes to the very heart of a health system's objectives.…”

Section: Introductionmentioning

confidence: 99%

“…The scheduling of chemotherapy treatments has to satisfy multiple objectives and thus constitutes a complex problem (Ramos et al., 2020). Such objectives include minimizing the number of days between the first appointment with an oncologist and the first chemotherapy infusion session, reducing patient intraday waiting times, balancing nurse workloads, maximizing chair occupancy, and minimizing overtime.…”

Section: Introductionmentioning

confidence: 99%

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Multi–stage process for chemotherapy scheduling and effective capacity determination

Cataldo

Sufan

Lorca

et al. 2022

Int Trans Operational Res

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A novel solution approach is developed for the scheduling of chemotherapy sessions at cancer treatment centers. The problem is divided into two subproblems determining the day (interday scheduling) and the time slots (intraday scheduling), respectively. The interday subproblem is solved by a model that allows for effective treatment center capacity choices while the intraday subproblem is addressed using two optimization models. New patient arrivals and treatment protocols specifying the latest starting date and session spacing are sources of uncertainty. Unlike other existing approaches, the proposed method incorporates the concept of effective treatment capacity which facilitates the interaction between the interday and intraday subproblems allowing them to be solved sequentially and iteratively to thus achieve much more resource-efficient solutions. A case study using real data from a Chilean cancer center to conduct comparative simulations of its manual scheduling methods and the proposed methodology found that the latter almost always performed better, often significantly so, on makespan, resource utilization, overtime, and patient diversion metrics.

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Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis

2020

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Appointment and patient scheduling in chemotherapy: a case study in Chilean hospitals

Cited by 10 publications

References 35 publications

Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review

Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review

Multi–stage process for chemotherapy scheduling and effective capacity determination

Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis

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