Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan

Hesaraki, Alireza F.; Dellaert, Nico; Kok, A.G. de

doi:10.1016/j.ejor.2018.11.028

Cited by 25 publications

(36 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some clinics encourage pre-infusion appointments, allowing the providers to review lab results 24-48 hours prior to a patient's chemotherapy infusion, thereby eliminating the uncertainty of those processes, but this is not practical for VA hospitals since many of their patients travel a great distance for treatment. Much of the reviewed literature focused exclusively on the infusion phase of outpatient chemotherapy clinics, which is a significant simplification because it eliminates the uncertainty, variability, and delays of the lab and pharmacy phases (Chabot & Fox, 2005;Delaney, Jalaludin, Moylan, & Barton, 2002;Hesaraki, Dellaert, & de Kok, 2019;Turkcan, Zeng, & Lawley, 2012).…”

Section: Chemotherapy Schedulingmentioning

confidence: 99%

Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study

et al. 2020

View full text Add to dashboard Cite

Over the last decade, chemotherapy treatments have dramatically shifted to outpatient services such that nearly 90% of all infusions are now administered outpatient. This shift has challenged oncology clinics to make chemotherapy treatment as widely available as possible while attempting to treat all patients within a fixed period of time. Historical data from a Veterans Affairs chemotherapy clinic in the United States and staff input informed a discrete event simulation model of the clinic. The case study examines the impact of altering the current schedule, where all patients arrive at 8:00 AM, to a schedule that assigns patients to two or three different appointment times based on the expected length of their chemotherapy infusion. The results identify multiple scheduling policies that could be easily implemented with the best solutions reducing both average patient waiting time and average nurse overtime requirements. ARTICLE HISTORY

show abstract

Section: Chemotherapy Schedulingmentioning

confidence: 99%

Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study

et al. 2020

View full text Add to dashboard Cite

show abstract

“…If the laboratory results are not satisfactory with respect to side effects or effectiveness, the oncologist postpones drug administration for a few days or continues the treatment with another regimen (protocol). Hesaraki et al (2019) 1 3…”

Section: Introductionmentioning

confidence: 99%

“…1 (setting up and monitoring) to optimize the drug administration schedule while taking the time requirements of patients, pharmacy, and oncologists into consideration. Thus, the three prior steps for each patient are scheduled based on the drug administration appointment (Hesaraki et al 2019). With a multi-objective formulation, we reach a trade-off among the interests of patients, nurses, and the clinic.…”

Section: Introductionmentioning

confidence: 99%

“…It starts with time requirements and appointment requests. For further descriptions of the chemotherapy process and brief literature reviews of scheduling outpatient chemotherapy appointments, we refer the reader to Turkcan et al (2012), Liang and Turkcan (2016), and Hesaraki et al (2019).…”

Section: Introductionmentioning

confidence: 99%

“…In a prior study (Hesaraki et al 2019), we propose a bicriterion mixed integer programming (MIP) model to generate appointment templates that can be used for the online scheduling of outpatient chemotherapy. The two criteria are flowtime and makespan, which pertain to having appointments started and ended as early as possible for the sake of patients and nurses, respectively.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Integrating nurse assignment in outpatient chemotherapy appointment scheduling

2020

Self Cite

View full text Add to dashboard Cite

In outpatient chemotherapy, nurses administer the drugs in two steps. In the first few minutes of each appointment, a nurse prepares the patient for infusion (drug administration). During the remainder of the appointment, the patient is monitored by nurses and if needed taken care of. One nurse must be assigned to prepare the patient and set up the infusion device. However, a nurse who is not busy setting up may simultaneously monitor up to a certain number of patients who are already receiving infusion. The prescribed infusion durations are significantly different among the patients on a day at a clinic. We formulate this problem as a multi-criterion mixed integer program. The appointments should be scheduled with start times close to patients’ ready times, balanced workload among nurses, few nurse changes during appointments, and few nurse full-time equivalent (FTE) assigned to the schedule of the day. As the number of nurse FTEs is an output of the model rather than a fixed input, the clinic can use the nursing capacity more efficiently, i.e., with less labor cost. We develop a 3-stage heuristic for finding criterion points with the minimum weighted average deferring time of appointments for the minimum feasible number of nurse FTEs or a desired value above that. By not constraining the number of chairs or beds, we can find solutions with better (dominating) criterion points. Drug preparation, oncologist visit, and the laboratory test can be scheduled based on the drug administration appointment start time. Thus, the drug administration resources are efficiently used with desirable performance in taking the interests and requirements of various stakeholders into consideration: patients, nurses, oncologists, pharmacy, and the clinic.

show abstract

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

Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan

Cited by 25 publications

References 35 publications

Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study

Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study

Integrating nurse assignment in outpatient chemotherapy appointment scheduling

A stochastic programming approach for chemotherapy appointment scheduling

Contact Info

Product

Resources

About