Abstract

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.

Highlights

  • Cancer is the first cause of death in The Netherlands (CBS 2016) and the second cause of death in the European Union after circulatory system diseases

  • 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

  • We focus on appointment scheduling in contrast to capacity allocation (Schütz and Kolisch 2012), which is done in the online day planning stage of Fig. 3, where the appointment days are decided as requests arrive (e.g., Gocgun and Puterman 2014)

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Summary

Introduction

Cancer is the first cause of death in The Netherlands (CBS 2016) and the second cause of death in the European Union after circulatory system diseases. Our model explicitly assigns nurses to patients, for all staffing ranks, e.g., full time, part-time, and primary, who are affiliated with the clinic and available on an intended day. We develop a 3-stage heuristic to find trade-off solutions between workload imbalance among nurses and number of nurse changes for minimum deferring time of appointments with a chosen number of nurse FTEs in the schedule These criterion points can serve as feasible solutions for warm starting the search to find other criterion points that are on efficient frontiers

Problem and model formulation
Nurse assignment
Decision variables and the station assignment rule
Scheduling constraints
Scheduling objective criteria
Multi‐criterion mixed integer programming
Three‐stage heuristic
Numerical illustration
Generalizability of the model
Concluding remarks
Managerial implications
Findings
Limitations and future research
Full Text
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