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Nursing care flexibility in chemotherapy appointment scheduling

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Abstract

The flexibility level allowed in nursing care delivery and the uncertainty in infusion durations are important factors for chemotherapy scheduling. The nursing care delivery scheme employed in an outpatient chemotherapy clinic (OCC) determines the strictness of the patient-to-nurse assignment policies, while the estimation of infusion durations affects the trade-off between patient waiting time and nurse overtime. We study the problem of daily scheduling of patients, assignment of patients to nurses and chairs in the presence of uncertainty in infusion durations for an OCC that functions according to any of the commonly used nursing care delivery system representing fully, partially, and inflexible care systems. We develop a two-stage stochastic mixed-integer programming model minimizing expected weighted cost of patient waiting time and nurse overtime. We propose multiple variants of a scenario grouping-based decomposition algorithm to solve the model using data from a major university oncology hospital. We compare input-based, solution-based, and random scenario grouping methods within the decomposition algorithm. We obtain near-optimal schedules that are also significantly better than the schedules generated based on the policy used in the clinic. We analyze the impact of nursing care flexibility in order to determine whether a partial or fully flexible delivery system is necessary to adequately improve waiting time and overtime.

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References

  • Wilson BE, Jacob S, Yap ML, Ferlay J, Bray F, Barton MB (2019) Estimates of global chemotherapy demands and corresponding physician workforce requirements for 2018 and 2040: a population-based study. Lancet Oncol 20(6):769–780

    Article  Google Scholar 

  • Turkcan A, Zeng B, Lawley M (2012) Chemotherapy operations planning and scheduling. IIE Trans Healthc Syst Eng 2(1):31–49

    Article  Google Scholar 

  • Karakaya S, Gul S, Çelik M (2023) Stochastic scheduling of chemotherapy appointments considering patient acuity levels. Eur J Oper Res 305(2):902–916

    Article  MathSciNet  Google Scholar 

  • Liang B, Turkcan A (2016) Acuity-based nurse assignment and patient scheduling in oncology clinics. Health Care Manag Sci 19(3):207–226

    Article  Google Scholar 

  • Ireland A, DePalma J, Arneson L, Stark L, Williamson J (2004) The oncology nursing society ambulatory office nurse survey. Oncol Nurs Forum 31(6):147–156

    Article  Google Scholar 

  • Hooshangi-Tabrizi P, Contreras I, Bhuiyan N, Batist G (2020) Improving patient-care services at an oncology clinic using a flexible and adaptive scheduling procedure. Expert Syst Appl 150:113267

    Article  Google Scholar 

  • Demir NB, Gul S, Çelik M (2021) A stochastic programming approach for chemotherapy appointment scheduling. Naval Res Logist (NRL) 68(1):112–133

    Article  MathSciNet  Google Scholar 

  • Gupta D, Denton B (2008) Appointment scheduling in health care: challenges and opportunities. IIE Trans 40(9):800–819

    Article  Google Scholar 

  • Ahmadi-Javid A, Jalali Z, Klassen KJ (2017) Outpatient appointment systems in healthcare: a review of optimization studies. Eur J Oper Res 258(1):3–34

    Article  MathSciNet  Google Scholar 

  • Benzaid M, Lahrichi N, Rousseau L-M (2020) Chemotherapy appointment scheduling and daily outpatient-nurse assignment. Health Care Manag Sci 23:34–50

    Article  Google Scholar 

  • Hesaraki AF, Dellaert NP, de Kok T (2020) Integrating nurse assignment in outpatient chemotherapy appointment scheduling. OR Spectr 42:935–963

    Article  MathSciNet  Google Scholar 

  • Lyon G, Cataldo A, Angulo G, Rey PA, Sauré A (2022) A column generation approach to intraday scheduling of chemotherapy patients. Int J Prod Res. https://doi.org/10.1080/00207543.2022.2067505

    Article  Google Scholar 

  • Cataldo A, Sufan S, Lorca A, Andresen M, Sánchez C, Sauré A (2023) Multi-stage process for chemotherapy scheduling and effective capacity determination. Int Trans Oper Res 30(1):151–180

    Article  MathSciNet  Google Scholar 

  • Castaing J, Cohn A, Denton BT, Weizer A (2016) A stochastic programming approach to reduce patient wait times and overtime in an outpatient infusion center. IIE Trans Healthc Syst Eng 6(3):111–125

    Article  Google Scholar 

  • Mandelbaum A, Momcilovic P, Trichakis N, Kadish S, Leib R, Bunnell CA (2020) Data-driven appointment-scheduling under uncertainty: the case of an infusion unit in a cancer center. Manag Sci 66(1):243–270

    Article  Google Scholar 

  • Slocum RF, Jones HL, Fletcher MT, McConnell BM, Hodgson TJ, Taheri J, Wilson JR (2021) Improving chemotherapy infusion operations through the simulation of scheduling heuristics: a case study. Health Syst 10(3):163–178

    Article  Google Scholar 

  • Gul S (2021) Chemotherapy appointment scheduling under uncertainty by considering workload balance among nurses. Pamukkale Univ J Eng Sci 27(4):570–578

    Article  Google Scholar 

  • Alvarado M, Ntaimo L (2018) Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming. Health Care Manag Sci 21(1):87–104

    Article  Google Scholar 

  • González-Maestro A, Brozos-Vázquez E, Casas-Méndez B, López-López R, López-Rodríguez R, Reyes-Santias F (2022) Effective optimisation of the patient circuits of an oncology day hospital: mathematical programming models and case study. Mathematics 10(1):62

    Article  Google Scholar 

  • Crainic TG, Hewitt M, Rei W (2014) Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design. Comput Oper Res 43:90–99

    Article  MathSciNet  Google Scholar 

  • Escudero LF, Garin MA, Perez G, Unzueta A (2013) Scenario cluster decomposition of the Lagrangian dual in two-stage stochastic mixed 0–1 optimization. Comput Oper Res 40(1):362–377

    Article  MathSciNet  Google Scholar 

  • Gade D, Hackebeil G, Ryan SM, Watson J-P, Wets RJB, Woodruff DL (2016) Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs. Math Program Ser B 157:47–67

    Article  MathSciNet  Google Scholar 

  • Jiang X, Bai R, Wallace SW, Kendall G, Landa-Silva D (2021) Soft clustering-based scenario bundling for a progressive hedging heuristic in stochastic service network design. Comput Oper Res 128:105182

    Article  MathSciNet  Google Scholar 

  • Oliveira W, Sagastizabal C, Scheimberg S (2011) Inexact bundle methods for two-stage stochastic programming. SIAM J Optim 21(2):517–544

    Article  MathSciNet  Google Scholar 

  • Hewitt M, Ortmann J, Rei W (2022) Decision-based scenario clustering for decision-making under uncertainty. Ann Oper Res 315:747–771

    Article  MathSciNet  Google Scholar 

  • Keutchayan J, Ortmann J, Rei W (2022) Problem-driven scenario clustering in stochastic optimization. arXiv:2106.11717

  • Arthur D (2006) Vassilvitskii S k-means\(^{++}\): the advantages of careful seeding. Technical Report 2006-13, Stanford InfoLab

  • Lame G, Jouini O, Cardinal JS-L (2016) Outpatient chemotherapy planning: A literature review with insights from a case study. IIE Trans Healthcare Syst Eng 6(3):127–139

  • Hadid M, Elomri A, Mekkawy TE, Jouini O, Kerbache L, Hamad A (2022) Operations management of outpatient chemotherapy process: An optimization oriented comprehensive review. Oper Res Perspect 9:100214

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Authors and Affiliations

  1. Department of Operations and Information Management, Isenberg School of Management, University of Massachusetts Amherst, Amherst, MA, 01003, US

    Serhat Gul

  2. Department of Industrial Engineering, TED University, Ankara, 06420, Turkey

    Serhat Gul

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  1. Serhat Gul
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Correspondence to Serhat Gul.

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Gul, S. Nursing care flexibility in chemotherapy appointment scheduling. Flex Serv Manuf J (2023). https://doi.org/10.1007/s10696-023-09526-6

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  • DOI: https://doi.org/10.1007/s10696-023-09526-6

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