IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v23y2020i2d10.1007_s10729-019-09469-1.html
   My bibliography  Save this article

Quantitative thresholds based decision support approach for the home health care scheduling and routing problem

Author

Listed:
  • Jamal Abdul Nasir

    (City University of Hong Kong)

  • Chuangyin Dang

    (City University of Hong Kong)

Abstract

In the domain of Home Health Care (HHC), precise decisions regarding patient’s selection, staffing level, and scheduling of health care staff have a significant impact on the efficiency and effectiveness of the HHC system. However, decentralized planning, the absence of well defined decision rules, delayed decisions and lack of interactive tools typically lead towards low satisfaction level among all the stakeholders of the HHC system. In order to address these issues, we propose an integrated three phase decision support methodology for the HHC system. More specifically, the proposed methodology exploits the structure of the HHC problem and logistic regression based approaches to identify the decision rules for patient acceptance, staff hiring, and staff utilization. In the first phase, a mathematical model is constructed for the HHC scheduling and routing problem using Mixed-Integer Linear Programming (MILP). The mathematical model is solved with the MILP solver CPLEX and a Variable Neighbourhood Search (VNS) based method is used to find the heuristic solution for the HHC problem. The model considers the planning concerns related to compatibility, time restrictions, distance, and cost. In the second phase, Bender’s method and Receiver Operating Characteristic (ROC) curves are implemented to identify the thresholds based on the CPLEX and VNS solution. While the third phase creates a fresh solution for the HHC problem with a new data set and validates the thresholds predicted in the second phase. The effectiveness of these thresholds is evaluated by utilizing performance measures of the widely-used confusion matrix. The evaluation of the thresholds shows that the ROC curves based thresholds of the first two parameters achieved 67% to 71% accuracy against the two considered solution methods. While the Bender’s method based thresholds for the same parameters attained more than 70% accuracy in cases where probability value is small (p ≤ 0.5). The promising results indicate that the proposed methodology is applicable to define the decision rules for the HHC problem and beneficial to all the concerned stakeholders in making relevant decisions.

Suggested Citation

  • Jamal Abdul Nasir & Chuangyin Dang, 2020. "Quantitative thresholds based decision support approach for the home health care scheduling and routing problem," Health Care Management Science, Springer, vol. 23(2), pages 215-238, June.
  • Handle: RePEc:kap:hcarem:v:23:y:2020:i:2:d:10.1007_s10729-019-09469-1
    DOI: 10.1007/s10729-019-09469-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-019-09469-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10729-019-09469-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bräysy, Olli & Dullaert, Wout & Nakari, Pentti, 2009. "The potential of optimization in communal routing problems: case studies from Finland," Journal of Transport Geography, Elsevier, vol. 17(6), pages 484-490.
    2. Rasmussen, Matias Sevel & Justesen, Tor & Dohn, Anders & Larsen, Jesper, 2012. "The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies," European Journal of Operational Research, Elsevier, vol. 219(3), pages 598-610.
    3. Wright, P. Daniel & Mahar, Stephen, 2013. "Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction," Omega, Elsevier, vol. 41(6), pages 1042-1052.
    4. Carello, Giuliana & Lanzarone, Ettore, 2014. "A cardinality-constrained robust model for the assignment problem in Home Care services," European Journal of Operational Research, Elsevier, vol. 236(2), pages 748-762.
    5. Yufen Shao & Jonathan Bard & Ahmad Jarrah, 2012. "The therapist routing and scheduling problem," IISE Transactions, Taylor & Francis Journals, vol. 44(10), pages 868-893.
    6. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    7. Sachidanand V. Begur & David M. Miller & Jerry R. Weaver, 1997. "An Integrated Spatial DSS for Scheduling and Routing Home-Health-Care Nurses," Interfaces, INFORMS, vol. 27(4), pages 35-48, August.
    8. Semih Yalçındağ & Andrea Matta & Evren Şahin & J. George Shanthikumar, 2016. "The patient assignment problem in home health care: using a data-driven method to estimate the travel times of care givers," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 304-335, June.
    9. Nickel, Stefan & Schröder, Michael & Steeg, Jörg, 2012. "Mid-term and short-term planning support for home health care services," European Journal of Operational Research, Elsevier, vol. 219(3), pages 574-587.
    10. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    11. Salma Chahed & Eric Marcon & Evren Sahin & Dominique Feillet & Yves Dallery, 2009. "Exploring new operational research opportunities within the Home Care context: the chemotherapy at home," Health Care Management Science, Springer, vol. 12(2), pages 179-191, June.
    12. Eveborn, Patrik & Flisberg, Patrik & Ronnqvist, Mikael, 2006. "Laps Care--an operational system for staff planning of home care," European Journal of Operational Research, Elsevier, vol. 171(3), pages 962-976, June.
    13. Semih Yalçındag & Evren Sahin & Andrea Matta, 2016. "The patient assignment problem in home health care: using a data-driven method to estimate the travel times of care givers," Post-Print hal-01736728, HAL.
    14. Giulia Garavaglia & Emanuele Lettieri & Tommaso Agasisti & Silvano Lopez, 2011. "Efficiency and quality of care in nursing homes: an Italian case study," Health Care Management Science, Springer, vol. 14(1), pages 22-35, March.
    15. Dorota Mankowska & Frank Meisel & Christian Bierwirth, 2014. "The home health care routing and scheduling problem with interdependent services," Health Care Management Science, Springer, vol. 17(1), pages 15-30, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vahid Akbari & İhsan Sadati & F. Sibel Salman & Davood Shiri, 2023. "Minimizing total weighted latency in home healthcare routing and scheduling with patient prioritization," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(3), pages 807-852, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    2. Jamal Abdul Nasir & Chuangyin Dang, 2018. "Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    3. Nasir, Jamal Abdul & Kuo, Yong-Hong, 2024. "Stochastic home care transportation with dynamically prioritized patients: An integrated facility location, fleet sizing, and routing approach," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
    4. Semih Yalçındağ & Andrea Matta & Evren Şahin & J. George Shanthikumar, 2016. "The patient assignment problem in home health care: using a data-driven method to estimate the travel times of care givers," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 304-335, June.
    5. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.
    6. Gomes, Maria Isabel & Ramos, Tânia Rodrigues Pereira, 2019. "Modelling and (re-)planning periodic home social care services with loyalty and non-loyalty features," European Journal of Operational Research, Elsevier, vol. 277(1), pages 284-299.
    7. Pahlevani, Delaram & Abbasi, Babak & Hearne, John W. & Eberhard, Andrew, 2022. "A cluster-based algorithm for home health care planning: A case study in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    8. Biao Yuan & Zhibin Jiang, 2017. "Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    9. Gang Du & Luyao Zheng & Xiaoling Ouyang, 2019. "Real-time scheduling optimization considering the unexpected events in home health care," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 196-220, January.
    10. Christian Fikar & Patrick Hirsch, 2018. "Evaluation of trip and car sharing concepts for home health care services," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 78-97, June.
    11. de Aguiar, Ana Raquel Pena & Ramos, Tânia Rodrigues Pereira & Gomes, Maria Isabel, 2023. "Home care routing and scheduling problem with teams’ synchronization," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    12. Braekers, Kris & Hartl, Richard F. & Parragh, Sophie N. & Tricoire, Fabien, 2016. "A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience," European Journal of Operational Research, Elsevier, vol. 248(2), pages 428-443.
    13. Amir M. Fathollahi-Fard & Abbas Ahmadi & Behrooz Karimi, 2021. "Multi-Objective Optimization of Home Healthcare with Working-Time Balancing and Care Continuity," Sustainability, MDPI, vol. 13(22), pages 1-33, November.
    14. Gang Du & Xi Liang & Chuanwang Sun, 2017. "Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows," Sustainability, MDPI, vol. 9(2), pages 1-22, February.
    15. Paola Cappanera & Maria Grazia Scutellà, 2015. "Joint Assignment, Scheduling, and Routing Models to Home Care Optimization: A Pattern-Based Approach," Transportation Science, INFORMS, vol. 49(4), pages 830-852, November.
    16. Cappanera, Paola & Scutellà, Maria Grazia & Nervi, Federico & Galli, Laura, 2018. "Demand uncertainty in robust Home Care optimization," Omega, Elsevier, vol. 80(C), pages 95-110.
    17. Paola Cappanera & Maria Grazia Scutellà, 2022. "Addressing consistency and demand uncertainty in the Home Care planning problem," Flexible Services and Manufacturing Journal, Springer, vol. 34(1), pages 1-39, March.
    18. Jalel Euchi & Malek Masmoudi & Patrick Siarry, 2022. "Home health care routing and scheduling problems: a literature review," 4OR, Springer, vol. 20(3), pages 351-389, September.
    19. Maya Duque, P.A. & Castro, M. & Sörensen, K. & Goos, P., 2015. "Home care service planning. The case of Landelijke Thuiszorg," European Journal of Operational Research, Elsevier, vol. 243(1), pages 292-301.
    20. Klaus-Dieter Rest & Patrick Hirsch, 2016. "Daily scheduling of home health care services using time-dependent public transport," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 495-525, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:hcarem:v:23:y:2020:i:2:d:10.1007_s10729-019-09469-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.