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Health Care Management Science

, Volume 22, Issue 2, pp 376–390 | Cite as

Patient-centric design of long-term care networks

  • Paul IntrevadoEmail author
  • Vedat Verter
  • Lucie Tremblay
Article

Abstract

Long-term care networks may soon buckle under the weight of overwhelming demand. We present two dynamic, large-scale mixed-integer programs for long-term care network design that execute jointly strategic and tactical facility location, modular capacity acquisition, and patient-assignment decisions. The first model is an adaptive network-design model whose focus is more strategic in nature, whereas the second model focuses exclusively on the expansion of an existing long-term care network and incorporates additional tactical decisions such as patient backlogs. Working directly with the president of the Order of Québec Nurses—the provincial organization representing over 75,000 nurses—we incorporate facets such as assignment permanence, as well as develop and measure patient-centric quality-of-life proxies such as geographic mis-assignment and un-assigned patients, the latter of which is quantified via parametric optimization. Various network-design and patient-assignment policies are explored. We conclude that the use of home care as an alternative to long-term care facilities is cost prohibitive under specific conditions. Employing a bisection algorithm, we identify the implicit cost placed on keeping medically stable elderly patients in a hospital ward, concluding no cost savings are generated from such a policy. The model is analyzed and validated using empirical data from the long-term care network in Montréal, Canada.

Keywords

Long-term care Nursing homes Multi-period capacity planning Network design Mixed integer programming 

References

  1. 1.
    Avkiran NK , McCrystal A (2014) Intertemporal analysis of organizational productivity in residential aged care networks: scenario analyses for setting policy targets. Health Care Manag Sci 17:113–125CrossRefGoogle Scholar
  2. 2.
    Cardoso T, Oliveira M D, Barbosa-Povoa A, Nickel S (2012) Modeling the demand for long-term care services under uncertain information. Health Care Manag Sci 15(4):385–412CrossRefGoogle Scholar
  3. 3.
    Cardoso T, Oliveira MD, Barbosa-povoa A, Nickel S (2015) An integrated approach for planning a long-term care network with uncertainty, strategic policy and equity considerations. Eur J Oper Res 247(1):321–334CrossRefGoogle Scholar
  4. 4.
    Cardoso T, Oliveira M D, Barbosa-Povoa A, Nickel S (2016) Moving towards an equitable long-term care network: a multi-objective and multi-period planning approach. Omega 58:69–85CrossRefGoogle Scholar
  5. 5.
    Cinnamon J, Schuurman N, Crooks VA (2009) Assessing the suitability of host communities for secondary palliative care hubs: a location analysis model. Health Place 15(3):822–830CrossRefGoogle Scholar
  6. 6.
    Derfel A (2015) Quebec’s eldercare challenge: a crisis comes of age. http://montrealgazette.com/news/local-news/aging-well/quebecs-eldercare-challenge-a-crisis-comes-of-age
  7. 7.
    Fidelman C (2013) Fining hospitals for keeping elderly patients is tantamount to abuse, critics say. http://www.montrealgazette.com/health/Fining+hospitals+keeping+elderly+patientstantamount+abuse+critics/9148273/story.html
  8. 8.
    Greene VL, Ondrich J, Laditka S (1998) Can home care services achieve cost savings in long-term care for older people? J Gerontol Ser B Psychol Sci Soc Sci 53(4):S228–S238CrossRefGoogle Scholar
  9. 9.
    Hare W, Alimadad A, Dodd H, Ferguson R, Rutherford A (2009) A deterministic model of home and community care client counts in british columbia. Health Care Manag Sci 12:80–98CrossRefGoogle Scholar
  10. 10.
    Kim D-G, Kim Y-D (2010) A branch and bound algorithm for determining locations of long-term care facilities. Eur J Oper Res 206(1):168–177CrossRefGoogle Scholar
  11. 11.
    Lin F, Kong N, Lawley M (2012) Capacity planning for publicly funded community based long-term care services. In: Community-based operations research. Springer, pp 297–315Google Scholar
  12. 12.
    Melo M T, Nickel S, Saldanha da Gama F (2006) Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning. Comput Oper Res 33(1):181–208CrossRefGoogle Scholar
  13. 13.
    Patrick J (2011) Access to longer term care: The true cause of hospital congestion?. Prod Oper Manag 20 (3):347–358CrossRefGoogle Scholar
  14. 14.
    Shroff HE, Gulledge TR, Haynes KE, O’Neill MK (1998) Siting efficiency of long-term health care facilities. Socio Econ Plan Sci 32(1):25–43CrossRefGoogle Scholar
  15. 15.
    Stanimirovic Z, Maric M, Bozovic S, Stanojevic P (2012) An efficient evolutionary algorithm for locating long-term care facilities. Information Technology And Control 41(1):77–89CrossRefGoogle Scholar
  16. 16.
    Thanh PN, Bostel N, Péton O (2008) A dynamic model for facility location in the design of complex supply chains. Int J Prod Econ 113(2):678–693CrossRefGoogle Scholar
  17. 17.
    United Nations, Department of Economic and Social Affairs. Global Population Estimates by Age, 1950-2050. http://www.pewglobal.org, 2014
  18. 18.
    Zhang Y, Puterman ML, Nelson M, Atkins D (2012) A simulation optimization approach for long-term care capacity planning. Oper Res 60(2):249–261CrossRefGoogle Scholar
  19. 19.
    Zhang Y, Puterman ML (2013) Developing and adaptove policy for long-term care capacity planing. Health Care Manag Sci 16:271–279CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics & StatisticsUniversity of San FranciscoSan FranciscoUSA
  2. 2.Desautels Faculty of ManagementMcGill UniversityMontrealCanada
  3. 3.President of the Order of Nurses of QuébecQuébecCanada

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