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Office-based and home-care for older adults in primary care: A comparative analysis using the Nash bargaining solution

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  • Mendoza-Alonzo, Jennifer
  • Zayas-Castro, José
  • Charkhgard, Hadi

Abstract

Three care delivery settings are compared in this study: office-based care, home-care, and mixed-care, i.e., office-based care combined with home-care, in solo, small, medium, and large primary care practices. The objective of this paper is to identify which of these settings better achieves the secondary goals of the so-called quadruple aim, i.e., reducing costs, improving the patient experience, and improving the physician experience. A multi-objective integer programming formulation is developed to capture the elements of strategic health care planning. The formulation considers the minimization of four objective functions: the total cost of care workers, the total number of care workers, the total rejected demand and unsatisfied preferred care location, and the total panel size of the providers. Instead of computing the entire Pareto frontier, we used the Nash bargaining solution to determine a single Pareto optimal solution for the problem. The approach was tested using real world instances, which can be adjusted to any specific primary care practice. The numerical results show that none of the settings provides the smallest values in all objective functions. The choice of a setting for a primary care practice depends on the secondary goals that the practice desires to emphasize, and, in most cases, it is independent of the type of practice size. For the analyzed instances, a calculated overall score for each setting determined that, on average, the settings based on home-care strengthen the achievement of the secondary goals of the quadruple aim more so than in comparison to the office-based physician settings.

Suggested Citation

  • Mendoza-Alonzo, Jennifer & Zayas-Castro, José & Charkhgard, Hadi, 2020. "Office-based and home-care for older adults in primary care: A comparative analysis using the Nash bargaining solution," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
  • Handle: RePEc:eee:soceps:v:69:y:2020:i:c:s0038012118303203
    DOI: 10.1016/j.seps.2019.05.001
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    References listed on IDEAS

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    1. Roberto Serrano, 2005. "Fifty years of the Nash program, 1953-2003," Investigaciones Economicas, Fundación SEPI, vol. 29(2), pages 219-258, May.
    2. 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.
    3. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    4. Nash, John, 1953. "Two-Person Cooperative Games," Econometrica, Econometric Society, vol. 21(1), pages 128-140, April.
    5. Nash, John, 1950. "The Bargaining Problem," Econometrica, Econometric Society, vol. 18(2), pages 155-162, April.
    6. 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.
    7. Aharon Ben-Tal & Arkadi Nemirovski, 2001. "On Polyhedral Approximations of the Second-Order Cone," Mathematics of Operations Research, INFORMS, vol. 26(2), pages 193-205, May.
    8. Jennifer Perloff & Catherine M. DesRoches & Peter Buerhaus, "undated". "Comparing the Cost of Care Provided to Medicare Beneficiaries Assigned to Primary Care Nurse Practitioners and Physicians," Mathematica Policy Research Reports afadd8863f3c4d24afbea022d, Mathematica Policy Research.
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