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Visibility-based layout of a hospital unit – An optimization approach

Author

Listed:
  • Uttam Karki

    (University of Louisville)

  • Pratik J. Parikh

    (University of Louisville)

Abstract

A patient fall is one of the adverse events in an inpatient unit of a hospital that can lead to disability and/or mortality. The medical literature suggests that increased visibility of patients by unit nurses is essential to improve patient monitoring and, in turn, reduce falls. However, such research has been descriptive in nature and does not provide an understanding of the characteristics of an optimal inpatient unit layout from a visibility-standpoint. To fill this gap, we adopt an interdisciplinary approach that combines the human field of view with facility layout design approaches. Specifically, we propose a bi-objective optimization model that jointly determines the optimal (i) location of a nurse in a nursing station and (ii) orientation of a patient's bed in a room for a given layout. The two objectives are maximizing the total visibility of all patients across patient rooms and minimizing inequity in visibility among those patients. We consider three different layout types, L-shaped, I-shaped, and Radial; these shapes exhibit the section of an inpatient unit that a nurse oversees. To estimate visibility, we employ the ray casting algorithm to quantify the visible target in a room when viewed by the nurse from the nursing station. The algorithm considers nurses' horizontal visual field and their depth of vision. Owing to the difficulty in solving the bi-objective model, we also propose a Multi-Objective Particle Swarm Optimization (MOPSO) heuristic to find (near) optimal solutions. Our findings suggest that the Radial layout appears to outperform the other two layouts in terms of the visibility-based objectives. We found that with a Radial layout, there can be an improvement of up to 50% in equity measure compared to an I-shaped layout. Similar improvements were observed when compared to the L-shaped layout as well. Further, the position of the patient's bed plays a role in maximizing the visibility of the patient's room. Insights from our work will enable understanding and quantifying the relationship between a physical layout and the corresponding provider-to-patient visibility to reduce adverse events.

Suggested Citation

  • Uttam Karki & Pratik J. Parikh, 2024. "Visibility-based layout of a hospital unit – An optimization approach," Health Care Management Science, Springer, vol. 27(2), pages 188-207, June.
  • Handle: RePEc:kap:hcarem:v:27:y:2024:i:2:d:10.1007_s10729-024-09670-x
    DOI: 10.1007/s10729-024-09670-x
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    References listed on IDEAS

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    1. Farouq Halawa & Sreenath Chalil Madathil & Alice Gittler & Mohammad T. Khasawneh, 2020. "Advancing evidence-based healthcare facility design: a systematic literature review," Health Care Management Science, Springer, vol. 23(3), pages 453-480, September.
    2. Pablo Pérez-Gosende & Josefa Mula & Manuel Díaz-Madroñero, 2021. "Facility layout planning. An extended literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3777-3816, June.
    3. Burkey, M.L. & Bhadury, J. & Eiselt, H.A., 2012. "A location-based comparison of health care services in four U.S. states with efficiency and equity," Socio-Economic Planning Sciences, Elsevier, vol. 46(2), pages 157-163.
    4. H K Smith & P R Harper & C N Potts, 2013. "Bicriteria efficiency/equity hierarchical location models for public service application," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(4), pages 500-512, April.
    5. Mowrey, Corinne H. & Parikh, Pratik J. & Gue, Kevin R., 2018. "A model to optimize rack layout in a retail store," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1100-1112.
    6. Thitithep Sitthiyot & Kanyarat Holasut, 2020. "A simple method for measuring inequality," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    7. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
    8. Moslehi, Ghasem & Mahnam, Mehdi, 2011. "A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search," International Journal of Production Economics, Elsevier, vol. 129(1), pages 14-22, January.
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