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A simple empirical inventory model for managing the processed corneal tissue equitably in hospitals with demand differentiation

This paper peruses one of the most challenging healthcare concerns related to human organ transplantation. In this regard, a medical system’s health-economic objectives are investigated to (1) achieve a desirable level of health equity in offering healthcare services to patients who are differentiat...

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Detalles Bibliográficos
Autores principales: Sohrabi, Mahnaz, Zandieh, Mostafa, Afshar-Nadjafi, Behrouz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529247/
http://dx.doi.org/10.1007/s40314-021-01663-8
Descripción
Sumario:This paper peruses one of the most challenging healthcare concerns related to human organ transplantation. In this regard, a medical system’s health-economic objectives are investigated to (1) achieve a desirable level of health equity in offering healthcare services to patients who are differentiated in terms of medical conditions, and (2) minimize total costs incurred across managing the inventory. This paper presents the first-ever operational research study to manage processed corneal tissue (PCT). Besides, hybrid demand-oriented policies have been proposed to equitably issue and assign specific inventories to demands with distinct medical urgent levels (ULs). In this regard, a practical multi-objective mixed-integer linear programming (MOMILP) model is proposed for a system with multiple products that can be substituted with each other according to medical priorities. A goal programming (GP) approach is utilized to find the optimum solution. The applicability of the model is validated through a real case study. Finally, several sensitivity analyses are conducted to examine the effect of critical parameters on the solutions to gain useful managerial insights. The results show that the proposed health-economic trade-off is well performed and can efficiently handle the real case.