Allocation‐routing problem in a multi‐hospital home hospitalization system: the case of a healthcare provider in Portugal

Abstract Home hospitalization (HH) represents a paradigm shift in healthcare delivery, providing vital patient‐centered services that enhance care quality and significantly reduce the burden on conventional healthcare facilities. Given the complexity of HH systems, where specialized nurses and doctors allocate their time between inpatient and outpatient systems, efficiently managing their time and workload becomes critical. For this purpose, we develop the multi‐hospital home hospitalization allocation‐routing problem as a mixed‐integer linear programming formulation. We define three different objective functions: minimizing routing costs, workload balancing among nurses, and the minimization of employed doctors. The model is solved by optimizing each objective function individually and then analyzing the trade‐offs by combining the functions in pairs, generating a series of two‐objective Pareto frontiers as part of a comprehensive multi‐objective framework. The model is validated using benchmark instances derived from HH historical data. Through a single‐objective perspective, we provide an economic analysis that assesses the cost implications and the benefits of opening new HH units. Furthermore, the bi‐objective results are analyzed presenting Pareto frontiers to facilitate the provider's decision‐making process regarding the trade‐offs between different objectives. A technique for order of preference by similarity to ideal solution (TOPSIS) analysis is subsequently applied to identify the most promising solution according to varying objectives weights. Finally, useful managerial insights are developed to assess the impact of prioritizing one objective function over the other and the economi implications on different strategic options.

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Publication Details

Journal
International Transactions in Operational Research
Published
2025-03-20
DOI
https://doi.org/10.1111/itor.70025
Citations
1
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
1.24

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article

Allocation‐routing problem in a multi‐hospital home hospitalization system: the case of a healthcare provider in Portugal

Ana Paula Barbosa‐Póvoa, Maria Lopes, Valentina Bonomi, Renata Mansini et al.
1 citations
International Transactions in Operational Research
Vehicle Routing Optimization Methods
1.24
article

Allocation‐routing problem in a multi‐hospital home hospitalization system: the case of a healthcare provider in Portugal

Ana Paula Barbosa‐Póvoa, Maria Lopes, Valentina Bonomi, Renata Mansini, Daniel Santos
article en
1 citations

Abstract

Abstract Home hospitalization (HH) represents a paradigm shift in healthcare delivery, providing vital patient‐centered services that enhance care quality and significantly reduce the burden on conventional healthcare facilities. Given the complexity of HH systems, where specialized nurses and doctors allocate their time between inpatient and outpatient systems, efficiently managing their time and workload becomes critical. For this purpose, we develop the multi‐hospital home hospitalization allocation‐routing problem as a mixed‐integer linear programming formulation. We define three different objective functions: minimizing routing costs, workload balancing among nurses, and the minimization of employed doctors. The model is solved by optimizing each objective function individually and then analyzing the trade‐offs by combining the functions in pairs, generating a series of two‐objective Pareto frontiers as part of a comprehensive multi‐objective framework. The model is validated using benchmark instances derived from HH historical data. Through a single‐objective perspective, we provide an economic analysis that assesses the cost implications and the benefits of opening new HH units. Furthermore, the bi‐objective results are analyzed presenting Pareto frontiers to facilitate the provider's decision‐making process regarding the trade‐offs between different objectives. A technique for order of preference by similarity to ideal solution (TOPSIS) analysis is subsequently applied to identify the most promising solution according to varying objectives weights. Finally, useful managerial insights are developed to assess the impact of prioritizing one objective function over the other and the economi implications on different strategic options.

International Transactions in Operational Research
University of Lisbon (PT), Universidade Politécnica de Lisboa (PT), University of Brescia (IT)
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 21%
Vehicle Routing Optimization Methods
1.24
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