A home healthcare routing-scheduling optimization model considering time-balancing and outsourcing

Home care services have a significant role in lowering healthcare expenditure. Supply chain management in home healthcare (HHC) ensures efficient delivery of medical supplies and equipment to patients' homes, improving overall quality of care and patient outcomes. This study proposes a routing and scheduling optimization model for HHC by prioritizing patients, developing an effective delivery strategy, and considering home care logistics and services. The model primarily concerns reducing logistics activities’ overall expenses while considering patients’ priorities. A bi-objective optimization model for a multi-period HHC problem is developed by prioritizing patients with urgent critical needs. The best-worst method (BWM) and technique for order of preference by similarity to ideal solution (TOPSIS) are used to prioritize patients using a linear programming metric (Lp-metric). The BWM and TOPSIS have been uniquely used in this study for routing and scheduling in HHC. Eventually, the applicability of the proposed method is demonstrated through a real-life case study with a series of numerical examples and sensitivity analysis. For instance, by analyzing privilege, we see patients are carefully matched with caregivers possessing advanced skills, leading to increased patient satisfaction. Based on assigned routes, caregivers prioritize patients with higher weight and emergency conditions at the start of each path, followed by patients with less urgent conditions. This ensures that patients with more severe conditions are serviced first.

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Publication Details

Journal
Supply Chain Analytics
Published
2024-08-13
DOI
https://doi.org/10.1016/j.sca.2024.100077
Citations
7
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
2.44
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article

A home healthcare routing-scheduling optimization model considering time-balancing and outsourcing

Amir Aghsami, Babak Moradi, Shabnam Rekabi, Farima Salamian et al.
7 citations
Supply Chain Analytics
Advanced Manufacturing and Logistics Optimization
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article

A home healthcare routing-scheduling optimization model considering time-balancing and outsourcing

Amir Aghsami, Babak Moradi, Shabnam Rekabi, Farima Salamian, Mahsa Zokaee, Niloofar Fadavi
article en
7 citations

Abstract

Home care services have a significant role in lowering healthcare expenditure. Supply chain management in home healthcare (HHC) ensures efficient delivery of medical supplies and equipment to patients' homes, improving overall quality of care and patient outcomes. This study proposes a routing and scheduling optimization model for HHC by prioritizing patients, developing an effective delivery strategy, and considering home care logistics and services. The model primarily concerns reducing logistics activities’ overall expenses while considering patients’ priorities. A bi-objective optimization model for a multi-period HHC problem is developed by prioritizing patients with urgent critical needs. The best-worst method (BWM) and technique for order of preference by similarity to ideal solution (TOPSIS) are used to prioritize patients using a linear programming metric (Lp-metric). The BWM and TOPSIS have been uniquely used in this study for routing and scheduling in HHC. Eventually, the applicability of the proposed method is demonstrated through a real-life case study with a series of numerical examples and sensitivity analysis. For instance, by analyzing privilege, we see patients are carefully matched with caregivers possessing advanced skills, leading to increased patient satisfaction. Based on assigned routes, caregivers prioritize patients with higher weight and emergency conditions at the start of each path, followed by patients with less urgent conditions. This ensures that patients with more severe conditions are serviced first.

Supply Chain AnalyticsVol. 7
Southern Methodist University (US), University of Toronto (CA), University of Tehran (IR), Canada Research Chairs (CA), University of Tabriz (IR), K. N. Toosi University of Technology (IR)
Openalex Percentile: Top 10%
Advanced Manufacturing and Logistics Optimization
2.44
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