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<p>The healthcare sector has faced numerous and complex challenges, including a drastic reduction of public resources. However, the public healthcare sector must ensure equity and accessibility to care. Therefore, public decision makers are required to make decisions aimed at improving efficiency despite the constraints arising from resource scarcity. These decisions are typically intrinsically focused on human behavior, influenced by cognitive constraints, political pressures, and competing objectives. This work, through the lens of a real case study, aims to provide an analysis of work organization and healthcare workforce allocation in a region of Southern Italy characterized by a high risk of exclusion from healthcare services. The paper proposes a new approach that integrates the AHPSort II sorting method and a resource optimization model that not only classifies medical-health professions based on their strategic priorities, but also identifies professions that represent optimal solutions given the availability of limited resources such as space, time, and budget. The results show that the highest-ranked professions as follows: psychologist (0.168), general practitioner (0.167), dietitian (0.165), breast specialist (0.164), and psychotherapist (0.156). In the baseline scenario, with a budget of c 300,000, the model selects 29 medical health professions, achieving an overall priority of 3.78 and 14,690 annual visits, and an estimated profit of the baseline scenario, with a budget 165,761. The application results provide policy makers and healthcare organization managers with the replicable and integrated Multi-Criteria Decision Making (MCDM) and optimization model grounded in decision sciences to support public decisions on human resources management (HRM), with the aim of systematically prioritizing healthcare workers.</p>

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Strategic decision-making and personnel planning in the healthcare sector: an integrated AHPSort II and resource optimization approach

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Gerarda Fattoruso,
  • Walter Vesperi,
  • Antonio Violi

摘要

The healthcare sector has faced numerous and complex challenges, including a drastic reduction of public resources. However, the public healthcare sector must ensure equity and accessibility to care. Therefore, public decision makers are required to make decisions aimed at improving efficiency despite the constraints arising from resource scarcity. These decisions are typically intrinsically focused on human behavior, influenced by cognitive constraints, political pressures, and competing objectives. This work, through the lens of a real case study, aims to provide an analysis of work organization and healthcare workforce allocation in a region of Southern Italy characterized by a high risk of exclusion from healthcare services. The paper proposes a new approach that integrates the AHPSort II sorting method and a resource optimization model that not only classifies medical-health professions based on their strategic priorities, but also identifies professions that represent optimal solutions given the availability of limited resources such as space, time, and budget. The results show that the highest-ranked professions as follows: psychologist (0.168), general practitioner (0.167), dietitian (0.165), breast specialist (0.164), and psychotherapist (0.156). In the baseline scenario, with a budget of c 300,000, the model selects 29 medical health professions, achieving an overall priority of 3.78 and 14,690 annual visits, and an estimated profit of the baseline scenario, with a budget 165,761. The application results provide policy makers and healthcare organization managers with the replicable and integrated Multi-Criteria Decision Making (MCDM) and optimization model grounded in decision sciences to support public decisions on human resources management (HRM), with the aim of systematically prioritizing healthcare workers.