Optimizing Hospital On-Call Scheduling Across Multiple Sites: A Collaborative Metaheuristic Approach...20th World Congress on Medical and Health Informatics (MEDINFO), August 9-13, 2025, Taipei, Taiwan

Medical staff scheduling is a complex challenge with significant implications for patient care and staff well-being. This study presents an innovative approach that combines multiple optimization algorithms working collaboratively in a multi-agent system (MAS) to address shift allocation. By integra...

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Publicado en:Studies in Health Technology & Informatics Vol. 329; pp. 886 - 891
Autores principales: AJMI, Faiza, BEN OTHMAN, Sarah, RENARD, Jean-Marie, ZGAYA, Hayfa, HAMMADI, Slim
Formato: proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2025
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      pub: Sage Publications Inc.
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        atl: Optimizing Hospital On-Call Scheduling Across Multiple Sites: A Collaborative Metaheuristic Approach...20th World Congress on Medical and Health Informatics (MEDINFO), August 9-13, 2025, Taipei, Taiwan
      aug:
        au:
          AJMI, Faiza
          BEN OTHMAN, Sarah
          RENARD, Jean-Marie
          ZGAYA, Hayfa
          HAMMADI, Slim
        affil: ICL, Junia, Université Catholique de Lille, LITL, F-59000 Lille, France
      sug:
        subj:
          Personnel, Health Facility Psychosocial Factors
          Personnel Staffing and Scheduling
          Diffusion of Innovation
          Algorithms
          Collaboration
          Decision Support Systems, Management
          Congresses and Conferences Taiwan
          Taiwan
          Patient Care
          Occupational Health
          Psychological Well-Being
          Shiftwork
          Attitude of Health Personnel
          Workload
          Respect
          Interprofessional Relations
          Intraprofessional Relations
          Conceptual Framework
          Automation
          Emergency Service Administration
      ab: Medical staff scheduling is a complex challenge with significant implications for patient care and staff well-being. This study presents an innovative approach that combines multiple optimization algorithms working collaboratively in a multi-agent system (MAS) to address shift allocation. By integrating these algorithms, the method ensures fair distribution, optimizes staff preferences, and minimizes constraint violations, effectively balancing workload and respecting individual requests. Tested on both simulated and real-world data, the solution demonstrates enhanced scheduling efficiency and adaptability particularly using heuristics for managing multiple schedules.
      pubtype: Academic Journal
      doctype:
        proceedings
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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