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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation

João Lopes1, Tiago Guimarães1, Júlio Duarte1

  • 1ALGORITMI Research Centre, University of Minho, Rua da Universidade, Braga, 4800-058, Portugal, 351 934373667.

JMIR Medical Informatics
|February 12, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) heuristic models optimize surgical scheduling, significantly reducing penalties and wait times. This AI-driven approach enhances hospital efficiency and patient-centered care.

Keywords:
artificial intelligencehealth caremetaheuristic modelmodel optimizationsurgery schedulingsurgery scheduling problem

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Area of Science:

  • Health Informatics
  • Operations Research
  • Artificial Intelligence

Background:

  • Healthcare systems face challenges in optimizing clinical and organizational processes.
  • The COVID-19 pandemic highlighted the need for patient-centered care and efficient decision-making.
  • Surgical scheduling is complex and prone to suboptimal decisions, impacting waiting lists and costs.

Purpose of the Study:

  • To propose a heuristic approach for optimizing surgical center management.
  • To collaborate with a leading Portuguese hospital (CHUdSA) to implement and test the approach.

Main Methods:

  • Analysis of CHUdSA's surgical scheduling process.
  • Application of artificial intelligence (AI)-based heuristic models, specifically hill climbing (HC) and simulated annealing (SA) algorithms.
  • Evaluation of the models' effectiveness in minimizing scheduling penalties.

Main Results:

  • AI heuristic models demonstrated significant improvements in scheduling efficiency.
  • The hill climbing (HC) algorithm scheduled 96.7% of surgeries with zero penalties in specific specialties.
  • The simulated annealing (SA) algorithm also improved scheduling rates and reduced penalties compared to manual methods.

Conclusions:

  • Integrating AI solutions into surgical scheduling increases efficiency and reduces costs.
  • AI-driven strategies can minimize patient wait times and maximize resource utilization.
  • These AI algorithms offer a transformative impact on adapting healthcare environments and enhancing surgical outcomes.