An Agent-Based Simulation Framework for Clinical Management Integrating Fuzzy Logic-Based Patient Satisfaction Evaluation
Abstract
Efficient clinical management relies on coordinated operational workflows and reliable mechanisms for assessing patient experience. This study proposes an agent-based simulation framework for clinical management that integrates a fuzzy logic-based Patient Satisfaction Evaluation Agent (PSEA) within a multi-agent system composed of twelve specialized agents. The framework was implemented using the Mesa simulation platform and evaluated through simulation-based experiments involving 100 patients over 100 simulated time steps. Prior to its integration into the multi-agent system, the fuzzy satisfaction model embedded within the PSEA was independently designed and empirically validated using real survey data collected from 80 patients. The satisfaction scores produced by the fuzzy inference system showed strong agreement with patient-reported evaluations, achieving a correlation coefficient of 0.76 and a mean absolute error of 1.12. At the system level, simulation-derived indicators reveal a balance between adaptive coordination and operational stability. The multi-agent system performed an average of 3.68 ± 1.79 resource reallocation decisions per time step, while 12 out of 100 simulated time steps involved no reallocation, reflecting the emergence of stable operational phases.Overall, the results demonstrate that combining agent-based simulation with a pre-validated fuzzy satisfaction assessment provides a coherent and interpretable framework for supporting coordinated and patient-centered clinical management. Future work will focus on interoperability through standards such as HL7 and FHIR.References
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