ArticleBMC medical informatics and decision making2022
Resource management framework using simulation modeling and multi-objective optimization: a case study of a front-end department of a public hospital in Thailand.
Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Interpretable SHAP-based machine learning framework for patient satisfaction prediction: a case study in Thammasat University Hospital.BMC medical informatics and decision making · 2026Article
- Economic changes and public health resources associated with satisfaction toward the state health service system among older adults under the Universal Coverage Scheme across 77 provinces in Thailand, 2017-2024.International journal for equity in health · 2026Article
- A scenario-driven simulation approach to sustainable hospital resource management: aging society, pandemic preparedness and referral enhancement.BMC health services research · 2025Article
- Optimizing inpatient bed management in a rural community-based hospital: a quality improvement initiative.BMC health services research · 2023Article
- Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment.BMC medical informatics and decision making · 2022Article
- Innovation in physical education: The role of cognitive factors and self-efficacy.Frontiers in psychology · 2022Article
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Abstract
backgroundThe overcrowded patients, which cause the long waiting time in public hospitals, become significant problems that affect patient satisfaction toward the hospital. Particularly, the bottleneck usually happens at front-end departments (e.g., the triage and medical record department) as every patient is firstly required to visit these departments. The problem is mainly caused by ineffective resource management. In order to support decision making in the resource management at front-end departments, this paper proposes a framework using simulation and multi-objective optimization techniques considering both operating cost and patient satisfaction.
methodsTo develop the framework, first, the timestamp of patient arrival time at each station was collected at the triage and medical record department of Thammasat University Hospital in Thailand. A patient satisfaction assessment method was used to convert the time spend into a satisfaction score. Then, the simulation model was built from the current situation of the hospital and was applied scenario analyses for the model improvement. The models were verified and validated. The weighted max-min for fuzzy multi-objective optimization was done by minimizing the operating cost and maximizing the patient satisfaction score. The operating costs and patient satisfaction scores from various scenarios were statistically compared. Finally, a decision-making guideline was proposed to support suitable resource management at the front-end departments of the hospital.
resultThe three scenarios of the simulation model were built (i.e., a real situation, a one-stop service, and partially shared resources) and ensured to be verified and valid. The optimized results were compared and grouped into three situations which are (1) remain the same satisfaction score but decrease the cost (cost decreased by 2.8%) (2) remain the same satisfaction score but increase the cost (cost increased up to 80%) and (3) decrease the satisfaction score and decrease the cost (satisfaction decreased up to 82% and cost decreased up to 59%). According to the guideline, the situations 1 and 3 were recommended to use in the improvement and the situation 2 was rejected.
conclusionThis research demonstrates the resource management framework for the front-end department of the hospital. The experimental results imply that the framework can be used to support the decision making in resource management and used to reduce the risk of applying a non-improvement model in a real situation.
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