Objective <p>This study investigates operational efficiency in public general hospitals using a system dynamics (SD) model, focusing on resource allocation, patient flow and policy interventions. It explores the interactions between human resources, financial subsidies and patient visitation rates and their impact on hospital performance.</p> Methods <p>An SD model was developed to simulate various scenarios, incorporating data on hospital capacity, staffing and financial inputs, along with patient flow dynamics. Key performance metrics, including bed occupancy rate (BOR), average length of stay (ALOS), average cost per visit and workload index, were analysed under different policy scenarios.</p> Results <p>Simulation of four policy scenarios revealed that increased fiscal subsidies (scenario 2) consistently improved operational efficiency by reducing ALOS, staff workload and cost per visit. In contrast, scenarios involving human resource cuts or rapid patient growth triggered adverse feedback loops that undermined performance.</p> Conclusions <p>The SD model effectively captures the dynamic interactions within hospital operations and enables assessment of policy interventions over time. Enhanced government funding contributes most positively to efficiency, while demand surges and resource reductions introduce system strain and performance trade-offs.</p>

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Implementing system dynamics in hospital services to improve operational efficiency: An empirical research study

  • Hongxin Huang,
  • Xiaojun Huang,
  • Zihan Zhang,
  • Hao Chen,
  • Wei Wei,
  • Wei Lu

摘要

Objective

This study investigates operational efficiency in public general hospitals using a system dynamics (SD) model, focusing on resource allocation, patient flow and policy interventions. It explores the interactions between human resources, financial subsidies and patient visitation rates and their impact on hospital performance.

Methods

An SD model was developed to simulate various scenarios, incorporating data on hospital capacity, staffing and financial inputs, along with patient flow dynamics. Key performance metrics, including bed occupancy rate (BOR), average length of stay (ALOS), average cost per visit and workload index, were analysed under different policy scenarios.

Results

Simulation of four policy scenarios revealed that increased fiscal subsidies (scenario 2) consistently improved operational efficiency by reducing ALOS, staff workload and cost per visit. In contrast, scenarios involving human resource cuts or rapid patient growth triggered adverse feedback loops that undermined performance.

Conclusions

The SD model effectively captures the dynamic interactions within hospital operations and enables assessment of policy interventions over time. Enhanced government funding contributes most positively to efficiency, while demand surges and resource reductions introduce system strain and performance trade-offs.