Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation.

Area of Science:

• Healthcare Operations Research
• Health Services Management
• Simulation Modeling

Background:

• Outpatient phlebotomy services face challenges in efficiency and patient wait times.
• Decentralized models can lead to suboptimal resource allocation and workforce utilization.

Purpose of the Study:

• To apply simulation modeling for reconfiguring an outpatient phlebotomy service.
• To improve service efficiency, reduce patient queuing time, and enhance workforce utilization.
• To support evidence-based decision-making for service configuration.

Main Methods:

• Modeled the phlebotomy service using an inhomogeneous Poisson process.
• Developed a discrete-event simulation model to evaluate decentralized vs. centralized models.
• Tested various workforce arrangements through scenario analysis.

Main Results:

• Empirical insights into the relationship between staffing and system performance were generated.
• A specific staffing scenario was identified as balancing performance and workforce scheduling.
• The implementation of a centralized phlebotomy service was successfully commissioned.

Conclusions:

• Simulation and analytics provide a robust method for operational planning in hospitals.
• Evidence-based scenario analysis facilitates optimal service configuration decisions.
• This approach is crucial for managing outpatient services and workforce investment.