An optimization-embedded simulation approach for quantifying the operational impacts of right-sizing prenatal care

Area of Science:

• Healthcare Operations Research
• Maternal Health Services
• Clinical Workflow Optimization

Background:

• The U.S. faces high maternal mortality rates despite significant spending on maternity care.
• Outdated, standardized prenatal care guidelines may contribute to suboptimal outcomes.
• A shift towards tailored appointment pathways is emerging to modernize prenatal care.

Purpose of the Study:

• To evaluate the operational impacts of implementing tailored prenatal care appointment pathways.
• To develop a simulation model for optimizing patient scheduling under new care paradigms.
• To minimize patient delays, rescheduling, and clinic overbooking.

Main Methods:

• A discrete-event simulation model was developed, incorporating patient heterogeneity.
• A mixed-integer linear programming model was embedded for weekly patient scheduling.
• The model was applied to a case study at a prenatal care clinic within an academic health center.

Main Results:

• Tailored care pathways were found to significantly reduce patient delays, rescheduling, and overbooking.
• The flexibility offered by tailored pathways can enhance clinic capacity and adaptability.
• Scheduling appointments individually, rather than by broader timeframes, minimized delays and overbooking.

Conclusions:

• Implementing tailored prenatal care pathways offers substantial operational benefits for clinics.
• Optimized scheduling strategies are crucial for maximizing the efficiency of new care models.
• This approach can lead to improved patient flow and potentially better maternal health outcomes.