Capacity planning for maternal-fetal medicine using discrete event simulation

Area of Science:

• Maternal-fetal medicine
• Healthcare operations research
• Clinical informatics

Background:

• Maternal-fetal medicine is a rapidly expanding field necessitating interdisciplinary collaboration.
• Accurate capacity planning is essential for healthcare facilities to meet growing demand.
• Simulation modeling offers a method for estimating future capacity needs.

Purpose of the Study:

• To provide an evidence-based estimate of capacity needs for a maternal-fetal medicine clinic.
• To demonstrate the utility of simulation in healthcare capacity planning.
• To determine the impact of increased bed capacity on patient access.

Main Methods:

• A Discrete Event Simulation (DES) model of a specialized maternal-fetal medicine center was developed and validated.
• The validated DES model was used to assess inpatient bed capacity under increasing demand.
• The simulation determined the time until patient demand exceeded available bed capacity.

Main Results:

• The simulation model demonstrated high accuracy, with no significant deviation from historical data (p=0.889).
• Increasing inpatient bed capacity was shown to delay the time to balk, defined as the inability to admit patients.
• With current capacity, the mean time to balk is predicted at 276 days; adding three beds extends this to 762 days, and six beds to 1,335 days.

Conclusions:

• Ensuring adequate patient access is a critical patient safety concern.
• Strategic infrastructure investments require robust planning, supported by data.
• Computer-simulated analysis provides a valuable evidence base for clinical and administrative decision-making in complex healthcare settings.