A Simulation Model of the Effects of Tailored Prenatal Care Delivery on Care Access [ID: 1377136

Abstract

INTRODUCTION: The Michigan Plan for Appropriate Tailored Healthcare in pregnancy (PATH) recommends tailoring prenatal care delivery to patients’ risk factors for visit number (for low risk: 8–9 visits; for high-risk patients: 12–14 visits) and preferences for care modality (in-person only or hybrid with virtual visits). We used simulation to explore how tailored prenatal care recommendations affect care access. METHODS: A discrete event simulation was created in C++ to assess the operational effects of tailored recommendations in comparison to standard care. Patients enter the system and are divided into low-risk and high-risk categories based on medical conditions. The simulation models dynamic patient arrivals, varied patient classifications, tailored pathways, heterogeneous durations of total care, and patient flow until each patient's pathway ends (eg, childbirth). Metrics captured include patient delays, overbooked appointments, and unused capacity. The model was run with 1,000 replications during a 52-week period with a 10-year warm-up period to reach steady-state equilibrium within the simulation. The IRB designated this analysis of de-identified data exempt. RESULTS: Transitioning to the new prenatal care model reduced mean care delays per patient in all care modalities by 3.5 weeks for low-risk patients (9.79 weeks–6.37 weeks) and 0.4 weeks for high-risk patients (9.8 weeks–9.4 weeks). Tailoring care reduced the percentage of overbooked appointments by an average of 9.4% and the average unused capacity by 7.4%. CONCLUSION: Tailored prenatal care models including telemedicine result in improved operational efficiencies.