A Simulation Model of the Effects of Tailored Prenatal Care Delivery on Care Access [A308

Abstract

INTRODUCTION: New national prenatal care delivery guidance, the Plan for Appropriate Tailored Healthcare in Pregnancy (PATH), recommends tailoring the prenatal visit number, with 8-9 visits for low-risk patients and 12-14 visits for high-risk patients. We used simulation to explore how tailored prenatal care recommendations affect care access. METHODS: To evaluate the operational effects of tailored recommendations compared to usual care, a discrete event simulation was developed in C++. This model simulates dynamic patient arrivals, heterogeneous patient classifications, tailored pathways, and patient flow through the system until the end of each patient's care pathway (e.g., delivery). Patients were assigned to medically low-risk (9 visit) and high-risk (12 visit) groups based on the presence or absence of any medical conditions. Metrics captured included patient delays, overbooked appointments, and utilization. Simulation parameters were derived from a 1-year–long historical data set from a single institution. The model was run for a 52-week horizon for 1,000 replications. This study of de-identified data was deemed exempt by the institutional review board. RESULTS: The majority of patients in the parent dataset were medically high risk (3,527/4,968; 71%). Transitioning to the new prenatal care delivery model reduced mean delay to appointment per patient by 1 week. The percentage of patients overbooked was reduced from 27% to 24%. The average percent capacity utilized by each clinic decreased from 74% to 71%. CONCLUSION: In this dataset with many high-risk patients, tailoring prenatal care to medical risk factors modestly improved access parameters. Tailoring prenatal care is operationally feasible and may facilitate more equitable distribution of services.