WIP 94 - Prenatal Health Care Equity and Affordability: Is Prenatal Care Really Accessible?

Poster Number: WIP 94
Publication Number: WIP 94.879

Background: Adequate prenatal care is crucial for improved neonatal outcomes, with a decreased risk of neurologic and developmental impairments. Studies indicate that prenatal care is associated with a net expected hospital cost saving of $1000 for women. However, the absence of upfront cost information for prenatal care can be a barrier to many, especially those from marginalized and underserved communities, when seeking timely medical assistance during pregnancy.

Objective: In this study, we estimate the cash price and out-of-pocket expenses for prenatal care across the three trimesters using hospital price transparency data and transparency-in-coverage data. We aim to highlight the varying costs of prenatal care, with the goal of bridging the information gap for those who are uninsured or have high-deductible insurance plans, emphasizing a commitment to equity in healthcare access.

Design/Methods: This healthcare economics analysis is exempt from Institutional Review Board approval as the study uses cost data reported by hospitals and health insurers under the Price Transparency Final Rule required by the Center for Medicare and Medicaid Services, and does not include any patient data. Based on the ICD-10 codes of each trimester (Z34.91, Z34.92, and Z34.93), we determine basic procedure codes such as CPT 81025 (Urine pregnancy) that are performed to evaluate the patient's health in each trimester. Based on the diverse economic and health backgrounds of mothers, we adjust for a wide range of maternal and birth factors, providing both conservative and liberal cost estimates. In the conservative approach, we use mandatory services that need to be performed for each patient encounter, while in the liberal approach, we include additional procedures that are performed in specific cases. We use Spearman rank correlation to compare cash prices to commercially negotiated rates and compare these rates with Medicare rates. The pre-processed cost data for procedures will be collected by Nov 2023. The analysis is conducted using Python and results are expected to be completed by Feb 2024.