The Development of the Reproductive Healthcare Equity Algorithm (RHEA)

TL;DR

The paper introduces RHEA, an interactive optimization tool designed to help nonprofits efficiently allocate transportation resources for abortion access, aiming to reduce healthcare inequities among underserved women post-Roe v. Wade repeal.

Contribution

We developed RHEA, a web-based planning algorithm that optimizes resource allocation for abortion logistics, tailored to nonprofit needs and constraints.

Findings

RHEA effectively minimizes transportation costs and maximizes access.

The tool adapts to various logistical constraints and demand patterns.

Collaborations ensure practical relevance and usability.

Abstract

After the repeal of Roe vs. Wade in June 2022, women face long-distance travel across state lines to access abortion care. For women who also face socioeconomic hardship, travel for abortion care is a significant burden. To ease this burden, abortion access nonprofits are funding and/or supplying transportation to abortion clinics. However, due to the uneven distribution of demand and supply for abortions, these nonprofits do not have efficient logistical operations. As a result, low-income, underserved women may not have access to adequate reproductive healthcare, thus widening healthcare inequity gaps. Nonprofits may also risk not serving the needs of vulnerable women without access to adequate reproductive healthcare, and in doing so, waste resources, money, and volunteer hours. To address these challenges, we create an interactive, web-based planning tool, the Reproductive Healthcare Equity Algorithm (RHEA), to guide nonprofits in strategically allocating resources and serving demand. RHEA leverages an optimization model to determine the maximum flow and minimum transportation cost to route women across a network of counties and abortion clinics, subject to transportation supply, budget, and time constraints for one day of operations for a nonprofit. In doing so, we collaborate with abortion access nonprofits to cater our model design and interface development to their needs and considerations. Ultimately, we seek to optimize resource allocation for nonprofits providing abortion care logistics and improve abortion access for low-income, underserved women.