Multi-Criteria Clinic Allocation in Massachusetts to Reduce Access to Healthcare Disparities

Rural populations in the United States experience challenges in accessing healthcare facilities in ambulatory setting. While ambulatory healthcare facility location decisions have been widely studied, existing studies rarely use rurality and access to transportation together to inform equitable allocation of new facilities. We developed a novel optimization model to determine how to allocate a set of new clinics in a region to maximize coverage at the census tract level while considering rurality, lack of access to a vehicle, and existing clinics. Coverage is measured by the weighted size of vulnerable populations at the census tract level located within a predetermined distance from a new clinic. Weighting allows prioritization of census tracts with a: i) higher number of households with no access to a vehicle, and ii) higher level of rurality. Rurality is represented by the Rural-Urban Commuting Area codes. We applied the optimization model to allocate new clinics in Western Massachusetts, which includes 198 census tracts and 824,464 residents as of 2020. We used data from multiple publicly available datasets, and conducted sensitivity analyses on the distance threshold to new clinics and number of new clinics. Key findings indicate that Western Massachusetts has high rurality and a low number of clinics per census tract, thus highlighting the need for more clinics in the area. The proposed model serves as a useful tool for decision makers to select equitable clinic locations by operationalizing rurality and proportion of population with no access to a vehicle.