A local nonprofit delivering health care services to vulnerable populations was seeking to determine where best to consider expansion and/or relocation of existing services. To aid in the project, data in BDD was used extensively. The clinic’s own data was analyzed for where patients are sourced today, along with key demographic and psychographic information to determine the profile of the current patient population served. Then, data in BDD was utilized for several factors, including the percentage of population aged 18-64 below 100% Federal Poverty Level (FPL), percentage of population aged 18-64 who are uninsured, and three-year average rate of diabetes hospitalization per 10,000. These factors and others were cross-mapped to create geographic target zones for consideration.

The analysis also revealed populations that the clinic can better target because their current patient profile does not fully capture the demographics of the vulnerable populations most in need. An example is representation of females in their patient mix – they have an opportunity to serve more single, head-of-household females based on the data. So, data in BDD not only gave a road map (literally) of where to potentially locate services, but also which populations could be better served as they consider expansion.

This is an incredible tool that the community is so blessed to have access to!!