Health surveys are irreplaceable sources of information for estimating population health. Direct estimates that rely only on survey data collected within areas of interest may not always be reliable at the local level. Demands for local health estimates are getting ever more granular, but expanding survey sample is costly. As an alternative, small area estimation methods can increase the utility and reliability of estimates by using statistical models to borrow strength from data that is not collected for the area of interest. Small area estimation methods can also incorporate other data sources such as administrative records, census data, and big data with survey data to increase the quality of estimates. This study uses the California Health Interview Survey—a continuous 20,000+ household sample health survey that can typically generate substate estimates at the county level. We will illustrate how small area estimation can serve as a tool for maximizing the survey’s utility by generating estimates at the subcounty level. We also discuss how surveys could be designed to facilitate future small area estimation to raise their value for local jurisdictions and communities.