Hospital service areas (HSAs) are increasingly adopted as a basic analysis unit for health care studies. The popular Dartmouth HSAs were produced more than two decades ago, and the process was far from automated. This research uses a Huff-based model automated in a geographic information systems (GIS) environment to delineate HSAs. Based on the Florida State Inpatient Database (SID) in 2011, a best-fitting distance decay function is derived from the actual travel patterns of hospitalization and then fed into the Huff model to strengthen the model's theoretical foundation in individual spatial behavior. The HSAs derived from the Huff-based model are then compared to the traditional flow-based HSAs defined by the Dartmouth method and assessed in terms of self-containment and heterogeneity of internal socioeconomic structure and urbanicity. The Huff-based model requires fewer data and is easy to implement as an automated toolkit and thus has great potential for replication in other regions to define large-scale and consistent HSAs.