Block-Group versus ZIP-Code Level Analysis in Ambulatory Network Planning

By Scott Stuecher, Vice President, Hammes Healthcare

As a health system considers its ambulatory network strategy numerous questions must be analyzed and answered. Fundamental among those questions is that of location. Site placement, whether a primary care clinic or a large multi-specialty center, is driven by numerous factors and data points. Specificity is key in comparing geographies as results can vary drastically without it.

Historically, hospitals and health systems have analyzed their service area and sub-service areas at a ZIP-code level. This has mainly been out of necessity, as most data sets that these organizations access, such as demographics and state utilization databases, provide ZIP-code level information. However, ZIP codes do not always contain homogeneous demographics, particularly in urban and suburban areas. When considering the location of retail-sensitive ambulatory care services, which are significantly impacted by travel times and distances, more specificity in a geographic analysis provides the best possible location for a site’s success.

For years, traditional retailers have examined markets at a block-group level. For these organizations, site selection has significant consequences. Distances as short as a quarter mile can determine if a new storefront is competitive and can draw customers without cannibalizing business from existing locations. Block groups, similar to ZIP codes, are census-defined boundaries. There are more than 240,000 block groups across the United States, compared to approximately 41,000 ZIP codes. Block groups are limited to a population of 300 to 3,000 individuals, while ZIP codes can range from populations of less than 100 to more than 100,000 individuals. Examining demographic characteristics at a more granular block-group level can reveal areas of market attractiveness that traditional ZIP-code analyses may aggregate out.

Figure 1 below demonstrates the varying levels of granularity that can be applied to a Midwestern metropolitan market when examined at a ZIP-code level versus a block-group level.

ZIP-Code vs Block-Group Level
Figure 1: ZIP-code boundaries (left) compared to block-group boundaries (right)

Similar to the demographic analysis, understanding a location’s trade area at a block-group level can allow healthcare organizations to select a site that best meets their strategic goals based on the patient population they intend to serve. Block-group analysis for a trade area can more clearly identify patient or population segments compared to large catchment areas of aggregated ZIP codes. Building a trade area at a block-group level can better account for natural or man-made travel barriers (rivers, expressways, etc.) that impact access or traffic patterns to the site. Additionally, as population health continues to be a priority for providers, being able to accurately determine and forecast the geographic coverage of an ambulatory network will be increasingly important.

Healthcare providers have access to tools, such as Hammes Precision™, that allow them to explore their market demographics at a block-group level and devise a location strategy with the best information possible. With thin margins and the rising cost of capital, hospitals and health systems need to ensure that their facility investments yield sufficient return. Unlike major retailers, some healthcare providers may acquire or develop a new facility only once every few years, further highlighting the need to “get it right” when those opportunities are pursued.

Scott Stuecher is a Vice President for Hammes Healthcare’s Advisory Services practice. Over the past 15 years, he has partnered with more than 100 organizations across the United States, including community and teaching hospitals, health systems, academic medical centers, post-acute care providers and physician enterprises. Scott brings considerable expertise in strategic and business planning, service line development, affiliation evaluation and planning, physician alignment and quantitative and qualitative analytics.