Measuring geographic access to health care: raster and network-based methods

Abstract

Background: Inequalities in geographic access to health care result from the configuration of facilities, population distribution, and the transportation infrastructure. In recent accessibility studies, the traditional distance measure (Euclidean) has been replaced with more plausible measures such as travel distance or time. Both network and raster-based methods are often utilized for estimating travel time in a Geographic Information System. Therefore, exploring the differences in the underlying data models and associated methods and their impact on geographic accessibility estimates is warranted.

Methods: We examine the assumptions present in population-based travel time models. Conceptual and practical differences between raster and network data models are reviewed, along with methodological implications for service area estimates. Our case study investigates Limited Access Areas defined by Michigan's Certificate of Need (CON) Program. Geographic accessibility is calculated by identifying the number of people residing more than 30 minutes from an acute care hospital. Both network and raster-based methods are implemented and their results are compared. We also examine sensitivity to changes in travel speed settings and population assignment.

Results: In both methods, the areas identified as having limited accessibility were similar in their location, configuration, and shape. However, the number of people identified as having limited accessibility varied substantially between methods. Over all permutations, the raster-based method identified more area and people with limited accessibility. The raster-based method was more sensitive to travel speed settings, while the network-based method was more sensitive to the specific population assignment method employed in Michigan.

Conclusions: Differences between the underlying data models help to explain the variation in results between raster and network-based methods. Considering that the choice of data model/method may substantially alter the outcomes of a geographic accessibility analysis, we advise researchers to use caution in model selection. For policy, we recommend that Michigan adopt the network-based method or reevaluate the travel speed assignment rule in the raster-based method. Additionally, we recommend that the state revisit the population assignment method.

Figure 1

A) Network data model and B) Cost example.

Figure 2

A) Raster data model and B) Cost example.

Figure 3

Conversion of vector road data to raster cells. The original roads (black lines on left) are converted to a cell-based representation with large cell sizes (middle), resulting in an overconnected travel grid. Smaller cells (right) improve the topological structure of the travel grid. However, the two roads are still erroneously connected in this scenario.

Figure 4

Hierarchical classification system for speed limits.

Figure 5

Travel time estimates from custom-built networks compared with travel time estimated from Google Maps.

Figure 6

Example of raster filter.

Figure 7

Service areas (and resulting underserved areas) produced by network-based method.

Figure 8

Underserved areas.

Figure 9

Example of the similarities and differences between network and raster-based underserved areas.

Figure 10

Limited Access Areas.

Figure 11

Limited Access Areas with block population assignment method.

Figure 12

Conversion of vector roads data to raster data format with slowest route rule.

Figure 13

Service area delineation in areas where no roads are present.