Related Experiment Video
Updated: May 26, 2026

Clinical Application of Phase Angle and BIVA Z-Score Analyses in Patients Admitted to an Emergency Department with Acute Heart Failure
Published on: June 30, 2023
Estimating proximity to care: are straight line and zipcode centroid distances acceptable proxy measures?
Robin L Bliss1, Jeffrey N Katz, Elizabeth A Wright
1Department of Orthopedic Surgery, Orthopedic and Arthritis Center for Outcomes Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. rbliss@partners.org
Background:
Spatial accessibility of healthcare may be measured by proximity of patient residence to health services, typically in driving distance or driving time. Precise driving distances and times are rarely available. Although straight line distances between zipcode centroids and between precise address locations are used as proxy measures for distance to care, the accuracy of these measures has received little study.
Methods:
Among a cohort of Medicare beneficiaries, actual driving distances and times between patient residence and clinic were obtained from commercial software (MapQuest). We used a split-sample design to build and validate linear regression models that predict actual driving distances and times from estimated distances between zipcode centroids and between precise residential and hospital locations, adjusting for urban/suburban/rural residential status.
Results:
On average, predicted driving distances and times were larger than actual values. Zipcode centroid distances alone predicted longer driving distances than observed values: rural +19% (3.2 miles), suburban +23% (3.7 miles), and urban +27% (2.0 miles). Predicted time was 36% (9.4 min) longer in rural, 32% (6.8 min) longer in suburban, and 38% (4.7 min) longer in urban areas than observed values. Including urban/suburban/rural categorization of residence improved the accuracy of predicted driving distance and time for suburban and urban areas but diminished accuracy for rural areas. Similar trends were observed for distance estimates from precise locations.
Conclusions:
Distances between zipcode centroids and precise residential/hospital locations provide reasonable estimates of driving distance and time for epidemiologic research. Estimates are improved for suburban and urban residences when data are augmented by urban categorization.
Related Concept Videos
Centroid of a Body: Problem Solving
The x-coordinates and y-coordinates of each element's...
The Distance Formula
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Centroid of a Body
For a homogeneous body with constant density, the centroid can usually be found using equations representing a balance of the moments of the body's volume. If the...
Coordinates and Map Projections
Design Example: Measuring Distance Between Two Points with Obstructions