Modeling travel distance to health care using geographic

information systems

Anupam Goel, MDWayne State University

Detroit, MI (USA)

Author’s background

Initially, a research project

• Determine the distance to the closest mammogram center for Vermont women ages 40 and older

• Applications to other public health settings

Learning objectives

• Define GIS

• Recognize potential data sources for GIS projects

• Recognize some strengths and limitations of using GIS technology

Performance objectives

• Recognize variations in measuring geographical access

• Critically review an article using GIS

Geographic Information Systems (GIS) overview

• A method to visualize, manipulate, analyze, and display spatial data, information linked to a specific place

• Additional description of GIS

Geographic Information Systems (GIS) overview (cont.)

• Can include spatial data from many sources

• Applications include: environmental modeling, government or military uses, and business forecasting

Software choices

• Available GIS programs

• This presentation uses ESRI software, namely ArcView 3.2a and Network Analyst 1.1b

Methods to measure access

• Distance to closest facility

Straight-line

Driving distance

• Number of facilities within a given distance

• Travel across political boundaries

Using this methodology for mammography utilization

• All relevant mammography facilities

• Assign women to representative points throughout the state

• Road atlas

• The shortest road distance from each group of women to a facility

Mammography facilities

• Mammography Facility Registry

• Subset of mammography facilities within Vermont and the surrounding counties

• Mobile mammography centers and Canadian centers not included

Estimating a woman’s location

• Eligible women within each Vermont ZIP code (Claritas, Inc.)

• Assigned these women to the ZIP code population centroid (Geographic Data Technologies, Inc.)

Estimating a woman’s location (cont.)

X

X

XX

X

XX

X

X

X

X

ResidenceGeographic centroidPopulation centroid

GP

G

P

Road network

• Census 2000 county road networks

• All counties within Vermont (n=14)

• The US counties surrounding Vermont (n=10)

• Canadian roads were not included

Distance to closest facility

Applied mathematics

Graph theory

Network optimization

Dijkstra’s algorithm – a method to find the shortest path from a node to all other nodes connected by a network

What we found

• Median distance to travel for a mammogram in Vermont was 11.2 km (range, 0.5-49.1 km)

• Women in the most populated ZIP codes traveled less for a mammogram than women in the least populated ZIP codes

Limitations

• Mammography from work instead of from home

• Mobile facilities not included

• No women surveyed for their actual driving distance

• Driving distance, not driving time

Implications of this project

Two ways to place new facilities:1) Reduce the longest distances

traveled (place new facilities in rural areas)

2) Reduce the average distance Vermont women travel (place new facilities in urban areas with less access to mammography)

Next directions

• New data sourcesCensus 2000, Utilization files

• New questionsUtilization in other areas, targeting interventions

• New analytic approachesAdjusting for covariates, spatial statistics

Acknowledgements• University of Vermont

Benjamin Littenberg, Richard G. Pinckney, Division of GIM

Austin Troy, SNR

Berta Geller and VBCSS

• National Cancer Institute funding

3 P30 CA22435-17S3 and 1 R03 CA101493-01