1. Modeling travel distance to health care using geographic information systems Anupam Goel, MD Wayne State University Detroit, MI (USA)

2. 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

3. Learning objectives Define GIS Recognize potential data sources for GIS projects Recognize some strengths and limitations of using GIS technology

4. Performance objectives Recognize variations in measuring geographical access Critically review an article using GIS

5. 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

6. Geographic Information Systems (GIS) overview (cont.) Can include spatial data from many sources Applications include: environmental modeling, government or military uses, and business forecasting

7. Software choices Available GIS programs This presentation uses ESRI software, namely ArcView 3.2a and Network Analyst 1.1b ESRI software ArcView 3.2a Network Analyst 1.1b

8. Methods to measure access Distance to closest facility Straight-line Driving distance Number of facilities within a given distance Travel across political boundaries

9. 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

10. Mammography facilities Mammography Facility Registry Subset of mammography facilities within Vermont and the surrounding counties Mobile mammography centers and Canadian centers not included

11. Estimating a woman’s location Eligible women within each Vermont ZIP code (Claritas, Inc.)Claritas, Inc. Assigned these women to the ZIP code population centroid (Geographic Data Technologies, Inc.)Geographic Data Technologies, Inc.

12. Estimating a woman’s location (cont.) X X X X X X X X X X X Residence Geographic centroid Population centroid G P G P

13. 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

14. Distance to closest facility Applied mathematics Graph theory Network optimization Dijkstra’s algorithm Dijkstra’s algorithm – a method to find the shortest path from a node to all other nodes connected by a network

15. 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

16. 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

17. 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)

18. Next directions New data sources Census 2000Census 2000, Utilization files New questions Utilization in other areas, targeting interventions New analytic approaches Adjusting for covariates, spatial statistics

19. 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