modeling travel distance to health care using geographic information systems anupam goel, md wayne...
TRANSCRIPT
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Modeling travel distance to health care using geographic
information systems
Anupam Goel, MDWayne State University
Detroit, MI (USA)
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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
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Learning objectives
• Define GIS
• Recognize potential data sources for GIS projects
• Recognize some strengths and limitations of using GIS technology
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Performance objectives
• Recognize variations in measuring geographical access
• Critically review an article using GIS
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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
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Geographic Information Systems (GIS) overview (cont.)
• Can include spatial data from many sources
• Applications include: environmental modeling, government or military uses, and business forecasting
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Software choices
• Available GIS programs
• This presentation uses ESRI software, namely ArcView 3.2a and Network Analyst 1.1b
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Methods to measure access
• Distance to closest facility
Straight-line
Driving distance
• Number of facilities within a given distance
• Travel across political boundaries
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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
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Mammography facilities
• Mammography Facility Registry
• Subset of mammography facilities within Vermont and the surrounding counties
• Mobile mammography centers and Canadian centers not included
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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.)
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Estimating a woman’s location (cont.)
X
X
XX
X
XX
X
X
X
X
ResidenceGeographic centroidPopulation centroid
GP
G
P
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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
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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
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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
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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
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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)
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Next directions
• New data sourcesCensus 2000, Utilization files
• New questionsUtilization in other areas, targeting interventions
• New analytic approachesAdjusting for covariates, spatial statistics
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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