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Three Times a Week: Mapping the Transportation of Dialysis Patients Dayton, Ohio

Three Times a Week: Mapping the Transportation of Dialysis Patients Dayton, Ohio. Langdon Sanders GIS Technician City of Kettering, OH. Ambreen Hasan Research Analyst Lakeland Community College. 2013 Ohio GIS Conference September 11 - 13, 2013 | Columbus Marriott Northwest | Dublin, Ohio.

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Three Times a Week: Mapping the Transportation of Dialysis Patients Dayton, Ohio

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  1. Three Times a Week: Mapping the Transportation of Dialysis Patients Dayton, Ohio Langdon Sanders GIS Technician City of Kettering, OH AmbreenHasan Research Analyst Lakeland Community College 2013 Ohio GIS Conference September 11 - 13, 2013 | Columbus Marriott Northwest | Dublin, Ohio

  2. Three Times a Week: Mapping the Transportation of Dialysis Patients in the Greater Dayton Area Ambreen Hasan and Langdon Sanders Sponsored by Ohio GIS Conference, Sept. 13, 2013

  3. Purpose • Examine current transportation system for dialysis patients in Montgomery, Miami & Greene co. • Inform Transit, Medical, and Public communities • Identify Target Areas, Issues & Challenges Towards Improving Service, Reducing Cost

  4. Research Questions • Where are the patients? • “Hot Spots” and rideshare possibilities • How do they travel to dialysis? • Field Observation, Patient Survey • Are they going to the closest center?

  5. Direct Observation Findings

  6. Selected Survey Results

  7. Where are the Patients? Geocoded points by transit provider

  8. Where are the ‘hotspots’? Created a density surface using Spatial Analyst Notes: • We used kernel density • Pick a search radius • play with results • Cell size det. ‘smoothness’ • Lowest color empty

  9. Accessibility to Personal Transport Areas with high percentages of households without a vehicle

  10. Accessibility to Public Transport Density of Patients & Public Bus Routes

  11. Travel Efficiency: Closest Dialysis? • Geocoded PickUp & DropOff Addresses, dialysis centers • XY to Line tool • Org.  Dest. • Kept TRIP_ID • Distance Traveled • Nearest Center • Ratio of distance • Actual / Closest • Results • 2/ 2 = 1.000 • Or 2.5/ 2 = 1.25

  12. Nearest Center Results • 40% not going to nearest center • Weighted by GDRTA with 111 trips

  13. RideShare Analysis: Day & Provider

  14. RideShare Analysis: Day & Provider

  15. RideShare Analysis: Day & Provider

  16. RideShare Analysis: Day & Provider

  17. Implications for Decision Makers Where do we go from here?

  18. Limitations & Thoughts for Future • Only part of the system • Data from RTA, Anton’s, Greene CATS, MCPT and Fairborn Sen. Center. • Straight lines distance used instead of actual distance. • Easy, does not require network • Different date ranges of data. • Surveyed & Observed only two centers • both in Montgomery County

  19. Thank you. AmbreenHasan Research Analyst Lakeland Community College Ambreen.Hasan@wright.edu Langdon Sanders GIS Technician City of Kettering Langdon.Sanders@ketteringoh.org (937)296-3209

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