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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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slide1

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

three times a week mapping the transportation of dialysis patients in the greater dayton area

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

purpose
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

research questions
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?
where are the patients
Where are the Patients?

Geocoded points by transit provider

where are the hotspots
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
accessibility to personal transport
Accessibility to Personal Transport

Areas with high percentages of households without a vehicle

accessibility to public transport
Accessibility to Public Transport

Density of Patients & Public Bus Routes

slide11

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
slide12

Nearest Center Results

  • 40% not going to nearest center
    • Weighted by GDRTA with 111 trips
slide18

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
slide19

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