The document reviews two case studies that use GIS to analyze spatial accessibility to healthcare facilities. The first case study examines healthcare access in Jeddah, Saudi Arabia by mapping facility locations and calculating catchment areas. The second assesses cardiac access in Australia by developing a Cardiac Access-Remoteness Index to measure travel times to different levels of cardiac services. Both studies demonstrate how GIS can help health planners evaluate current access levels and identify areas in need of additional services.

1. Assessment of Spatial
Accessibility To Healthcare
Facilities Using GIS
Applications
“A review of two case studies”
Mohammad A. A. Az-Zahrani
MAY 14, 2014

2. Outline
 Introduction
 Objectives
 Methodology
 Background
 Literature Review
 Case Study 1 (Saudi Arabia)
 Case Study 2 (Australia)
 Discussion
 Conclusion Mohammad Al-Zahrani 2

3. Introduction
 Increasing demand for healthcare services
world-wide.
 Many cases and diseases need quick medical
care interventions
 Inequitable access to healthcare has long been
recognized as a problem world-wide.
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4. Introduction
 Spatial accessibility to healthcare refers to the
ease with which residents of a given area can
reach medical services and facilities
 calculated by geographic information systems,
referred to as the GIS-based accessibility.
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5. Introduction
 Accessibility is tool in Health care planning.
 Influenced by many factors, including
 Availability (number and distribution) of health
services in the area (supply)
 Number and distribution of population living in that
location (demand)
 Geographical impedance between population and
health services (e.g. inefficient transportation)
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6. Objectives
 To review the available published literature that
focused on role of GIS in representing and
analyzing the accessibility issue in Healthcare
sector.
 To highlight 2 case studies (in Saudi Arabia and In
Australia) where the GIS technology used to
address the accessibility level.
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7. Methodology
 Literature review of articles about the GIS
use in healthcare accessibility to understand
how GIS is used in this regard.
 Review and compare two cases in order to
further explain accessibility using GIS
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8. Background
Application of GIS in healthcare includes the following
areas:
 determining geographic distribution of diseases;
 analyzing spatial and temporal trends;
 mapping populations at risk;
 assessing resource allocation;
 planning and targeting interventions; and
monitoring
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9. Literature Review
 A search of online sources in 2007 identified 621 journal
articles and book chapters reporting health-related
applications of GIS (Nykiforuk & Flaman, 2011).
 138 were access to health or health planning related.
 These studies were from a range of countries, both
developed and developing and included access to a range
of medical services.
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10. Literature Review
 A tenfold difference in the physician supply between
urban and rural populations (US). Rosenblatt and Lishner
(1991)
 Extremely low accessibility to general practitioners in
remote rural areas. Lovett et al. (2002)
 Shortage of general practitioners in Mid- western and
southern counties, but a surplus in northern and eastern
counties. Meade and Emch (2010)Mohammad Al-Zahrani 10

11. Literature Review
Accessibility Approaches
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12. (Murad, 2012) has used GIS application in viewing
accessibility of healthcare in Jeddah City, Saudi Arabia.

13. CASE 1 - Database
Location of health
centers (point feature)
Attributes (number
physicians and
number of dentist)
Road network (line
feature)
Attributes (length
and type).
City districts
coverage (polygon
dataset)
Attributes (district
name and area, and
size of population and
households)
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14. CASE 1
Figure 1: Health care centers by number of physicians (Murad, 2012)
(3)
Figure 2: Classification of Health centers based on No. of dentists
(Murad, 2012) (3)
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15. CASE 1
Population Density
of Jeddah Districts
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16. CASE 1
 Indicator 1 : distance - to - provider method
 Every health center should cover a catchment
area extending 2 km radius wide
 These areas are mainly situated north and east
of the city with some to the west.
 Existing health centers are serving larger
catchment area than the standard size
A. Accessibility
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17. Accessibility to
Healthcare
facilities in
Jeddah
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18. CASE 1
 Indicator 2 : service area for a hospital
 Travel time is calculated for roads and used for producing
a 15-min drive-time area.
 ArcGIS is used to select all parts of the city that fall within
the 15-min service area of the selected hospital.
 Helpful for hospital planners for the purpose of hospital
marketing and utilization.
 Results: Alzahra and Alnahda are the main demand
zones for this hospital.
A. Accessibility
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19. 15-min drive-
time service area
for a private
hospital
(Jeddah)
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20. CASE 1
Step 1
 create a point coverage showing location of all health centers and
then links diabetic data to this coverage.
Step 2
 use GIS classification methods for describing variations of diabetic
patients
The resulted distribution indicates that diabetes patients are
concentrated mainly at Al-Rabwah, Bani Malik and Al-Sabail districts.
B. Identifying health demand distribution
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21. Spatial
distribution of
diabetes
patients at
Jeddah city
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22. (Coffee, Neil et al, 2012) used GIS to develop an Index to
assess the accessibility issue for the cardiac patients and
cardiac health centers which are existing in Australia.

23. CASE 2
 The Cardiac Access-Remoteness Index of
Australia (Cardiac ARIA)
 GIS used to model population level, road
network accessibility to cardiac services
before and after a cardiac event
 20,387 population localities in Australia.
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24. CASE 2
 CVD is the leading cause of mortality in US.
 CVD is Australia’s biggest killer, 50,000 deaths
each year (34% of all deaths)
 Diabetics are two- to four-fold more likely to die of
CVD-related causes than non-diabetics.
 Factors for CVDs
 age, gender, blood pressure, diabetes, tobacco, alcohol, sugar, family
history, obesity, in-activity, air pollution
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25. CASE 2
 Remoteness - being distant geographically
 the ease of approach from one location to another location
 measured in terms of distance travelled, the cost of travel,
or the time taken
 Communities on the fringes of major cities (50-100 km
away), do not have sufficient accessibility to major health
facilities or cardiac services.
 For remote areas of Australia, access to services is limited
due to the vast distances between population centers and
lower population densities
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26. CASE 2
PHASE 3
Comparison between Cardiac ARIA and census-derived
local population characteristics.
PHASE 2
Data acquisition and GIS modeling
PHASE 1
definition of the scope of a cardiac event, and generation
of a master list of the necessary cardiac services
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27. CASE 2
• Five categories of medical facilities/
hospitals were defined.
• Based on decreasing levels of
access to cardiac services and
increasing remoteness
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28. CASE 2
Principal Referral Hospital with
Cardiac Catheter Laboratory;
Principal Referral Hospital without
Cardiac Catheter Laboratory
Large Hospital, Major city, Regional
Centre and Remote location.
Medium Hospital Major city, Regional
Centre and Remote location.
Other Hospital, Regional Centre and
Remote location
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29. CASE 2
Location Links Data Layers
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30. CASE 2
The numeric
index ranged from
1 (access to principle
referral center with
cardiac catheterization
service ≤ 1 hour)
to 8 (no ambulance
service, > 3 hours to
medical facility, air
transport required).
The alpha index
ranged from
A (all 4 services
available within 1
hour drive-time)
to E (no services
available within 1
hour).
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34. CASE 1 -result
 13.9 million (71%) Australians resided
within Cardiac ARIA 1A locations
(hospital with cardiac catheterization
laboratory and all aftercare within 1 hour)
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35. DISCUSSION - Comparison
Comparison Saudi Arabia (Murad, 2012) Australia (Coffee et al 2012)
Objective Create GIS application for Accessibility
to healthcare facilities
develop an index of geographic accessibility to
cardiac services
Study area Jeddah City, Saudi Arabia All Australia
Value Provides spatial decision support system
for health planners in Jeddah city
Create a novel, simple objective geographic
measure of accessibility to cardiac services
Software ArcGIS, and its geostatistical analyst
extension
Arc Map, version 9.3.1(ESRI, 2010; ESRI
Arcview, 2006)
Project Team Author and interviewee (managers in
Healthcare organization)
geographers and health professionals
Data size small Large and complex
Raster Cell
size
192.91m (for provider density); 214.65
(for population density) (14)
200m
Patient type Diabetic CVDs
Number of
Health centers
39 44 (only for category 1 hospitals with Cardiac
unit)
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36. DISCUSSION – Data Constraint
 Not all data was of sufficient quality to be used in
the modeling. Due to:
 differing management policies,
 incomplete coverage of national data,
 confidentiality,
 inconsistent classifications and
 resourcing constraints affecting supplying agencies
 "Of the 20 national datasets determined after
consensus of the expert panel, 9 were utilized in
the final model of the index"
 Vector-Raster Integration Issues (size)
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37. CONCLUSION
 In Saudi Arabia, big potential to widely adopt the use of GIS in
healthcare planning and management for greater service improvement
and expanded coverage with optimized cost and resources.
 GIS is important tool that can help health care facility planners and
managers better understand the healthcare needs using visualizations
and modeling
 data related to people density, locations of facilities, distances from
such facilities, types of health services provided within certain zones
and areas are essential ingredients.
 without the use of GIS it would not have been possible to quantify
variations in accessibility in the same level of detail
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38. CONCLUSION
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39. REFERENCES
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1. Murad, AbdulKader A., (2012), “Benchmarking the location of health centers at Jeddah
city: a GIS approach”, Benchmarking: An International Journal, Vol. 19 No. 1, 2012. pp.
93-108.
2. Burkey, Mark L.(2012) ”Decomposing geographic accessibility into component parts:
methods and an application to hospitals”, Ann Reg Sci 48:783–800
3. Buchmueller , Thomas C. et al (2006) “How far to the hospital? The effect of hospital
closures on access to care” Journal of Health Economics 25- 740–761
4. Graves, Ann (2009) “A model for assessment for potential geographical accessibility: A
Case for GIS”, Online Journal of Rural Nursing and Healthcare, Vol 9 No , pp 46-55.
5. S.S. Radiah Shariff, Noor Hasnah Moin, Mohd Omar (2007), “Location allocation
modeling for healthcare facility planning in Malaysia” Computers & Industrial
Engineering 62, 1000–1010.
6. Guagliardo, M., Ronico, C., Cheung, I., Chacko, E. and Josef, J. (2004), “Physician’s
accessibility: an urban case of pediatric providers”, Health Place, Vol. 10, pp. 273-83.
7. Coffee, Neil, et al (2012), “Measuring national accessibility to cardiac services using
geographic information systems”, Applied Geography, 34 445-455.
8. Murad, A. (2006), “Creating a GIS application for health services at Jeddah city”,
Computers in Biology & Medicine, Vol. 37, pp. 879-89.

40. Mohammad Al-Zahrani 40