#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Spatial accessibility Study
1. A study of spatial accessibility to health
facilities for elderly people in metro Atlanta
usingacategoricalmulti-stepfloatingcatchmentareamethod
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Presenter:
Zhaoying Wei
Committee Member:
Xiaobai Yao(Chair)
Lan Mu
Sara Wagner
2. Outline
• Introduction
• Research question
• Literature Review on Accessibility
• Research Objectives
• Research Design
• Method
• Case study
• Results
• Limitation 2
3. Introduction
Elderly population
• A defining global issue: population ageing
• Concerns have emerged in the area of elderly health care
• 65 years and over: (2010 Census)
US 40,267,984 13% GA 1,032,035 10.7%
• Limited regenerative abilities , suffer mobility, health and
disability problems
• Placing a strain on government finances and health care facilities
• eligible for Medicare regardless of income and assets
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4. Introduction
• Medicare is the federal health insurance program for people who
are 65 or older, some disabled individuals under the age of 65, as
well as patients with end-stage renal (kidney) disease.
• Not covered (the official US government site for Medicare)
Non-skilled personal care
Routine dental or eye care
Dentures
Cosmetic surgery
Acupuncture
Hearing aids and the exams for fitting them
Routine foot care
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Medicare
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5. 1. What is an appropriate
method of measuring
accessibility to health facilities
for people who are eligible for
Medicare?
2. What is the current
situation of accessibility to
health facilities for people
who are eligible for Medicare
in Atlanta?
Research question
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6. Review on accessibility
What is accessibility?
• Accessibility: the relative ease by which the locations of activities,
such as work, shopping and health care, can be reached from a
given location (BTS 1997)
• Access to health facility in a given location : the measurement of
opportunities available to that health facility within certain distance
or travel time (Aday and Andersen 1974)
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7. classification
• Spatial Access: varieties across space due to the uneven
distribution of providers and consumers (spatial factors)
• Nonspatial Access: varieties among population groups because of
their different socioeconomic and demographic characteristics
(nonspatial factors)
• Focus on the method for measuring spatial accessibility to health
care facilities
• not consider race and income disparity due to data unavailability
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Review on accessibility
8. Current Methods
Pros
• Catchment Area: distance impedance
• Sum of facility to population ratio:
• Selection Weight
competition within one type of health facility
Two-step
floating catchment
area(2000)
Enhanced two-step
floating catchment
area(2009)
Three-step
floating catchment
area(2012)
★
★
Demand
upplyS
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Review on accessibility
9. Current Methods
Cons
• the catchment size could be more flexible
• only consider competition within the same group
Categorical multi-steps floating catchment area
diverse catchment sizes (step 1-4)
competition ratio to involve competition from other groups (step 4)
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Review on accessibility
10. Research Objectives
1. Propose a categorical multi-
step floating catchment area
(CMSFCA)method
2. Conduct a case study for
people who are 65 and over in
metropolitan Atlanta MSA.
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What’s an
appropriate
method?
What’s the
current
situation?
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12. Method
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Categorical multistep floating catchment area method
Various Catchment Sizes
• Step 1: selection weight
• Step 2: facility to population ratio
• Step 3: general accessibility to facilities
• Step 4: categorical accessibility
NEW STEP
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Python & Network Analyst
13. Health facility type Catchment
Size (min)
Distance impedance
coefficient β
Offices of Physicians 60 0.11
General Medical and
Surgical Hospitals
90 0.08
Homes for the elderly 120 0.05
Nursing care facility 120 0.05
Method
Step 1——Determination on The Likelihood of Selecting Health
Facility at Population Locations
★
★ census tract centroid
Health facility
dij : real travel time
β : distance friction
parameter
Selection Weight
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★ ★
★★
Competition within group
negative exponential function
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14. Method
Step 2——Obtaining The Ratio of Medical Capacity of Health
Facilities to Demand of Elderly Population at Health Facility
Locations
★★
★
★
★
★
★
★
★ census tract centroid
Health facility
medical capacity–
employee number
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Supply/selection-weighted Demand
dij : real travel time
β : distance friction
parameter
Selection Weight
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15. Method
Step 3——The General Spatial Accessibility Without Including
Competitions Between Groups
★
★ census tract centroid
Health facility
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dij : real travel time
β : distance friction
parameter
Sum of selection-weighted facility to population ratio
Selection Weight
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16. Method
Step 4——The Categorical Spatial Accessibility Including
Competitions Between Groups
• Diverse subgroups usually compete with each other for
opportunities：e.g. hospital vs offices of physician
nursing care facilities vs homes for the elderly
• Assumption: no competition between acute care services and long
term care services
• Preference score: impact choices of visiting health facilities
e.g. people’s knowledge of health facility; the quality of service provision;
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Competition ability between groups
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17. Method
Step 4——The Categorical Spatial Accessibility Including
Competitions Between Groups
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Competition ability between groups
PR=1
dij : real travel time
β : distance friction
parameter
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18. Case study
Study area
• Atlanta metropolitan
statistical area (MSA)
• 28 counties, 946 census tracts
• Total people: 5,268,860
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19. Case study
Demand Data: elderly population
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Demographic Data
• Georgia Census 2010
Summary File 1
• Elderly population(>=65):
471,753 , 9%
Corresponding geographic
boundaries
• 2010 Census TIGER/Line
dataset
Mobility problem
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20. Case study
Supply Data: Health Facilities for elderly people
Health facility points
• extracted from 2008 Business point from MapInfo
• North American Industry Classification Code (NAICS) 2010
edition
• Facility capacity : actual number of employees
NAICS Code Label Number
621111 Office of physicians (except
mental health specialist)
234
622110 general medical and surgical
hospitals
5414
623312 home for the elderly 388
623110 nursing care facilities 742
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21. Case study
Supply Data: Health Facilities for elderly people
Health facility points
• Offices of Physicians:
data clearing
(manual editing)
• 4336 remained (80%)
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23. Case study
Measuring travel distance
Distance parameter : travel time
• road network: 2005
• Diverse catchment sizes:
Offices of physicians: 60 min
Hospitals: 90 min
Homes for the elderly and nursing care
(long term): 120 min
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24. Measuring travel distance
Case study
• Origin-Destination Cost Matrix
•Total_Cost：
travel time (min) between
origin and destination pairs
Hospitals elderly population
Offices of physicians
Nursing care facilities
Homes for the elderly 24
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29. Limitation
• appropriate function for the distance decay weights, beta
• suitable catchment size
• use employee number as medical capacity
• overlap of hospitals and physicians
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as population ageing has grown into a “defining global issue”, concerns have emerged regarding policy interventions appropriate for older people, especially in the area of elderly health care.
the advantage of being an elderly people
Help with activities of daily living like bathing, dressing, eating
Medicare doesn’t pay for this kind of care if this is the only kind of care you need
Elderly population don’t need to pay for other kinds of care except these kinds of care
We also need to exclude these kinds of care in our study.
Can be generally divided into two types based on different influential factors
Census tract level
The evolvement of how
Build rings around target point, each represents one threshold travel time , only consider distance impedance effect on points within the rings
Sum of ratio, measure accessibility to health facility at each population site
Different preference when make decision, competition among one group
First 3 are modified based on 3SFCA
The entire method is implemented in stand-alone python scripts combining the network analyst extension in ArcGIS
logical assumption， population’s healthcare demand for a medical site is influenced by other nearby medical site.
Likelihood is represented by selection weight
At each census tract, build catchment area, assign weight based on negative exponential function, proportion of assigned weight at one health facility among the sum of assigned weight at all health facilities
The value of distance impedance coefficient beta for offices of physicians 0.11 is from another model in Minnesota, which is calculated based on the real data. Curve fitted well with the real data (percent of trip) due to the lack of sample data in out study area，utilize the value from that particular model ; sensitivity to distance
Wr is the impedance of the rth sub-zone Dr, Gkj is the selection weight between j and population site k
Sum of weighted supply to demand ratio
Competition ability for one type, sum of competition ability for all types
sum of the employee number weighted by distance, multiplying the preference score of that type ,
Defined, north GA
There are not many elderly people residing in the center of metropolitan area. Conversely, they most live in the peripheral area.
Mobility problem: the children are responsible for taking elderly people to health facilities, not suffer mobility problem in this case
might not be an accurate representation of its capability for health care, to my knowledge the two have a close relationship and employee number is the best data available to me that are relatively consistent across facilities.
These are the four types that I choose to use based on general knowledge of the health care that elderly population use most.
Pediatrics obstetrics gynecologic
Delete unrelated and uncovered points
Most point locate in the center of Atlanta MSA
Thirty minutes has been suggested an appropriate catchment size for analyzing spatial access to health care
This study extends the catchment size to 60 minutes so that isolated rural regions can be included in the computation
ID of each pair
In both general and categorical access, the access in center is higher than the peripheral area, because low density of residence and high density of health facility
the categorical access is lower than general access, more smooth transition from very high access metropolitan areas to very low access suburban areas than general accessibility
Use the national threshold value for designating physician shortage area
It’s especially obvious for homes for the elderly,
it is a highly possible that the general access overestimate the access.
Difference: most significant for homes for the elderly , overestimation most serious for the homes for the elderly
The highest difference is in the center of metropolitan area, the overestimation problem is the most serious for center
calculate potential accessibility over a range of exponent values and explore the stability of the observed accessibility patterns in the future
To properly address all of these issues, detailed surveys of actual utilization of health facilities would be necessary
