Accessmod Session 2

8/9/2019 Accessmod Session 2

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I n t r o d u c t i o n t o G I S a n d A c c e s s M o d Session 2

-Using GIS to measure and

analyze availability,accessibility and geographic

coverage

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I n t r o d u c t i o n t o G I S a n d A c c e s s M o d

• Introduction• Methods and tools

• Data issues

• Data quality• Data accuracy

• How to address these issues

Session 2 - Content

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I n t r o d u c t i o n t o G I S a n d A c c e s s M o d • Why measuring availability of care and

access to health care ?• Concept of "coverage"

• Effective interventions

• Effective coverage

• A model of service access

• Availability coverage

• Accessibility coverage

• Other components (not addressed)• Geographic coverage

• Concluding words and questions

Session 2 - Introduction

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Why measuring availability of careand access to health care ?

Availability of care and access to health care areimportant components of an overall healthsystem

Measuring accessibility to health care contributesto a wider understanding of the performance ofthis health systems and the identification ofpotential gaps

This wider understanding allows for betterplanning of resources

Advocacy and decision making

scaling up

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Concept of "coverage"

"Health service coverage is a conceptexpressing the extent of interactionbetween the service and the people

for whom it is intended, not beinglimited to a particular aspect of

service provision, but ranging over

the whole process..."

(Tanahashi 1978).5


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Effective interventions

‘Effective’ in this context does not refer to thespecific health impact of the intervention.

Effective coverage of the population is ameasure of the proportion of the populationwho fully comply with a recommendedtreatment regime.

For example , in the case of measurement of a

TB/DOTS programme, we should be concernedwith the proportion of TB patients who havecompleted the entire course of treatment

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Effective coverage

The proportion of the population in need of an

intervention who have received an effectiveintervention. Sometimes the evaluation ofservice quality is included in this dimension.

The key to measurement of effective coverage is

to determine what constitutes an effectiveintervention.

The measurement of effective coverage , as anintermediate goal, is expected to link healthsystem performance measurement more directlyto managerial practices and decision- makingprocess at local, regional and national levels.

Source : Tanahashi, 1978 and Background paper for the Technical Consultation on Effective Coverage of Health Systems. World HealthOrganization 2001.

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P r o c e s s

o f s e r v i c e

p r o v

i s i o n

Source: Tanahashi, T. (1978) "Health service coverage and its evaluation", Bulletin of the World HealthOrganization , 56(2) : 295-303.

TARGET POPULATION

Availability Coverage

Accessibility Coverage

Acceptability Coverage

Contact Coverage

Effectiveness Coverage

SERVICE DELIVERY GOAL

Target population who do not

contact services

A model of service access

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TARGET POPULATION

Availability Coverage

Accessibility Coverage

Acceptability Coverage

Contact Coverage

Effectiveness Coverage

SERVICE DELIVERY GOAL

A model of service access

Strong geographic dimension

P r o c e s s

o f s e r v i c e

p r o v

i s i o n

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Geographic coverage


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Availability coverage

Availability coverage shows what resources are

available in what amount for delivering an intervention.This might include: number of health facilities, numberof personnel, availability of technology (drugs,equipment, etc.).

In other words, availability coverage relates the capacityof a health system to the size of the target population.

Two ways of measuring availability coverage aresuggested: – The proportion of people for whom sufficient resources and

technologies have been made available. – The ratio of resources to the total population in need. – The proportion of facilities that offer specific resources, drugs,

technologies, etc.

Source : Tanahashi, 1978 and Background paper for the Technical Consultation on Effective Coverage of Health Systems. World Health

Organization 2001.

Offer

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Availability coverage

• nbr of nurses by inhabitants

Examples of measure:

• nbr of hospitals by district

• ...

• frequency of drug stock out

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Accessibility coverage Accessibility coverage measures how accessible

resources are for the population. The resources mightbe available but inconveniently located, thereforehindering physical access.

The distance from a health care provider seems to be a

very strong factor of accessibility. Another factor of accessibility related to distance and

transportation facilities is time. The travel time to ahealth facility and the waiting time to see a healthprofessional seem to be well associated withconsumers’ perception of accessibility of services.

Source : Tanahashi, 1978 and Background paper for the Technical Consultation on Effective Coverage of Health Systems. World

Health Organization 2001.

Concern the demand side

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Accessibility coverage

• percentage of the population livingwithin 5 km from the nearest facility


• number of patient having to travelmore than 1 hour to reach care

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Accessibility coverage

• Spatial distribution of the prevalence population

and of the ART patient compare to the location ofthe ART sites

Axis

Example of spatialdistribution of theprevalence populationaccording to the traveltime to the nearest ART

site (model)

X: travel time expressed inminutes

Y: percentage of totalconsidered population

Curves

Example of spatialdistribution of the ARTpatients according to thetravel time they took inthe reality (survey)

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 > 8

Travel time (hours)

% o

f t o t a l c o n s i d e r e d p o p u l a t i o

n

Prevalencepopulation

ART

patients

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Other components (not addressed)

Acceptability coverage measures the proportion of

people for whom services are acceptable. Even ifresources are available and accessible, they may notbe used if they are not acceptable to the population. Acceptability includes affordability, in the first place,as well as non-pecuniary factors such as culturalacceptability, beliefs, religion, gender, type of facility,

neighbourhood of facility, etc.Contact coverage measures the proportion of the

population who have had contact with a health serviceprovider. It is similar to “utilization of services”. For

health interventions that require a one-time action,contact coverage may be virtually equivalent toeffective coverage. For other interventions,effectiveness requires several contacts with a healthcare provider.

Source : Tanahashi, 1978 and Background paper for the Technical Consultation on Effective Coverage of Health Systems. World

Health Organization 2001.15


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Combining availability andaccessibility coverage: "geographic

coverage":• Availability looks at how the offer is spatially

distributed without considering if this offer isphysically accessible

• Accessibility looks at how physically accessible aservice is to the population without considering ifthe offer would be enough to cover the demand

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Geographic coverage

• Percentage of the prevalence population located within a given

travel time (e.g. 1,2,5,… hours) of the nearest ART site taking

into account the patient coverage capacity of each site.

Travel timePrevalence

population

covered (size)

% of the total

prevalence

population

increase in

coverage

Within 1 hour 120'000 52

Within 2 hours 145'000 63 + 11 %

Within 3 hours 190'000 82 +19 %

Within 9 hours 190'000 82 + 0 %

Within 10hours

190'000 82 % + 0 %

Reach the maximumcoverage capacity of thecare delivery system

Spatial distribution

of the population being

not covered


Use for scaling up !17


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Concluding words

Thematic Mapping

Spatial Analysis

Spatial Modelling

Complexity Data Accuracy Data Quality

accessibilitycoverage

geographic

coverage

availability

coverage

Need for appropriate methods and tools

Questions ?18


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• Availability coverage

• Accessibility coverage

• Geographic Coverage• Concluding words and

questions

Session 2 – Methods and tools

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Availability coverage (method)

Survey instrument which integrates a"Geo" component

• Need to standardize the collection of

the geographic component

Notion of Signature Domain

Well established

data collection,

cleaning and

validation

protocols

(Minimum set of field

to uniquely identify

an object)

• Health facility or upper level

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Availability coverage (tool)

Example: Service Availability and Readiness

Assessment (SARA)

http://www.who.int/healthinfo/systems/sara_introduction/en/

The Service Availability and

Readiness Assessment

(SARA) is a health facility

assessment tool designed

to assess and monitor the

service availability and

readiness of the health

sector and to generateevidence to support the

planning and managing of a

health system

( )

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http://www.who.int/healthinfo/systems/sara_introduction/en/http://www.who.int/healthinfo/systems/sara_introduction/en/http://www.who.int/healthinfo/systems/sara_introduction/en/


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Availability coverage (tools)

Same availability coverage (e.g nbr ofhealth facility by district) !

Consider this surface as a closed system !

Limitations: location and borders

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I n t r o d u c t

i o n t o G I S a

n d A c c e s s M

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Country population: 11'272'219 (wt Likoma)

At the country level:

ART sites: 103 (101 mapped)

Country level prevalence data:

16'350 people infected by 1 full time physician

• Nbr of patients under ART: 81'632

• Total nbr of people infected: 1'572'907

850 patients under ART by full time physician

Nbr of full time Physicians: 96

Number of infected people / ART patient by full time physician


Limitations: level of desegregation

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At the regional level:



At the country level:

16'350 people infected by 1 full time physician

850 patients under ART by full time physician

Limitation: level of desegregation

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Number of infected peoples Number of patients under ART



At the district level:

Depends on the level of desegregation !

Limitations: level of desegregation

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• Mostly looking at public facilities

• Survey or census = snap shot intime while the health caredelivery system is dynamic

Should move towards a maintainedhealth facility registry

potential sensitivities

importance of the privatefacilities for certaininterventions (e.g.HIV/AIDS)

Limitations: others

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Accessibility coverage (methods)

SpiderBuffers Network Surface

• 4 main methods:

• 2 types of measure:

• distances • travel time

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Distance versus travel time

• peoples are better at estimating time thandistances

• time is a more comparable measure (e.g. betweencountries) than distances

• distance can be derived, to some extent, fromgeography while time is dependent on thetransportation media, condition of the patient andother factors such as climate,...

• the level of emergency when needing to receive

care is measure in time not in distance

All of this advocate in the favor of using timeand not distance for measuring accessibility

• ...

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• geographic location of the consideredhealth facilities

• maximum travel time considered forreaching the health facility =>distance (speed)

• only realistic in flat areas and where everybody istraveling by feet ! Does not take barriers into

account

Need:

• a GIS software allowing to draw abuffer around each facility andmeasure the population located ineach of them

Main advantage:

Major limitations:

• easy to implement once we have the location ofthe facilities

Buffers

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• maximum travel time considered forreaching the health facility

• Does not cover areas outside of the existing roadnetwork

Need:

• the road network

Main advantage:

Major limitation:

• realistic in countries where most of thepopulation use the roads (bus, car, motorcycle,..)

Network

• a GIS software able to performnetwork analysis and link eachpopulation with the facilities

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• maximum travel time considered forreaching the health facility

• Requires several GIS layers to create the traveltime distribution grid

Need:

• travel time distribution grid

Main advantage:

Major limitation:

• allow to cover all the country and take differenttravel scenario into account (walking, car,...)

• a GIS software to draw catchmentareas based on the travel timedistribution grid

Surface

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• geographic location of the visitedhealth facilities

• geographic location of the point oforigin (e.g household)

• Requires an important field data collectionexercise to get a representative picture

Need:

• a survey to have the information

about the length of travel (time) andtransportation media used

Main advantage:

Major limitation:

• gives the extend of the "real" catchment area

Spider

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Not designed based on a maximumdistance or travel time

• Does not take potential barriers to movementsinto account (e.g. rivers).

Need:

Main advantage:

Major limitation:

• indicates which facility is the closest from any pointin the country

Thiessen polygons

• a GIS software able to draw thethiessen polygons

• geographic location of the considered

health facilities

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Notion of catchment area

Definition: The area and population fromwhich a city or individual serviceattracts visitors or customers. 1

1 www.wikipedia.org

Modeled versus "real" catchment area

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http://www.wikipedia.org/http://www.wikipedia.org/


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Big difference in the results !


Different models

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example: 10 km buffer

Can't aggregate the data back to the

district level

Counting the same patient several

times !


Managing the overlaps !

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To, from and round trip

Round trip = to + waiting time + from

To = from


Will produce different catchment areas37


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Accessibility coverage (tools)

SIGEpi SIGEpiNetwork Analyst (ext.to ArcView)

Severalextension to ArcView 1

ESRIproductsand ext. 1

... Health Analyzer 3

1 http://www.esri.com/

2 http://grass.itc.it/

GRASS 2

...

...

3 www.healthsystems2020.org/files/628_file_HealthGIStoolkit.pdf

Flomap

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AccessMod

http://arcscripts.esri.com/http://grass.itc.it/http://www.healthsystems2020.org/files/628_file_HealthGIStoolkit.pdfhttp://www.healthsystems2020.org/files/628_file_HealthGIStoolkit.pdfhttp://grass.itc.it/http://arcscripts.esri.com/http://arcscripts.esri.com/http://arcscripts.esri.com/


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Spider Patient exit survey conducted in the

context of the WHO Equity project

• Unique ID for each facility (slide 2-19)

• point of origin for each patient (home,work,...)

• transportation media used (car, feet,bicycle, bus,...)

• administrative unit in which the patient

lives

• time taken to reach the facility

1. Questionnaire

• additional information (e.g. any facilitycloser ?)

855 patients after cleaning

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• Geographic location of each facility(latitude/longitude)

• Extension of the considered administrativeunits (traditional authorities)

• ArcView 3.2

2. GIS layers

3. GIS software

• Spider script

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0%

20%

40%

60%

80%

100%

Bicycle (own, hired) 7% 15% 22% 27%

Car (own, hired) 3% 2% 4% 5%

Public bus 36% 46% 34% 21%

Walk 54% 37% 39% 48%

0-30 31-60 61-120 121+




Travel time by sex and wealth quintile

0

20

40

60

80

100

120

Poorest

20%

Q2 Q3 Q4 Richest

20%

T r a v e l t i m e i n m i n u t e s

Male

Female

Fullsample

Results

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context of the WHO Equity projectResults

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Spider

• Survey = snap shot in time while thehealth care delivery system isdynamic => institutionalization

• importance of the samplerepresentativity if this exercise can'tbe applied to all the facilities

• need to have the geographic locationof all the surveyed facilities + of theplace of origin

institutionalize the process (routine)

importance of the health facility registry

can be implemented in the electronic

medical record system if any

Limitations

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Surface 2 tools presented here:

1 http://flowmap.geog.uu.nl/ 2 http://www.who.int/kms/initiatives/accessmod/en/index.html

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Freeware Freeware

Stand alone Extension

($)

$

Utrecht Univ. WHO

Point of origin,destination, roadnetwork

Health facility location, population,landcover, roads, barriers (rivers,lakes,..), DEM

2011 2012

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http://flowmap.geog.uu.nl/http://www.who.int/kms/initiatives/accessmod/en/index.htmlhttp://www.who.int/kms/initiatives/accessmod/en/index.htmlhttp://flowmap.geog.uu.nl/


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SurfaceFlowmap was specificallydesigned to handle:• Storing, displaying, and

analysis of spatial flowpatterns, (for instance commuter trips, trade flows,and telephone calls);

• Computing distances, travel times, or transportcosts using a transportation network map;• Modelling the market areas of existing or planned

facilities.

Main advantages:• standalone

• limited number of data required

Major limitations:• limited number of parameters

taken into account• does not handle anisotropic

movements46


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Surface AccessMod has beendesigned to :• analyze physical

accessibility• analyze the population coverage capacity of an

existing health facility network

• provide potential solutions for scaling up theexisting network if necessary

Main advantages:• take a larger number of parameters

into account• consider different traveling

scenarios (walking, car, bicycle)• manage anisotropic movements• access to ArcView capacities

Major limitations:• not a stand alone application

• require more input data47


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Geographic coverage (Methods)

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Maximum

travel time

Processing

Order

ToFrom

New health

facility

information


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Concluding words

Combining where patients are coming from

(survey) with the results of the model

Potential bypassing

• confidentiality• quality of care

• ...

Potential gaps

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Concluding words

Combining where patients are coming from

(survey) with the results of the modelAxis

Example of spatialdistribution of theprevalence populationaccording to the traveltime to the nearest ARTsite (model)

X: travel time expressed inminutes

Y: percentage of totalconsidered population

Curves

Example of spatial

distribution of the ARTpatients according to thetravel time they took inthe reality (survey)

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 > 8

Travel time (hours)

% o

f t o t a l c o n s i d e r e d p o

p u l a t i o n

Prevalence

population

ART

patients

The use of several method is often needed toallow for the analysis50


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Concluding words

Scaling up the existing network

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Concluding words

Questions ?

in French !

http://www.ij-healthgeographics.com/

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http://www.ij-healthgeographics.com/http://www.ij-healthgeographics.com/http://www.ij-healthgeographics.com/http://www.ij-healthgeographics.com/


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• The issues

• Data accuracy

• Data quality

• How to address these issues ?

Session 2 – Data

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The issues

Thematic Mapping

Spatial Analysis

Spatial Modelling

Complexity Data Accuracy Data Quality

accessibility

coverage

geographic

coverage

availability

coverage

Need high data accuracy and quality !

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Data accuracy

Logical accuracy

A

B

C

a. b.

A

B

C

Refers to the integrity of relationships amonggeographic features. 1

the logical accuracy is respected between 1. and 2.

Positional accuracy

1 http://unstats.un.org/unsd/publication/SeriesF/SeriesF_79E.pdf

a. b.

A B C

A

B

C

A

B

C

Positional accuracy, in contrast, maintainsthat the coordinates of features in the GISdatabase are correct relative to their truepositions on the earth’s surface. 1

the positional accuracy is not respected between1. (true position) and 2. (GIS database)

1. 2.

1. 2.

If positional accuracy is fulfilled, logical accuracy isnormaly ensured by the oposite is not true

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http://unstats.un.org/unsd/publication/SeriesF/SeriesF_79E.pdfhttp://unstats.un.org/unsd/publication/SeriesF/SeriesF_79E.pdf


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Data accuracy

Some real examples (positional accuracy)

Dedza district hospital

MOH

CDC

NSO

LATH

500 m

RiversCSO

Survey Dpt.

DCW

Satellite image

! !!

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D


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Data accuracy

Some real examples (positional accuracy)

RiversRoads

PopulationPopulation

Incompatibility

between layers 57

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Data quality

Completeness Refers to having all parts or elements; lacking

nothing; whole; entire; full:

A real example

Coverage under estimated ! 58

D li


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Data quality

Time stamp Refers to the temporal representativity of the data

Example

will not produce coherent results !

2000

1950

1980

2008

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H t dd th i ?


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How to address these issues ?

R e c o m m e n d a t i o n s

R e c o m m e n d a t i o n s

S t a n d a r d

s

P r a c t i c e

s

S t a n d a r d

P r o t o c o l

P r o t o c o l

P r o t o c o l

- Unique identifier

- Time stamp

- Completeness

- Scale, projection

- ...

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H t dd th i ?


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How to address these issues ?

P r o t o c o l

P r o t o c o l

P r o t o c o l

Data production chain61

S i 2 St th i f th


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• The Challenges – the exampleof Malawi

• Using health as the driver forthe change• A different approach – the

example of Zambia• Current activities• Conclusion

Session 2 – Strengthening of thegeographic component of the HMIS

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Th Ch ll


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Survey Department

Forestry Department

Survey Department

Survey Department

National Road Authority

National Statistical Office

GIS capacity and

technical expertise All

Survey Department

Ministry of Health

National AIDS Council

Local Government

National Statistical Office

CDC

.....

Survey Department

Coverage Capacity

Prevalence Ministry of Health

NAC

CDC

UNAIDS

...

The Challenges

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The Challenges e ample of Mala i


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- existence of many different coding schemes that are notlinked together,

Major observed issues:

- very limited integration of the time dimension

- Lack of agreed upon data collection standards and protocols

- Existence of an important capacity, in terms of skills, hardware andsoftware in the country but dispersed among a large number of GIS

stakeholders making each of them very thin in terms of capacity,

- Very limited or even a complete lack of communication between

institutions producing health data and/or geographic information of

interest in public health (MOH, NAC, NGOs, Survey Department,

National Statistical Office (NSO),…),

- The MOH is not participating in the development of the National

Spatial Data Infrastructure (NSDI) for the country,

- Lack of awareness of the data, resources and GIS skills available in

the country (e.g. from the academic sector),

- Important competition for funding.

The Challenges – example of Malawi

The Challenges example of Malawi


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Duplication of efforts for the creation of

datasets that are of questionable quality

CSO

Survey Dpt.

DCWSatellite image


Important limitations towards the applicationof the accessibility and geographic coverage

GIS based methods

Rivers

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The Challenges example of Malawi


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o d Important number of lost opportunities

- collect by the NSO of the location of the health facilities and schools, inthe context of the 2008 population census without collaborating withthe Ministry of Health nor the Ministry of education

Large park of specific hardware (e.g. largesize printer, GPS devices) which is notfrequently used

Leveraging the existing capacity and dataas well as improving the workingconnection between the stakeholderswould benefit all and improve decision

making

- nobody at the Ministry of Health knew that the University of Malawiwas giving a course on medical geography


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Using health as the driver for the


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Access to care is a major public health concern inany intervention (HIV/AIDS in Malawi)

Using health as the driver for thechange

Geography is one strong componentwhich influence access to care

Several compatible GIS layers are needed inorder to measure and analyse this component

The stakholders who manage these differentlayers need to wok together in order to

improve data accuracy and quality andbenefit from each other resources

Improving data will allow more informeddecision making and therefore improve

access to care68

A different approach – the example


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A different approach the exampleof Oman

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Capacity

Biological

Technological

Natural

Societal

Population

Infrastructures

Services

There is a Geog raphic dimens ion

to Risk

Highest

Risk

VRAM principle



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There is a

Geographic

dimension

to Risk



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A different approach the exampleof Oman - SOEMIS

“Providing the right information in the rightplace at the right time…

…to protect and save lives as well as the

country’s investments”



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A different approach the exampleof Oman – Lessons learned (health)

• Health Information System not ready to supportEmergency Management and conduct riskassessments:

• Lack of complete and up-to-date registries(patients, health facilities, human resources,laboratories, catchment areas)

• Health data distributed among different databasesmanaged by different departments within MOH

• MOH not using specific data standards (i.e. coding

scheme) and disconnected from the other sectors• Geographic and time dimensions not integrated in

the HIS

• Health indicators to measure population

vulnerability at the sub national level not available



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A different approach the exampleof Oman – Lessons learned (health)

Project provided a unique opportunity to:• Bring the different department using/needing

geographic information and GIS together

• Start addressing the current gaps andlimitations in the HIS to support EmergencyManagement and risk assessment (i.e. uniquepatient ID)

• Start integrating the geographic and timedimensions in the HIS

Lead to the establishment of a task force to beconverted into a permanent MOH Committee onInformation Management and GIS (CIMGIS)



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d e e t app oac t e e a p eof Oman – Lessons learned (health)

• No entity at the MOH dealing with EmergencyManagement

• Lack of institutional framework and clear mandateamong departments regarding InformationManagement and GIS

• Limited technical capacity to answer the growingdemand for geographic information and GIS

Emphasized the need to address the above forthe MOH to ensure its role as the lead agency

for the Health sector its own needs

Vision defined when it comes to geographicinformation and GIS (“have all the healthdata/information on the map” )

http://www.testvram.org/SOEMIS/REPORTS/MOH_VRAM_pilot_final_report.pdf

Conclusion

http://www.testvram.org/SOEMIS/REPORTS/MOH_VRAM_pilot_final_report.pdfhttp://www.testvram.org/SOEMIS/REPORTS/MOH_VRAM_pilot_final_report.pdf


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Conclusion

The challenge for public health in countries when it

comes to geographic information is mainly to:- make sure that all the data necessary for the work is

accessible, compatible and of good quality (maintenance !)

- have access to the necessary skills, hardware andsoftware in order to insure the analysis of the data

standards, protocols, guidelines and practices

working connections and collaboration (skills,hardware, software,..)

policies and funding

infrastructures (metadata portal) and training

National Spatial Data Infrastructure (NSDI) !

skills directory

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"A Spatial Data Infrastructure or SDI is thetechnology, policies, standards, human

resources, and related activities necessaryto acquire, process, distribute, use,maintain, and preserve spatial data"

What is an SDI ?

An NSDI being a National SpatialData Infrastructure

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Conclusion


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Benefits of an SDI/NSDI

- improve decision making by giving access to more, ofbetter quality and compatible information/data

- build data once and use it many times for manyapplications

- integrate distributed providers of data: cooperativegovernance

- allow for "place-based management"

- share cost of data creation and maintenance andreduce the duplication of efforts

- support sustainable economic, social and

environmental development

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Conclusion


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Conclusion

Health can be the context which leads thedevelopment of an NSDI

NSDIs should actually been build to solve real

problems (e.g access to care) and not necessarilytechnical problems

Health should be part of the NSDI effort

This process indirectly strengthen thegeographic component of the HMIS

Documents

Accessmod Session 2