access to healthcare, utilization and health outcomes in turkey

Introduction Theoretical Background Research Design Analysis Modelling Strategy Conclusion Future work

Access to Healthcare, Utilization and HealthOutcomes in Turkey

Can KarahasanPiri Reis University

Firat BilgelOkan University

ERF WorkshopThe Economics of Healthcare in the ERF Region

MENA Health Policy ForumCairo, Egypt

22 May 2016

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MOTIVATION

Consolidation of the healthcare system in Turkey (post 2003 reform)

Developments in the healthcare system has sizable effects amongdifferent segments of the society

Current focus is on the access to healthcare system originating frommacro questions:

I size of the Ministry of Health budgetI deficit of the healthcare system in TurkeyI coverage of the systemI Equity among different income groups and among individuals

within and outside the coverage of the system

Our knowledge on the equity issue from regional perspective islimited

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RESEARCH QUESTION(S)Given the extent of regional disparities in Turkey and given sizablemeasures to transform the healthcare system during the last decade:

I What is the extent of regional healthcare inequality in Turkey?Focus is on the accessibility and outcome

I How do we define access to healthcare system?Potential vs. revealed accessibility

I Is it possible to offer an alternative way to measures inequalities?Spatial Analysis of healthcare system

I What is the extent of spatial dependence, heterogeneity andpersistence of regional differences?Spatiotemporal patterns

I How do we incorporate geography to introduce a geographicalaccessibility measure?

I What is the relationship between access to healthcare system andhealth outcomes of Turkish regions?

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HUMAN CAPITAL DEVELOPMENT:HEALTH AND EQUITY

I Gallup and Sachs (2001) and Barro (2013) indicate the impact ofhealth based human capital development in order to understandcross country income differences.

I Lopez-Casasnovas et al. (2005), Frohlich et al. (2006), Fang etal. (2010) put forward the regional dimension by examining intracountry variation of healthcare development

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DATA AND SAMPLE

DescriptionData Source: TurkStat, Ministry of Health Care Statistical YearbooksLevel of disaggregation: NUTS 3 (81 Province)Time Dimension: 2009-2014

CategorizationPotential healthcare accessibilityHealthcare utilization (revealed accessibility)Healthcare outcome

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HEALTHCARE VARIABLES

I Potential healthcare accessibilitypractitioners per 100K population (gptp)specialists per 100K population (specptp)

I Healthcare utilization (revealed accessibility)primary healthcare visits (phcvpc )secondary healthcare visits (sthcvpc)

I Healthcare outcomesinfant mortality (imr1)under five mortality rates (imr5)crude death rate in hospitals per 1K population (crudehosp)

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HOW TO DEFINE INEQUALITY?

I Usual suspectsI Theil Decomposition

T =

n∑i=1

yilog(

yi

xi

)+

n∑g=1

YgTg (1)

I Spatial Concentration - AutocorrelationMoran’s I and Geary’s C

I =ns

∑i wij(xi − x̄)(xj − x̄)∑

z2i

(2)

C =(n − 1)(

∑i∑

j wij(xi − xj)

2(∑

i∑

j wij)(xi − xj)2 (3)

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WEIGHT MATRIX CONSTRUCTION

I Contiguity Weight Matrix

wi,j =

w = 0 if i=jw = 0 if i,j non-neighborw = 1 if i,j neighbor

(4)

I Inverse Distance Weight Matrix

wi,j =1

dni,j

(5)

I k-th Nearest Weight Matrix

wi,j =

w = 0 if i = jw = 0 if di,j > Di(k)w = 1 if di,j ≤ Di(k)

(6)

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DECOMPOSING SPATIAL SPILLOVERS

Local Indicator of Spatial Association (LISA), Anselin (1995)

Ii = (xi − x̄)∑

j

wij(xj − x̄) (7)

4 different Spatial Regimes are identified

I H-H: High-High ClusterI L-L: Low-Low ClusterI L-H: Low-High OutliersI H-L: High-Low Outliers

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PERSISTENCE OF SPATIAL DEPENDENCE:MOBILITY VS. STABILITY

Distributional dynamics approach of Quah (1993, 1996) is lateraugmented by Rey (2001; 2014)

Given each spatial regime represents a state within the distribution, itwould be possible to trace how regions move among these regions inorder to identify the extent of the stability/mobility of the distribution

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SPATIAL MARKOV CHAIN ANALYSIS

Low-Low Low-High High-Low High-High

Low-Low 0 II I IIIALow-High II 0 IIIB IHigh-Low I IIIB 0 IIHigh-High IIIA I II 0

Source: Rey (2001)

F0,t, FI,t, FII,t, FIIIA,t, FIIIB,t

n = F0,t + FI,t + FII,t + FIIIA,t + FIIIB,t

Cohesion index:

Ct =FIIIA,t

n(8)

Augmented cohesion index:

C∗t =

FIIIA,t + F0,t

n(9)

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INCORPORATING THE IMPACT OF GEOGRAPHY:GEOGRAPHIC ACCESSIBILITY

I NEG framework to define market access / potential - Reddingand Schott (2003); Redding and Venables (2004)

I Harris (1954) market potential index is defined to control for thedemand and supply based potential of Turkish provinces

HAi =Hi

Dij(10)

I H measures the province based healthcare indicator(demand/supply in NEG framework, accessibility/utilization inthe current framework) of any region, D represents the physicaldistance between any pair of province.

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DESCRIPTIVE FIGURES

Mean Std. Dev. CoV Min-Max

2009 2014 2009 2014 2009 2014 2009 2014

gpptp 52.10 55.48 7.58 7.78 0.15 0.14 0.48 0.41specptp 62.82 76.64 24.59 27.35 0.39 0.36 0.17 0.19phcvpc 2.94 2.79 0.92 0.78 0.31 0.28 0.09 0.15sthcvpc 4.23 5.38 0.70 0.81 0.16 0.15 0.46 0.44imr1 13.77 10.99 3.27 3.40 0.24 0.31 0.38 0.20imr5 17.49 13.18 4.83 4.09 0.28 0.31 0.30 0.25crudehosp 10.87 15.80 4.34 5.88 0.40 0.37 0.08 0.08

Notes: For the phcvpc variable we use the 2012 data for 2009

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DECOMPOSITION OF INEQUALITIES

2009 2014

Theil Within Between Theil Within BetweenIndex (%) (%) Index (%) (%)

gpptp 0.011 30.26 69.83 0.010 57.51 42.49specptp 0.064 35.79 64.21 0.059 40.41 59.59phcvpc 0.053 20.33 79.65 0.043 21.39 78.61sthcvpc 0.013 48.46 51.54 0.011 55.83 44.17imr1 0.028 44.72 55.28 0.044 29.86 70.16imr5 0.036 30.95 69.05 0.045 25.18 74.84crudehosp 0.084 28.66 71.34 0.073 43.19 56.80

Notes: For the phcvpc variable we use the 2012 data for 2009

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SPATIAL CONCENTRATION

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SPATIAL CONCENTRATION: A SUMMARY

I Existence of sizable spatial dependenceI For primary healthcare access spatial dependence is decreasing,

while for primary healthcare utilization we detected rising spatialauto-correlation

I For all of the healthcare outcome indicators we do observe risingspatial dependence.

I Revisiting Combes et al. (2008) this validates the concerns on thelink between rising spatial concentration and inequalities, givingclues on the existing level of regional healthcare heterogeneities.

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DECOMPOSITION OF SPATIAL CONCENTRATION

LISA Analysis of Infant Mortality Rates (2009)

Not Significant

Low−Low

High−Low

High−High

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LISA Analysis of Infant Mortality Rates (2014)

Not Significant

Low−Low

Low−High

High−Low

High−High

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LISA Analysis of Crude Death Rates at Hospital (2009)

Not Significant

Low−Low

Low−High

High−Low

High−High

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LISA Analysis of Crude Death Rates at Hospital (2014)

Not Significant

Low−Low

Low−High

High−Low

High−High

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PERSISTENCE OF SPATIAL DEPENDENCE: MOBILITY

BETWEEN SPATIAL REGIMES

Low-Low Low-High High-Low High-High

Low-Low 0 II I IIIALow-High II 0 IIIB IHigh-Low I IIIB 0 IIHigh-High IIIA I II 0

Source: Rey (2001)

Type 0 Type I Type II Type IIIA Type IIIB Cohesion Fluxgpptp 0.595 0.123 0.227 0.044 0.010 0.640 0.360specptp 0.938 0.047 0.015 0.000 0.000 0.938 0.062phcvpc 0.932 0.043 0.025 0.000 0.000 0.932 0.068sthcvpc 0.807 0.111 0.074 0.005 0.002 0.812 0.188imr1 0.763 0.183 0.074 0.005 0.012 0.768 0.232imr5 0.805 0.158 0.030 0.007 0.000 0.812 0.188crudehosp 0.820 0.131 0.044 0.005 0.000 0.825 0.175

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ECONOMETRIC SPECIFICATION

I Non-Spatial Models: Cross Section and Panel Fixed EffectsI Spatial Models: Panel Fixed Effects (Spatial Lag and Error

Models)

Spatial Lag Procedure: Spatal Auto Regressive Models (SAR)

HOi,t = a + bHi,t + ρWHOi,t + εi,t (11)

Spatial Error Models (SEM)

HOi,t = a + bHi,t + Wλεi,t (12)

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RESULTS: CROSS SECTION MODELS

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RESULTS: PANEL MODELS

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RESULTS: SPATIAL PANEL MODELS: SAR

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RESULTS: SPATIAL PANEL MODELS: SEM

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SUMMARY OF ECONOMETRIC MODELS

I Cross section and panel models underline the significant impactof access and utilization on understanding regional healthoutcome differences

I Controlling for spatial networks via lag and error proceduresdepresses the impact of access and utilization

I Note that no regional controls are used so farI Geographical access is interestingly influencing our results:

impact of access and utilization is reloaded

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TO CONCLUDE...

I Inequalities matter for healthcare developmentI Outcome of healthcare services is spatially more concentrated,

more heterogeneous and less mobile within the distributionI Modelling outcome shows that even access and utilization

matters, this impact is not robust as incorporating spatialnetworks weakens the impact of access and utilization.

I Using the geographical access as distance weighted access andutilization measures reloads the impact of the two.

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TO DO LIST...

I Discussion on the literature for health and development.Similarly theoretical discussions are going to be reviewed inorder to formalize the background of the central researchquestion.

I Analysis of the spatial varying relationship by estimating theGWR models.

I Augment all set of models by using some other regional controlvariables.

I Discussing the policy issues on healthcare system in conjunctionwith the regional development paradigm.

I Central focus will be diverted to the one size fits approach ofboth healthcare and regional policies.

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Thank you, Q/A

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access to healthcare, utilization and health outcomes in turkey

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