disparities in regular health care utilisation in europe a life-time analysis sharelife meeting –...

Disparities in Regular Disparities in Regular Health Care UtilisationHealth Care Utilisation

in Europein Europe

A Life-time AnalysisA Life-time Analysis

SHARELIFE Meeting – Svendborg, (DK) July 20th, 2010

Nicolas Sirven*, Zeynep Or

Institute for Research and Information on Health EconomicsParis, France

(*) [email protected]

1. What do we know?

Regular Health Care utilisation is a public policy matter (prevention, early detection, care) contribute to improved health statusDespite common social security systems in Europe,

disparities in care utilisation across countries are significant

2. What is less well known?

What are dynamics of these disparities?

- How the utilisation of the health care system evolved across generations?

- What contributes more to changing habits? Econ. developt. or health system?

What are the determinants of cross-country differences?

- Few cross-country analysis

- No analysis of individuals’ long term care habits

3. Our contribution

Life-time analysis of individual + system characteristics on people’s behaviour

Comparison of 3 cohorts and 13 European countries over the last 35 years

Introduction

Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis – Nicolas Sirven & Zeynep Or (2010)

1. SHARE data

Individuals 50+ in 15 European countries (on health, social, economic)

Panel = 2 repeated cross-sections (2004, 2006) + retrospective (2008) Sharelife

2. Selected samplew3 + w1|w2 = 13 countries

Born between ]1925-1955] 3 cohorts: 1925-35 ; 1935-45 ; 1945-1955

“Good understanding of Sharelife questions” = drop 0.6% of the sample

Full rank = 22,814 obs. (12,440 for women only)

3. Dependant variables“Did you ever had regular checks…”

Blood tests, blood pressure, gynaecological, mammogram, vision

Binary: 1 Yes (has started regular checks), 0 No (didn’t star so far)

Data


0%

20%

40%

60%

80%

100%

50 55 60 65 70 75 80+

Age class in 2008-09

Blood Tests

0%

20%

40%

60%

80%

100%

50 55 60 65 70 75 80+


Blood Pressure Tests

0%

20%

40%

60%

80%

100%

50 55 60 65 70 75 80+


Vision Tests

0%

20%

40%

60%

80%

100%

50 55 60 65 70 75 80+


Gynaecological Visits

0%

20%

40%

60%

80%

100%

50 55 60 65 70 75 80+


Mammograms

Source: SHARELIFE (2008-2009). Calibrated individual weights used.

Frequencies by Euro-Regions and Age Class

Fig. 1: Population Having Regular Health Check-Ups

European Regions: North East Conti. South

Regular Health Care at a Glance


0%

2%

4%

6%

8%

Ker

nel d

ensi

ty

0 20 40 60 80

Age

Blood Tests

0%

2%

4%

6%

8%

Ker

nel d

ensi

ty

0 20 40 60 80

Age

Blood Pressure Tests

0%

2%

4%

6%

8%

Ker

nel d

ensi

ty

0 20 40 60 80

Age

Vision Tests

0%

2%

4%

6%

8%

Ker

nel d

ensi

ty

0 20 40 60 80

Age

Gynaecological Visits

0%

2%

4%

6%

8%

Ker

nel d

ensi

ty

0 20 40 60 80

Age

Mammograms

Source: SHARELIFE (2008-2009). Calibrated individual weights used.

Fig. 3: Age Start Regular Health Check-Ups

Cohort Birth: Before 1935 ]1935-1945] After 1945

Age Start Regular Health Care



Analysing Cohort Effects in a Given Country


Context Variables in a Given Country

OECD Series statistics

GDP per capitaTotal health

expenditure per capita

Public expend. on health (as % of total

exp. on health)

Practising physicians(Density /1000 pop.)

What context variables explain differences in individual behaviour across cohorts?






exp. on health)


Total growth rate over period p

average volume/level over period p

Mean average annual growth rate over

period p








exp. on health)


Total growth rate over period p

1 variable taking3 different values (cohort) for each

country

average volume/level over period p

Mean average annual growth rate over

period p

Total 5.160 8.031 9.623 22.814 Poland 289 444 755 1.488 Czechia 308 580 702 1.590 Belgium 609 764 1.027 2.400 Switzerland 250 386 438 1.074 Greece 575 794 1.175 2.544 Denmark 362 585 799 1.746 France 474 630 896 2.000 Italy 500 881 809 2.190 Spain 544 565 611 1.720 Netherlands 363 663 890 1.916 Sweden 357 698 580 1.635 Germany 306 686 663 1.655 Austria 223 355 278 856 Country ]1935] ]1935-45] >1945 Total cohort

. tab country cohort

Econometric Methodology


1. Country × Cohort effects

Retrospective data allow disentangling age/cohort effects

Idea: cluster (C=39) = country (J=13) × cohorts (T=3)

Total 2.816 4.269 5.355 12.440 Poland 163 239 444 846 Czechia 187 327 405 919 Belgium 333 418 542 1.293 Switzerland 129 215 242 586 Greece 320 404 629 1.353 Denmark 209 289 427 925 France 263 354 484 1.101 Italy 244 450 478 1.172 Spain 297 312 341 950 Netherlands 195 343 497 1.035 Sweden 184 389 317 890 Germany 150 333 381 864 Austria 142 196 168 506 Country ]1935] ]1935-45] >1945 Total cohort

. tab country cohort if gender==0

Y*ic = 0c + Xic + eic with

Hyp. 1: 0c = 0 + 0c

Hyp. 2: 0c = 0 + 01 Zc + 0c

Econometric Methodology


1. Country × Cohort effects

Retrospective data allow disentangling age/cohort effects

Idea: cluster (C=39) = country (J=13) × cohorts (T=3)

2. Multilevel Model (parsimonious)

3. Two-Step Multilevel- Gives same results (Coeffs. & S.E.) when comparing with HLM

- Allows more interesting Level 2 specification

4. Variables Set

- Age, gender, education, income, Employment status, ADL, Chronic illnesses (Cancer)

- Initial conditions (Index of comfort, SRH child, Relative School Performance)

+ Context variables (Zc)

Step 1: Individual level regressions 1/2


2/2


Step 1: Individual level regressions

-1-.

50

.51

1.5

coe

ffs.

of

clu

ste

rs f

rom

Lo

git

1 2 3 4 5

Practising physicians - Density /1000 pop. Average (over 10 years)

Cohort Birth: Before 1935 ]1935-1945] After 1945 Pooled

Cross-Country Differences in Regular Blood Tests Prevalence

Step 2: Country × Cohorts level regressions

1/2


-1-.

50

.51

1.5

coe

ffs.

of

clu

ste

rs f

rom

Lo

git

1 2 3 4 5


Cohort Birth: Before 1935 ]1935-1945] After 1945



1/2


-1-.

50

.51

1.5

coe

ffs.

of

clu

ste

rs f

rom

Lo

git

1 2 3 4 5


Cohort Birth: Before 1935 ]1935-1945] After 1945 Pooled



1/2



2/2


Purge the effect of health policies from economic conditions

Volume effect (no price effects)

1. SummaryAt the individual Level: Health! & Healthy Worker Effect

Education & economic conditions

… but still significant differences between countries & cohorts

Cohort effect: General shift towards more preventive care across generati

Cross-country: Investment in health care matters

- (Time invariant unobserved heterogeneity)

- People in times & places with higher spending in health have more chances to have regular care (Economic growth per se

matters less)

2. Further Work…

Duration analysis of “Age start regular health care”...

Any suggestions? Thank you!

Discussion


disparities in regular health care utilisation in europe a life-time analysis sharelife meeting –...

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