Disparities in Regular Health Care Utilisation in Europe

Transcription

1 Séminaire «Santé et Travail dans les Enquêtes Européennes» Lille, (FR) 13 décembre 2010 Disparities in Regular Health Care Utilisation in Europe A Life-time Analysis Nicolas Sirven *, Zeynep Or Institute for Research and Information on Health Economics Paris, France (*) sirven@irdes.fr

2 Introduction 1. What do we know? Regular Health Care utilisation is a public policy matter (prevention, early detection, care) contribute to improved health status Despite 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

3 Data 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 sample w3 + w1 w2 = 13 countries Born between ] ] 3 cohorts: ; ; 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)

4 Fig. 1: Population Having Regular Health Check-Ups Regular Health Care at a Glance Frequencies by Euro-Regions and Age Class European Regions: North East Conti. South 100% Blood Tests 100% Blood Pressure Tests 100% Vision Tests 80% 80% 80% 60% 60% 60% 40% 40% 40% 20% 20% 20% 0% 0% 0% Age class in Age class in Age class in % Gynaecological Visits 100% Mammograms 80% 80% 60% 60% 40% 40% 20% 20% 0% 0% Age class in Age class in Source: SHARELIFE ( ). Calibrated individual weights used.

5 Age Start Regular Health Care Fig. 3: Age Start Regular Health Check-Ups Cohort Birth: Before 1935 ] ] After % Blood Tests 8% Blood Pressure Tests 8% Vision Tests 6% 6% 6% Kernel density 4% Kernel density 4% Kernel density 4% 2% 2% 2% 0% 0% 0% Age Age Age 8% Gynaecological Visits 8% Mammograms 6% 6% Kernel density 4% Kernel density 4% 2% 2% 0% 0% Age Age Source: SHARELIFE ( ). Calibrated individual weights used.

6 Analysing Cohort Effects in a Given Country Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010)

7 Analysing Cohort Effects in a Given Country Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010)

8 Context Variables in a Given Country Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010) Public expend. on health Total health expenditure Practising physicians What OECD Series context statistics variables GDP explain per capita differences in (as % of total exp. on per individual capita behaviour across cohorts? (Density /1000 pop.) health)

9 Context Variables in a Given Country Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010) OECD Series statistics Total growth rate over period p average volume/level over period p GDP per capita Total health expenditure per capita Public expend. on health (as % of total exp. on health) Practising physicians (Density /1000 pop.) Mean average annual growth rate over period p

10 Context Variables in a Given Country Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010) OECD Series statistics Total growth rate over period p average volume/level over period p Mean average annual growth rate over period p GDP per capita Total health expenditure per capita Public expend. on health (as % of total exp. on health) 1 variable taking 3 different values (cohort) for each country Practising physicians (Density /1000 pop.)

11 Econometric Methodology 1. Country Cohort effects Retrospective data allow disentangling age/cohort effects Idea: cluster (C=39) = country (J=13) cohorts (T=3). tab country cohort cohort Country ]1935] ] ] >1945 Total. tab country cohort if gender==0 cohort Country ]1935] ] ] >1945 Total Austria Germany Sweden Netherlands Spain Italy France Denmark Greece Switzerland Belgium Czechia Poland Austria Germany Sweden Netherlands Spain Italy France Denmark Greece Switzerland Belgium Czechia Poland Total Total

12 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) Y* ic = β 0c + X ic γ + e ic with Hyp. 1: β 0c = τ 0 + μ 0c 3. Two-Step Multilevel - Gives same results (Coeffs. & S.E.) when comparing with HLM - Allows more interesting Level 2 specification Hyp. 2: β 0c = τ 0 + β 01 Z c + μ 0c 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 (Z c )

13 Step 1: Individual level regressions 1/2 Disparities in Regular Health Care Utilisation in Europe: A Life-time Analysis Nicolas Sirven & Zeynep Or (2010)

14 Step 1: Individual level regressions 2/2

15 Step 2: Country Cohorts level regressions 1/2 Cross-Country Differences in Regular Blood Tests Prevalence coeffs. of clusters from Logit Practising physicians - Density /1000 pop. Average (over 10 years) Cohort Birth: Before 1935 ] ] After 1945 Pooled

16 Step 2: Country Cohorts level regressions 1/2 Cross-Country Differences in Regular Blood Tests Prevalence coeffs. of clusters from Logit Practising physicians - Density /1000 pop. Average (over 10 years) Cohort Birth: Before 1935 ] ] After 1945

17 Step 2: Country Cohorts level regressions 1/2 Cross-Country Differences in Regular Blood Tests Prevalence coeffs. of clusters from Logit Practising physicians - Density /1000 pop. Average (over 10 years) Cohort Birth: Before 1935 ] ] After 1945

18 Step 2: Country Cohorts level regressions 1/2 Cross-Country Differences in Regular Blood Tests Prevalence coeffs. of clusters from Logit Practising physicians - Density /1000 pop. Average (over 10 years) Cohort Birth: Before 1935 ] ] After 1945 Pooled

19 Step 2: Country Cohorts level regressions 2/2 Purge the effect of health policies from economic conditions Volume effect (no price effects)

20 Discussion 1. Summary At 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!