1. WPIX – Development of Scenarios for Health Expenditure in the Accession Economies POLAND - assumptions and results Stanisława Golinowska, Ewa Kocot, Agnieszka Sowa

2. 1. General projection assumptions No policy changes Base year: 2003 Projection period: 2003 – 2050 HE per capita increase = GDP per capita increase Four scenarios: I. baseline, II. death-related costs, III. different LE improvement IV. different labour market indicators development (IV scenario finished not yet) I. Assuptions; variables, data

3. 2. Main model variables assumptions (base year value and projection necessary) : Demography: Total Fertility Rate, Life Expectancy, Labour Force: employment rate, unemployment rate, Economy: real GDP growth, labour productivity growth

4. 2. Main model variables assumptions (base year data and projection needed): 20032005201020152020202520302035204020452050 DEMOGRAPHY TFR1,221,261,351,431,511,581,641,691,731,751,76 LE-male70,570,971,972,873,674,475,275,976,476,977,4 LE-female78,979,280,080,781,281,782,282,783,183,583,9 LABOUR MARKET Employment Rate50%51%55%59%63%66%70%71%72%73%74% Unemployment Rate20%18%14%11%10%8%7% ECONOMY GDP growth3,8%5,3%5,1%4,8%4,2%3,7%3,2%2,6%2,1%1,5%1,0% Labour Productivity growth4,5%3,0%3,3%4,4%4,2%3,4%3,3%3,2%3,1%3,0%2,7% Main projection sources: Convergence Program, National Development Plan, national experts opinion TFR – medium variant of UN projection, LE – middle variant: ILO population module

5. Demographic variables development – change of size (decreasing) and change of structure (ageing) (1) year 2005 year 2050

6. Demographic variables development – change of size and change of structure (2) Total population - 13% decrease Young population – 26% decrease Active age population – 31% decrease Older population – nearly two times bigger (more than two times from the structure perspective)

7. Labour market and economic variables: Decreasing employment – despite increasing employment rate, higher influence of adverse demographic tendency

8. 3. Health care area - base year data Health Insurance Expenditures per capita by sex / 5-years age groups for base year ( source: National Health Fund) Aggregate Heath Expenditures ( source: National Health Accounts, base year) Additionally in Scenario II: Health Insurance Expenditures per capita by status : deceased or survivor ( source: National Health Fund) HE per capita was used instead of utilization per capita because of data availability in Poland

9. Average health expenditures - base year (as a share of GDP per capita) BASELINE SCENARIO typical J - curve

10. II. Modelling results 1. Revenues side 2. Expenditures side 3. Balance: surpluse/deficit

11. Results (1-2): public health care revenues and expenditures as a share of GDP BASELINE SCENARIO Revenues - important dates: slower growth after 2008 (stabilizing of contribution rate (9%)) about 2025 – still slower growth (lower productivity growth) about 2040 – faster growth (productivity growth higher than GDP growth)

12. Results (1-2): public health care revenues and expenditures as a share of GDP BASELINE SCENARIO Expenditures lesser speed of growing in the last period (slower GDP growth)

13. Results (3): balance - deficit of the health budget as a share of GDP BASELINE SCENARIO Deficit after 2025 : faster deficit growth 2040-2045 : nearly stable deficit after 2045 : deficit decline

14. Results : contribution rate planned and needed to close the gap between expenditures and revenues BASELINE SCENARIO Planned contribution rate - on the stable level 9% Needed contribution rate - dependly on projected deficit is growing up to about 12%, then is decreasing a little

15. Projected total expenditures by age BASELINE SCENARIO Total expenditure by age is growing for each age group, but definitely the largest growth is observed in the older age (connection between demography changes and health expenditures)

16. SCENARIO II – death-related costs SCENARIO II Population was divided into two groups: survivors and deceased Health care is definitely more expensive in the last year of life, independently of age Difference in costs is decreasing in age

17. k indicator a – age sex – male/female AE – average expenditures d - deceased s - survivor SCENARIO II

18. Results: expenditures with/without death-related costs SCENARIO II The last year of life is shifting to the older age – lower death-related costs: total expenditures decrease (0,38 p.p. in 2050)

19. Results: deficit of the health budget with/without death-related costs SCENARIO II

20. Results: contribution rate needed with/without death-related costs SCENARIO II Contribution rate decreases – 0,64 p.p. in 2050

21. SCENARIO III: different LE improvement: slow, middle, fast (demographic effect) SCENARIO III Main difference in the size of the older group of population Slight effect on the active age group

22. Health revenues and expenditures – LE development scenarios slower LE development: lower revenues, lower expenditures faster LE development: higher revenues, higher expenditures

23. Deficit – LE development scenarios slight impact on the deficit (+, - 0,07 percentage point) – expenditures increase (decrease) a little „stronger” than revenues increase (decrease)

24. Results: Scenario I, II and III Deficit is growing in years – different speed of growth Death-related costs scenario: no influence to revenues, quite significant influence to expenditures – lower deficit (compared to baseline scenario) LE scenario: slight influence to revenues, expenditures and deficit

25. Different scenarios sensitivity – changes (2050) as a share of baseline scenario results with death-related costs: nearly 30% lower deficit with better (worse) LE development only 5,4% of change