1. A prediction of the use of care provisions in the Netherlands (2005-2020) Jedid-Jah Jonker Ingrid Ooms Isolde Woittiez Social and Cultural Planning Office (SCP) The Hague, Netherlands j.jonker@scp.nl www.scp.nl

2. Outline 1.Introduction 2.Conceptual model 3.Determinants 4.Predictions 5.Conclusions

3. Introduction Determinants of the use of care provisions? Are care provisions substitutes? Predictions of the use of care? Research questions

4. Process to model Use of health care provisions No Care Informal care Privately paid care at home Publicly paid household care Publicly paid personal care Publicly paid nursing care Publicly paid residential care Publicly paid nursing homes

5. Conceptual model: nested ‘Choice’ dimensions Care versus No Care Care at home versus Care in an institution Public paid care at home versus Non-public Choice of the provision Nested logit Models probabilities of using provision

6. Nested logit model

7. Data Sample Dutch population in 2000 9,457 individuals 30 years or older Demographic variables (age, gender, education, household composition, degree of urbanization) Health variables (diseases, limitations, reason for need of care, use of special aid or resources) Income

8. Use of care provisions Decisions No care: 7,475 (79.0%) Informal care: 729 (8.0%) Privately paid care at home: 659 (7.0%) Public household care at home: 255 (3.0%) Public personal care at home: 67 (0.7%) Public nursing care at home: 116 (1.2%) Residential care: 106 (1.1%) Care in a nursing home: 49 (0.5%) Total: 9,457 (100%)

9. Determinants of the use of care

10. Conclusion determinants Determinants Demographic, health and incomes variables are important Demographic especially for care / no care and private / informal care at home decision Determinants not important for choice of public care provision at home

11. Macro-use of care provisions Prediction based on: Estimated probabilities of use of care provisions Forecasts of the determinants, based on population simulation model (not only demography) For instance: income based on projections by CPB, diseases on projections by RIVM

12. Prediction of determinants Ageing: more people of 60 years and older (from 30% to 38%) Not much evidence for double-ageing Impairments with movement (14% to 16%) Diabetes (from 5% to 7%) Asthma (from 9% to 12%) Education: only lower education decreases from 11% to 7% Real income grows with 0.75% per year

13. Care and no care (indices)

14. Care at home vs. in an institution

15. Residential care vs. nursing home

16. Public vs. non-public care at home

17. Privately paid vs. informal care

18. Public paid care at home

19. Summary of predictions Demand for care increases Care at home and in an institution both increase equally fast Care at home: Privately paid care grows fast. Public care and informal care grow slightly Institutional care: Nursing homes grows slightly faster than residential care Public care at home: Growth in personal care (and nursing care). Household care decreases

20. Conclusions (1) Privately paid care increases People rely less on public care at home Quality too low? Supply too limited (waiting times, too few hours)? Too high own payments? Informal care does not increase Informal care is not a substitute for public care Supply too limited? Difficult to ask? Privately paid more flexible?

21. Conclusions (2) Household care decreases People prefer privately paid care for ‘light’ care Personal care increases People stay at home longer, needing more specialized care Nursing care slightly increases ‘Heavy’ care: care at home no alternative for care in institution

22. Summary Use of care Demographic, health and income variables Demographic important for care / no care and private / informal care Prediction Rely less on public care Do not rely more on informal care Stay at home longer, needing more care Nursing care at home no alternative for institutional care