1 Disability trends among elderly people in 12 OECD countries, and the implications for projections of long-term care spending Comments on Work Package 8 Brussels 29 June 2007

2 2 Source of the slides which follow OECD Health Working Papers No. 26 Trends in Severe Disability among Elderly People: Assessing the Evidence in 12 OECD Countries and the Future Implications Gaétan Lafortune, Gaëlle Balestat, and the Disability Study Expert Group Members

3 3 Two factors driving number of elderly people in need of long-term care: population ageing and age-specific disability rates Number of elderly dependent people

4 4 Countries covered in OECD study Australia Belgium Canada Denmark Finland France Italy Japan Netherlands Sweden United Kingdom United States Key requirement for participation in the study: Availability of time series on the prevalence of severe disability among elderly people (covering ideally 10 years or more) Main focus of this study was to assess trends within countries (disability levels across countries often not comparable)

5 5 Results from OECD study No general pattern of decline in severe disability among elderly people across the 12 OECD countries Four groups of countries: 1)falling prevalence of severe disability (Denmark, Finland, Italy, Netherlands and United States) 2)stable prevalence of severe disability (Australia and Canada) 3)rising prevalence of severe disability (Belgium, Japan and Sweden) 4)impossible to draw a definitive conclusion on the direction of the trend at this time (France and United Kingdom)

6 6 Steady decline in old-age disability in the US (based on the National Long-term Care Survey) Pop. 65+, 1 or more ADL limitations Source: NLTCS

7 7 Reversal in old-age disability rates in Sweden Source: Survey of Living Conditions Pop , 1 or more ADL limitations Note: These estimates include the population at home and in institutions.

8 8 What is going on? What are the factors affecting trends in old-age disability? Positive factors Decreasing prevalence of some diseases (e.g., communicable diseases) Reduction in some risk factors (e.g., smoking) Improvements in medical care and pharmaceutical to treat/manage diseases Growing use of assistive devices (e.g., for walking) Improvements in socioeconomic status Negative factors Increasing prevalence of certain chronic diseases (e.g., arthritis, diabetes) Rising prevalence of some risk factors (e.g., hypertension, obesity) Improved survival rates of sick and disabled people (“frail elderly”) Growing income inequality in some countries

9 9 Projecting the future number of elderly dependent people, based on a simple extrapolation of past trends Expansion of disability (e.g. Belgium, Japan, Sweden) Population ageing only (e.g. Australia, Canada) Compression of disability (e.g. Denmark, Finland, Italy, Netherlands and US) Number of elderly dependent people

10 Projections of number of elderly dependent people – Illustration of country-specific results FINLANDSWEDEN

11 Implications of findings from OECD study on projections of LTC spending High level of uncertainties concerning future trends in severe disability among elderly people: ->need therefore to continue using a range of assumptions concerning the evolution of disability prevalence rates May need to be more cautious in assuming a “compression of disability”: ->need a scenario based on stable (no reduction) in age- specific prevalence of severe disability (combined with assumption of rising life expectancy, this translates into an “expansion of disability” scenario)

12 Trends in elderly people in LTC institutions Source: OECD Health Data 2006, and OECD Society at a Glance, * Refers only to people receiving publicly-funded LTC in institutions.

13 Observations on WP8 paper: hospital beds The revised version of the paper no longer shows number of hospital beds as showing a positive lagged contribution to overall costs. This result is itself surprising: most health systems (whether public or private in their management) have responded to the high costs of acute hospital care by reducing lengths of stay. This has in turn led to a reduction in the number of beds which are resourced. It would be an error, however, to interpret the reduction in total hospital beds as a reduction in capacity. At least in principle, the reason for the reduction is an increase in their capital intensity and productivity: –length of stay is reduced because hospital stays are more productive

14 Observations on WP8 paper: income elasticity of expenditure Why are results showing a low income elasticity of demand rejected? More explanation is needed Since the data used deflates nominal expenditure by GDP deflator, some discussion of what this impliesmay help: –As private sector provision (note, not financing) increases, the proportion of expenditure which is attributed to operating surplus/profits increases. –By definition, no operating surplus is attributed to enterprises operated by general government. Hence the price of services which are attributed to general government will in general be less, and aggregate expenditure (both nominal and deflated by GDP deflator) will also be correspondingly less. –But this is an accounting convention and does not necessarily represent lower real expenditure or commitment of resources.