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7.2  Modelling assumptions

The projection of health care expenditure follows the general LTFM framework for expenditure on public services, outlined in Section 6. Growth in nominal health care expenditure is therefore composed of factors driving growth in the price and the quantity of services, modelled in a way that is consistent with past trends.

The parameter values used for the historic trends scenario also follow the general form for public services expenditure, with annual price growth being composed of inflation (πt = 2.0%), real input price growth (wt = 1.2%), and productivity (at = 0.3%). Annual growth in the quantity of health care services is composed of demographically-driven growth (dt = 1.4% on average) and non-demographically-driven growth (pt = 0.8%). As noted in Section 6, the non-demographically-driven growth parameter is the residual growth in past expenditure that is not attributable to other drivers, and is derived from trends across government services. In a health care context, this parameter represents demand for new services, for example, due to technological changes expanding the scope of treatments.

The equation below outlines the framework for modelling public services expenditure, also explained in detail in Section 6.

The single exception to using the general parameter values for health care is for demographically-driven volume growth, which has health-specific cost weights and assumptions. The approach used to quantify the demographically-driven component of health spending growth is largely unchanged from that used in the 2006 Statement. This approach captures population growth and the effects of population ageing as a greater share of the population shifts into older age groups, which have historically received higher levels of spending. To capture this ageing effect, population projections are multiplied by age-sex specific cost weights, obtained from historic spending patterns across personal health, disability support, mental health, and public health services.[20] Health spending increases as a greater share of the population moves into older age groups, and into the higher cost weights. We again assume that the projected longevity gains translate into further years of good health, and adjust the cost curve for those aged 60 year and above, so that by 2050, the relative health costs of a person aged 65 years are assumed to be equivalent to a person aged 60 in 2009.

7.2.1  Changes from 2006

The modelling approach used in the 2009 Statement includes a number of changes from the approach used to model future health spending in the 2006 Statement. In 2006, health spending was modelled using the following framework:

  • demographically-driven growth, comprising population growth, the effects of an ageing population and changing health status
  • nominal GDP growth as a proxy for income growth (implicitly capturing some growth in input prices such as wages)
  • income elasticity of demand, capturing the demand for health care services as incomes rise, and
  • a residual growth factor, capturing expenditure growth beyond the effects captured by demographic and income-driven changes (eg relative-price changes or increasing service scope due to new technology). This factor was obtained after back-casting known variables, population growth, population ageing, income growth and income elasticity of demand (assumed to be unitary) through history. The base case included an assumption that this residual growth factor would be subject to intensifying long-run cost containment measures, equivalent to the residual abating incrementally from 1.0% to zero over the projection period.

The general modelling form was:

where:

Et = health spending

cwt = growth of Σ cost weights x population group (summing over age and sex)

gt = nominal GDP growth

ε = income elasticity of demand for health services, and

rt = a residual growth factor.

The 2006 approach used nominal GDP growth (3.5%), combining assumptions about inflation (2%) and real wage growth (1.5%). The 2006 base case projection set the income elasticity of demand to 1.0. The residual growth factor was set at 1.0%, and incrementally abated to zero over the projection period under the assumption of unspecified cost containment measures.

Figure 7.3 shows how the 2006 approach relates to that used in 2009, using a graphical representation. As noted above, the method for projecting demographically-driven growth is unchanged, with annual increase averaging 1.4% over the projection period (varying from 1.5% per year at the start of the projection to a peak of 1.9% in 2025, before tapering down to 0.7% by 2050). In contrast, the 2009 model rearranges the 2006 non-demographic factors of nominal GDP growth, income elasticity of demand, and the residual growth factor (representing cost and coverage decisions due to technology) into price components (inflation, real input price growth, offset by productivity gains) and a quantity component (non-demographic volume growth). As noted in Section 6, the new method has the advantage of enabling expenditure growth to be decomposed into price and quantity components, and allowing some flexibility to test different assumptions about public sector productivity.

Figure 7.3 - Modelling health spending growth - 2006 versus 2009
Figure 7.3 - Modelling health spending growth - 2006 versus 2009.

Notes

  • [20]The cost weights for disability support services include cost weights for people aged less than 65 years, and people aged 65 years and over (known as health of older people services).
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