National Health Insurance
Aging of the Population
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The graph below illustrates the expected population of South Africa at five year intervals to 2025, compared to the age and gender structure in 2009.
Figure 6: Age Profiles for South Africa from 2000 to 2025 using ASSA2003
The graph shows the reduction in the number of children, the increase in those in the working years, the increase in those near retirement age and particularly the increase of older women. This illustrates the importance of projections by both age and gender, as the gender mix in each age band in not static over time. Some diseases are more prevalent in females than males and this will affect the future need for specialists in those fields and for particular categories of medicines. The shift is rapid over the horizon of our planning process. In absolute terms, the increases in some age bands are very meaningful e.g. Females age 65-69 grow from some 521,000 in 2009 to 865,000 by 2025, or a 66% increase. This has important implications for future medicine and hospital usage.The table below uses the Managed Care version of the Preferred Table 2009 to isolate the effect of the aging demographics on the cost of healthcare for the country as a whole.
Table 2: Impact on Price of Healthcare of Age and Gender Differences to 2025
The change in age and gender profiles alone would have increased the price of healthcare by 4.1% from 2000 to now in 2009. The price of healthcare would be expected to increase by 10.2% by 2025, given the age and gender differences alone. This table has used the same price of healthcare going back in time and forward in time. However to be more realistic, a price table should be developed for each year taking into account the growing HIV epidemic. The effect would be to make both the historic and future increases larger than quoted. The provinces will also each have a different experience of aging. The Western Cape and Gauteng are expected to have the greatest growth in older people relative to children. Thus the impact of increased chronic disease (excluding HIV) will be highest in these provinces.
Developed using identical methodology to the REF Contribution Table [Base 2005, Use 2007] which was published by the Council for Medical Schemes. The Preferred tables have been produced using the REF Study 2005 data as a starting point and the same consistent methodology. This Preferred series thus gives a consistent historic series which can be used for research, pricing, risk analysis and managed care pricing. The tables are produced by Heather McLeod and updated annually.
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