Can You Compare Different Health Systems?




The effectiveness of different approaches to funding and running health systems is often hotly debated, with every viewpoint seemingly able to marshal facts in support of their case. In effect, health statistics have become every bit as politicized as criminal justice. With the current political focus on the limited reforms introduced into the US system by the Obama administration, accurate information is critical and in short supply.

So lets start with some comparative data courtesy of the Organisation for Economic Co-operation and Development (OECD).

In 2007, US health expenditure was estimated to be $7,290 per head leading to an average life expectancy of 78.05 and an infant mortality rate of 6.7 per 1000 live births. In comparison, Sweden spent $3,323 per capita, leading to life expectancy of 80.95 and infant mortality rates of 2.5 per 1000.

Life expectancy and infant mortality are used by the OECD as outcome measures as they are held to reflect the effectiveness of the overall public health system for the complete population.

If correct, the largely privatized US system dependent on individual insurance payments is more expensive (by a factor of 2) and far less effective than a system funded by taxation with access relatively free for the actual user. If true (and the figures are correct and available) then the clear implication is that the US system is both expensive and ineffective (at least for the population as a whole).

However, a more fundamental question is to ask if the methodology and the comparative usage is correct? For example, an early attempt by the World Health Organization (WHO) in the 1990s to prepare such comparisons was withdrawn after US complaints specifically about the methodology adopted.

So, what are the underlying problems in trying to compare different approaches to public health?

In effect, there are three related to the underlying data and an overarching issue about presentation. In terms of data gathering:

1) Measuring expenditure on health is not simple. Even those systems that rely mainly on state provision also raise money directly from users (such as prescription charges) and usually have a parallel private provision (and of course individuals can take out their own health insurance). In a system such as the US, actually identifying all the various strands of health expenditure is particularly complex. Furthermore health expenditure is not just spending on primary and secondary health care it can include public health initiatives around disease prevention and wider health advice (obesity, alcohol, diet). In effect, deciding just how much a given state is spending on health care is never easy;

2) If measuring expenditure is complex, measuring outcomes is even more so. The variety of perfectly valid indicators is overwhelming and each give different information. The data above cites two, based around infant mortality and longevity as these are often used as proxies for the overall health of the population. The World Health Organization, after its initial battering by the US administration, has started to rely on the concept ‘years of healthy life’ for such comparisons. Even without looking at the indicator in any detail that immediately raises the question how something as judgmental as ‘healthy life’ can be consistently measured;

3) The final problem is that each country has a different demographic profile and, in consequence, different health needs. The simplest example is that the elderly and the very young need the most health care. However, even this is not a sufficient adjustment to allow for comparisons (i.e. to start to answer the question does this country spend enough, as well to ask questions about efficiency of expenditure). For example, the health demands of a given population aged between 60-70 will vary due to differences in diet, consumption of alcohol, use of tobacco and level of physical activity undertaken in earlier years. On the other hand, a state with a large immigrant population (typically in their 20s-30s) will appear to do well on outcome measures regardless of actual expenditure, as this group are usually the healthiest sub-section of any human population.

All this leads to one final problem in comparing health outcomes. If all these figures are aggregated to give a simple single figure, as the WHO tried to do in the late 1990s, then that process of aggregation can be flawed. How can different measures, collected on different bases be combined? On the other hand, presenting users and policy makers with a sea of unaggregated numbers will invariably lead to a focus on those that most closely support their existing beliefs.

Given the importance of the current US debate on methods of health funding, these issues are not abstract. If a debate as to the merits of individual funded healthcare in comparison to socially funded models is to be conducted properly, a key element has to be to compare both levels of expenditure and health outcomes.

References

Becker, Gary S, Thomas J Philpson, and Rodrigo R Soares. The Quantity and Quality of Life and the Evolution of World Inequality. Chicago, 2003.

Buckley, John E., and Robert W. Van Giezen. Federal Statistics on Healthcare Benefits and Cost Trends: An Overview. Monthly Labor Review, 2004.

Holahan, John, and Linda J. Blumberg. An Analysis of the Obama Health Care Proposal. The Urban Institute Health Policy Center, 2008.

Castelli, A., Dawson, D., Gravelle, H., & Street, A. (2007). Improving the measurement of health system output growth Health Economics, 16 (10), 1091-1107 DOI: 10.1002/hec.1211

Navarro, V. (2000). Assessment of the World Health Report 2000 The Lancet, 356 (9241), 1598-1601 DOI: 10.1016/S0140-6736(00)03139-1

OECD. Health at a Glance. 2009. OECD Publishing. 3 August 2010.

Veillard, J. (2005). A performance assessment framework for hospitals: the WHO regional office for Europe PATH project International Journal for Quality in Health Care, 17 (6), 487-496 DOI: 10.1093/intqhc/mzi072

Roger Cook, MSc, PhD

Roger Cook, MSc, PhD, works in the UK higher education sector for almost 20 years at various universities in London, Lancaster, Edinburgh and Glasgow. He holds a BA in Economics from Exeter University, a MSc in Analysis of Decision Making Processes from Huddersfield University, and a PhD from Open University. He has been writing since 2007 with an emphasis on psychology and social policy work.
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