Nurses on strike

Monday saw the first strike by health service staff in England and Wales for 32 years. This dispute surrounds the refusal of the government to implement a 1% pay rise recommended by the NHS pay review body. The reason for not awarding the pay increase given by the Secretary of State for Health, Jeremy Hunt, was that it is “unaffordable”.

There are a number of intersecting interests involved in any industrial action such as this where various stakeholders have a number of positions to consider. For example, the Secretary of State for Health must balance his mandate to protect public health with political considerations such as re-election and positioning within his party. The reasons for rejecting the pay increase, however, are typically given an economic flavour; in particular, Jeremy Hunt warned that an increase in pay this year may lead to the laying off of a large number of nurses next year, leading to a reduction in the quality of care. But, an examination of some of the economic issues surrounding the rejection of pay increases in the healthcare sector may suggest that the driving forces are more likely to be of a political nature.

In England and Wales, the wage paid to nurses is regulated by the state, and is homogeneous across all areas regardless of the local wage rate. Propper and van Reenen (2010) showed that in areas where the regulated nursing wage is lower than the ‘outside’ market wage there are reductions in the quality of nursing staff and hence healthcare quality, which they measured using hospital mortality rates for acute myocardial infarction. Moreover, they found that ‘the effect is “convex” in that the negative effect of regulation on hospital quality is much stronger in the high-cost areas (where regulated wages are much lower than the outside wage) than the positive effect in the low-cost areas (where regulated wages are higher than the outside wage).’ While these findings may be used to argue against a nationally regulated pay structure for health service staff, they certainly suggest that suppressing the nursing wage is likely to have deleterious consequences to patient health outcomes.

Much of the reasoning behind reducing pay is to do with constraining expenditure in the healthcare sector which, across most developed countries, is rising as a proportion of GDP. Nonetheless, there are sound arguments as to why we might expect healthcare to take up an increasing proportion of national expenditure, and furthermore, why this is not a worry. In particular, the Cost Disease argument (which has been previous discussed here and here), suggests that healthcare will take up a bigger and bigger proportion of the GDP pie, but that this pie will grow at least as quick. This is, in part, due to the low marginal rate of substitution between capital and labour and less than average rate of productivity growth in the healthcare sector. If these arguments hold, then governments may be unnecessarily reducing real terms health expenditure. Indeed, in many cases the government targets for NHS spending are wholly unrealistic (Appleby, 2012).

There have certainly been changes to the composition of the labour force in the healthcare sector. The density of nurses has declined from 12.21 per 1,000 people in 1997 to 8.93 per 1,000 people in 2013 while the density of physicians has increased from 2.3 to 2.79 per 1,000 over the same period (World Health Organisation – data here). This may perhaps reflect a replacement of some nursing tasks with capital or the evolving nature of medical care. However, in many areas, recommended nurse to patient ratios are not met; for example, in neonatal care, one recent survey of neonatal units found that 54% of observed shifts were understaffed with respect to recommended nurse to patient ratios (Pillay, 2012). However, given the relative lack of evidence on the cost-effectiveness of nurse to patient ratios, it cannot be said that the reduction in total nursing labour is the result of calculated cost-effectiveness decisions.

Taken together, it would seem that suppressing the nursing wage rate, or reducing the number of nurses, would have negative consequences on patient outcomes. There may certainly be an argument that the losses in quality are worth the costs saved, whether you agree with it or not, but no evidence has been presented to support this point. At a macroeconomic level, the austerity plan presented by many Western governments, the UK’s included, is rejected by a large proportion of economists.* As many economists and commentators have suggested the austerity programme is likely to be used to satisfy political ends rather than economic ones.** The reduction (in real terms) of the nursing wage may support political gains at the expense of healthcare quality and worse patient outcomes.

*For a discussion of these issues and numerous links, see the blogs of Paul Krugman, Simon Wren-Lewis, Martin Wolf, Jonathan Portes, and Chris Dillow among many others.

**Again, this wide ranging discussion is captured by many commentators, see, for example, here and here, from the above mentioned blogs, and this article.

Diagnosing the cost disease

Last year William Baumol published a book entitled The Cost Disease in which he discussed his theory for why healthcare costs continue to rise as a proportion of GDP, while at the same time manufactured goods get cheaper. This idea wasn’t new; he’d first published it in 1967. However, even with 45 years for people to digest his idea, it has generally been overlooked. I shan’t go into much detail about the theory here as it is the subject of a previous post; nevertheless a short outline is probably warranted given its centrality to the rest of this post.

Baumol divides the economy into productive and stagnant sectors; the former includes industries with a high degree of capital input that see increases to labour productivity greater than average as a result of innovation (i.e. computers), while the latter has a less than average labour productivity growth rate since labour is the main input and there is a low degree of substitution between capital and labour (e.g. in healthcare). Wages increase in the productive sector in line with productivity growth. In the stagnant sector wages increase at the same rate to ‘keep up’ and not lose skilled workers, despite the smaller increases to productivity. As a result of productivity growth, overall the economy grows. The costs in the stagnant sector grow relative to the output, whereas costs in the productive sector don’t increase relative to output. Hence, the economy is bigger but the stagnant sector takes up a larger part of it.

The question arises, then, as to how we might test for the presence of the cost disease. The idea is simple and is based on the principle that wages in the economy as a whole rise in line with the productive sector, and that, in the productive sector, wages are tied to productivity. In the productive sector we should not expect to see any deviation in the difference between wages and productivity. Therefore, when we look at differences in wages and productivity in the economy as a whole, any variation in the difference between wages and productivity should be due to the stagnant sector. Shortfalls in productivity in the stagnant sector are not associated with changes to the wage rate. The test for the cost disease is then whether changes to the difference between wages and productivity in the economy as a whole are related to the costs in the stagnant sector, since the theory proposes that the driver of increased stagnant sector costs is the increase in wages relative to productivity.

In a very recent paper, using a panel of 50 US states between 1980 and 2009, Bates and Santerre estimated the effect of the difference between wages and productivity, in the economy as a whole, on unit costs in healthcare. This difference has been called the ‘Baumol variable’. It doesn’t seem to have much direct economic interpretation, but a positive coefficient is interpreted as evidence for the cost disease. They also included controls for the other possible determinants of rising healthcare costs: an aging population, unemployment and income per capita. In a previous paper, Hartwig estimated a similar model.

Both papers find a positive and statistically significant coefficient on the Baumol variable. Bates and Santerre argue that their method and results are an improvement over those of Hartwig, and since they support his findings they further strengthen the evidence for the presence of the cost disease in the US.

As Baumol himself identifies, if we accept the cost disease hypothesis, rising healthcare costs are not that great a problem. While healthcare costs take up a greater share of the pie, the pie is expanding at least as fast. However, Bates and Santerre also find evidence that population aging and unemployment cause increases to healthcare costs. This may mean that the pie does not grow proportionally to the healthcare slice but it does provide some reassurance that the problem is not as severe as depicted by many politicians.

From a policy perspective it may appear as if the solution is a Logan’s Run style scenario where, once people reach a certain age, they are vaporised and ‘renewed’. This would at once solve the aging problem and probably reduce unemployment too. Increases in healthcare costs would then only be a cost disease effect, but I doubt this idea would pass ethics approval. What is certainly true is that a greater understanding of the determinants of healthcare costs are required to better control them and understand the limits of our ability to control them.

The cost disease

Shortly after reading William Baumol’s new book ‘The Cost Disease: Why Computers Get Cheaper and Health Care Doesn’t‘, I thought that its subject matter – rising healthcare costs – may make a good subject for a post. However, John Appleby beat me to it with this excellent ‘Data Briefing’ in the BMJ. In this piece, Prof. Appleby discusses how the inexorable rise in healthcare spending will consume an ever larger portion of GDP. The cost disease does get a mention albeit only briefly:

“the prices of the inputs to healthcare have tended to rise in line with, or even faster than, costs in the economy as a whole—a reflection of the “cost disease” identified by William Baumol in labour intensive industries where the productivity increases that could offset rising pay costs are hard to achieve.”

For me, this is one of the most salient points in the whole discussion, and as such warrants further exploration. And, as Baumol reassures us, the cost disease analysis provides us with good news on the whole since the nature of the cost disease means that we will still be able to afford healthcare as time goes on.

The idea of the cost disease is a simple one. Overall the economy experiences productivity growth; innovation means that the marginal product of an hour’s work increases. But there are industries that experience productivity growth greater than the average and some that experience it less than the average. What’s more, it is almost always the same industries that lie on each side. Baumol and colleagues call the less than average group the ‘stagnant’ sector. These stagnant services typically involve large amounts of labour – a certain element of handicraft. These include healthcare, education, performing arts, and so forth. But why then do their costs rise?

In the non-stagnant sector increases in productivity (should) lead to increases in wages. A worker on an automobile production line where productivity has increased by 4% should expect to see wages increased by 4%. This means that the manufacturer’s profits remain the same and the price of the car remains the same even though the worker’s wages are higher. In the stagnant sector wages will increase to keep in line with wage increases in other areas; but a 4% rise in wages in a firm with less than 4% productivity growth must either lead to an increase in price or a decrease in profits. It is usually the former.

It is as simple as that. Healthcare costs are rising because productivity growth in the healthcare sector is slower than average but wages increase in line with the rest of the economy. If economic growth stops, healthcare costs stop increasing. So we shouldn’t be worried. And it is because of productivity growth that we shouldn’t be worried. For our automobile worker, his wage increases relative to the price of the car each year. Goods from the non-stagnant sector become more and more affordable. Productivity growth means GDP growth so that each individual’s spending power increases year on year. So while stagnant sector services like health care take up a greater and greater proportion of the pie, that pie is growing at least as fast in size. Prof. Appleby notes in his post that healthcare spending is projected to take up 17% of GDP by 2062 compared to just over 6% today. But, GDP is projected to be three times larger by 2062.

In Baumol’s book he points to a number of examples of increasing costs in stagnant sector services. In particular, he focuses on rising healthcare costs and university tuition but also notes other areas such as funeral services and music performance.

Baumol makes a number of important points about the cost disease that are important when considering health care:

  1. The cost disease disproportionately affects the poor – even though increasing productivity should help alleviate poverty by providing more goods and services to the poor, the increasing costs in healthcare could serve as a barrier to these services.
  2. Misunderstanding of the cost disease may lead to government intervention that could make the situation worse – the frightening prospect of healthcare spending inexorably taking over a greater and greater share of GDP could lead to ill-advised interventions. In particular, governments may implement cost controls to keep cost increases below economic growth. But, this will just lead to a reduction in services without actually reducing costs. As we have seen, the cost disease is unavoidable and is a consequence of growth. In another of Prof. Appleby’s BMJ pieces, he provides a graph demonstrating the frankly ludicrous productivity targets the government has imposed on the NHS. In light of our understanding of the cost disease these targets are obviously unobtainable while maintaining the same level of growth in the economy as a whole.
  3. The private sector is liable to the same issues – since many of the stagnant sector services are public sector services, governments are liable to privatise them to control costs. But, the private sector is not immune from the cost disease and can make the same mistakes.

It is important to note that this doesn’t mean that we can’t improve services and reduce spending somewhat now. There are inefficiencies that can be eliminated. Consider the US, which spends 16% of GDP of healthcare, and how it compares to the UK, which spends 6% of its GDP, and yet there are little differences in public health outcomes. There are certainly savings to be made in the US. But, whatever savings are made, healthcare costs will still increase faster than average and will consume an ever greater share of GDP.

Overall, I would recommend Baumol’s new book. It is somewhat over simplified and may not satisfy the economist who reads it. But, it provides a number of clear and relevant examples of the cost disease that should stimulate further discussion and analysis.