Chris Sampson’s journal round-up for 25th July 2016

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

The income-health relationship ‘beyond the mean’: new evidence from biomarkers. Health Economics [PubMed] Published 15th July 2016

Going ‘beyond the mean’ is becoming a big deal in health economics, as we get better data and develop new tools for analysis. In economic evaluation we’re finding our feet in the age of personalised medicine. As this new study shows, analogous changes are taking place in the econometrics literature. We all know that income correlates with measures of health, but we know a lot less about the nature of this correlation. If we want to target policy in the most cost-effective way, simply asserting that higher income (on average) improves health is not that useful. This study uses a new econometric technique known as the recentered influence function (RIF) to look at the income-health relationship ‘beyond the mean’. It considers blood-based biomarkers with known disease associations as indicators of health, specifically: cholesterol, HbA1c, Fibrinogen and Ferritin. Even for someone with limited willingness to engage with econometrics (e.g. me) the methods are surprisingly elegant and intuitive. In short, the analysis divides people (in terms of each biomarker) into quantiles. So, for example, we can look at the people with high HbA1c (related to diabetes) and see if the relationship with income is different to that for people with a low HbA1c. The study finds that the income-health relationship is non-linear across the health distribution, thus proving the merit of the RIF approach. Generally, the income gradients were higher at the top quintiles. This suggests that income may be more important in tipping a person over the edge – in terms of clinical cut-offs – than in affecting the health of people who are closer to the average. The analysis for cholesterol showed that looking only at the mean (i.e. income increases cholesterol) might hide a positive relationship for most of the distribution but a negative relationship at the top end. This could translate into very different policy implications. The study carried out further decomposition analyses to look at gender differences, which support further differentiation in policy. This kind of analysis will become increasingly important in policy development and evaluation. We might start to see public interventions being exposed as useless for most people, and perhaps actively harmful for some, even if they look good on average.

Using patient-reported outcomes for economic evaluation: getting the timing right. Value in Health Published 15th July 2016

The estimation of QALYs involves an ‘area under the curve’ approach to outcome measurement. How accurately the estimate represents the ‘true’ number of QALYs (if there is such a thing) depends both on where the dots (i.e. data collection points) are and how we connect them. This study looks at the importance of these methodological decisions. Most of us (I think) would use linear interpolation between time points, but the authors also consider an alternative assumption that the health state utility value applies to the whole of the preceding period. The study looks at data for total knee arthroplasty with SF-12 data at 6 weeks, 3 and 6 months and then annually up to 5 years after the operation. The authors evaluated the use of alternative single postoperative SF-6D scores compared with using all of the data, and both linear and immediate interpolation. This gave 12 alternative scenarios. Collecting only at 3 months and using linear interpolation gave a surprisingly similar profile to the ‘true’ number of QALYs, at only about 5% too high. Collecting only at 6 weeks would underestimate QALY gain by 41%, while 6 months and 12 months would be 18% too high and 8% too low, respectively. It’s easy to see that the more data you can collect, the more accurate will be your results. This study shows how important it can be to collect health state data at the most appropriate time. 3 months seems to be the figure for total knee arthroplasty, but it will likely differ for other interventions.

Should the NHS abolish the purchaser-provider split? BMJ [PubMed] Published 12th July 2016

The NHS in England (notably not Scotland or Wales) operates with what’s known as the ‘internal market’, which separates the NHS’s functions as purchasers of health care and as providers of health care. In this BMJ ‘Head to Head’, Alan Maynard argues that it ought to be abolished, while Michael Dixon (a GP) defends its maintenance. Maynard argues that the internal market has been an expensive experiment, and that the results of the experiment have not been well-recorded. The Care Quality Commission and Monitor – organisations supporting the internal market – cost around £300 million to run in 2014/15. Dixon argues that the purchaser-provider split offered “refreshingly new accountability” to local commissioners with front-line experience rather than to the Department of Health. Though Dixon seems to be defending an idealised version of commissioning, rather than what is actually observed in practice. Neither party’s argument is particularly compelling because neither draws on any strong empirical findings. That’s because convincing evidence doesn’t exist either way.

The impact of women’s health clinic closures on preventive care. American Economic Journal: Applied Economics [RePEcPublished July 2016

More than the UK, the US has a problem with anti-abortion campaigns having political influence to the extent that they affect the availability of health services for women. This study is interested in cancer screenings and routine check-ups, which aren’t politically contentious. The authors obtain data that include clinic locations and survey responses from the Behavioural Risk Factor Surveillance System. The analysis relates to Texas and Wisconsin, which are states that implemented major funding cuts to family planning services and women’s health centres between 2007 and 2012. 25% of clinics in Texas closed during this period. As centres close, and women are required to travel further, we’d expect use of services to decline. There might also be knock-on effects in terms of waiting times and prices at the remaining centres. The analyses focus on the effect of distance to the nearest facility on use of preventive services, controlling for demographics and fixed effects relating to location and time. The principal finding is that an increase in distance to a woman’s nearest facility is likely to reduce use of preventive care, namely Pap tests and clinical breast exams. A 100-mile increase in the distance to the nearest centre was associated with a 7.4% percentage point drop in propensity to receive a breast exam in the past year, and 8.7% for Pap tests. Furthermore, the analysis shows that the impact is greater for individuals with lower educational attainment, particularly in the case of mammography. These findings demonstrate the threat to women’s health posed by political posturing.

Photo credit: Antony Theobald (CC BY-NC-ND 2.0)

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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.

No borders, no nations, no user charges

It was recently proposed that, here in the UK, foreigners should start having to pay towards their health care because of the apparent budgetary pressure from ‘health tourists’. Let’s be clear upfront; this isn’t a problem. If you believe the media, ‘health tourism’ costs the NHS around £30m per year. That’s less than 0.03% of the NHS budget. And the evidence suggests immigrants don’t use much health care anyway. Nevertheless, at some point in the future, this issue may really need addressing.

The case for treating everyone

The moral case seems obvious; everybody has an equal right to health care. If you think nobody has a right to health care, that’s fine too, but why should foreigners’ health be of less value? Economics, arguably, has a great cosmopolitan and egalitarian tradition. Most economists have been driven by their discipline to accept humans as being equal; even if they’re immigrants. This perspective, I suspect, extends to health economists in the UK.

The NHS constitution does not discriminate against foreigners, so it would presumably need changing if user charges for immigrants are introduced. It states that “public funds for healthcare will be devoted solely to the benefit of the people that the NHS serves“, but does not state who is included in “the people”. I’d like to think it includes anyone who happens to be within our borders at their time of need. Surely it should at least include NHS employees; many of whom are immigrants. If we decide not to treat foreigners for free it means that we do not value their health gains equal to ours. Indeed, the implication here is that any health care they receive is at the expense of a native. If this is the case then we health economists will need to adjust our cost-effectiveness analyses to shift any observed benefits for immigrants to the cost side of the equation.

I totally buy in to the moral case for open borders. It matters not to me whether you were born in England or not; nor does it matter to me whether or not you pay taxes. What’s more important to me is that you are willing to pay taxes, and I know plenty of born-and-bred Brits who would readily shirk their tax-paying responsibilities given the chance. For me an immigrant or a tourist has as much right to health care as an unemployed native. One cannot oppose treatment of immigrants on the grounds that they do not pay taxes without also opposing treatment for the unemployed. Case closed.

Moral arguments aside, plenty of services provided by the NHS also resemble public goods. The spread of infectious disease is an obvious risk of discouraging foreigners from seeking treatment. Furthermore, poor health may prevent or discourage immigrants from entering the labour market. It seems possible, if not likely, that charging immigrants a nominal fee for their health care would cost more than it saved. Hopefully we’ll see more evidence either way in the future.

The case against treating everyone

I can’t fathom a moral objection. Xenophobia might be to blame for the recent policy proposal, but I’ll leave it to others to try and figure out the moral arguments against treating everyone. Practically, however, and it pains me to say this, in the case of the NHS we could potentially have a problem. If a health care system is funded through national health insurance or taxation, the system can’t afford to insure the global population. Milton Friedman would probably agree on this point. The availability of welfare is likely to attract migrants who hope to receive it. Rational agents with health care needs would flock to the UK for treatment.

The budgetary pressure of ‘health tourists’, in the extreme, could dramatically reduce the average health expenditure per NHS patient. More care for ‘health tourists’ leads to less care for natives, and it seems difficult to justify reductions in the quality of care. Just to reiterate, this isn’t a problem right now. The tiny nugget of the budget that goes towards treating ‘health tourists’ does not jeopardise the quality of care provided by the NHS. I am speaking in hypothetical terms here of a situation which hopefully will never arise, but for which we should have a solution.

The solution

I don’t know. Obviously every country in the world should provide high quality universal health care that is free at the point of delivery; regardless of one’s nationality. This might happen some day. Let’s hope it does. In the meantime let’s stop legislating for problems that don’t yet exist.

What do you think? Vote in the poll and share your thoughts in the comments box below