The efficiency of treating fat smokers

Recent changes to the NHS raise the potential for health care providers to deny treatment based on an individual’s characteristics, such as their weight or whether they smoke. I think this calls for a reminder of the implications of discriminating in this way, and why, I think, we would do best to avoid it.

Public preferences

The NHS is paid for by the public, so we generally accept that it should do what the public wants (unless the public gets it wrong, of course). A growing body of literature exists on public preferences for the distribution of health care, and the ways in which people might like to discriminate; at least one review of the literature has existed since 2005. When it comes to organ transplantation, some people show a preference for the recipient to have not caused their own illness. Elsewhere, polls have found that around 40% of people would give priority to such individuals. Despite this representing a large minority it does not indicate wide public support for discrimination based on this. Dolan et al (2008) reported that people give 8% less weight to individuals whose illness can be partially attributed to their own lifestyle.

So, it is not clear that the public wants the NHS to discriminate in this way. If it were clear it would presumably be included in NICE guidance. However, cynical readers will of course recognise that such policies are driven by financial incentives rather than a desire to act in the public’s interest.

Efficiency

8% said Dolan and co. This suggests that, if an intervention is close to NICE’s threshold QALY value, it may be justifiable for the fat smokers to miss out. Afterall, their health gain is of a reduced value to society. However, the real efficiency question is whether individuals responsible for their own health problem are actually likely to have a smaller health gain from treatment. This is a very real possibility, as fat smokers are more likely to experience complications in treatment and whatnot. More research should explicitly consider the impact of individual characteristics on the cost-effectiveness of treatment. But people’s capacity to benefit from treatment could be influenced by many things. If we are to discriminate based on efficiency arguments then we must also discriminate between people based on race, age, sex, sexuality, occupation, where they live, and who-knows-what else.

For me, none of this matters. Clinicians can make judgements in individual cases, and it may be efficient to do so, but I find it hard to imagine a situation where discriminating against individuals based on arbitrary distinctions would increase efficiency. If you don’t treat the fat smokers they’ll probably get more ill. They’ll probably die young. When the cancer spreads and the myocardial infarctions become frequent, it’ll cost a lot to save their lives  – a cost that just might have been avoided.

Cancer drugs and public preferences

Last year the UK government announced the establishment of a £600 million cancer drug fund, to be spent over 3 years. This represents a minuscule amount of money compared to the NHS’s annual budget, which is in excess of £100,000,000,000. However, it demonstrates the government’s preference for expenditure on the treatment of cancer over and above other terminal diseases such as multiple sclerosis (MS). Laura Weir of the MS Society recently spoke out in opposition to this special treatment of cancer. I tend to agree with her view, but am I justified?

Public preferences

In recent years an increasing number of newspaper column inches have been dedicated to criticising NICE for rejecting expensive cancer drugs because they are not deemed cost-effective. If we believe the media then the nation is in outrage about this. The prevailing ‘ideology’ in health economics is to evaluate interventions based on the extent to which they satisfy the preferences of the public. This is done by calculating the number of QALYs gained from an intervention and assigning a monetary value to this gain. The government has now implicitly increased this monetary value for cancer drugs, making them more likely to be deemed cost-effective. If we support the use of public preferences, and if the public support extra spending on cancer, then surely we must in turn also support the fund?

Preference for cancer drugs?

The question is whether society is willing to pay more for a drug that helps cancer patients than for a drug that improves or extends the life of anybody else. Is there really a public preference for spending on cancer drugs? I suspect there is, even if this preference has been reinforced and possibly created by the media. To my knowledge there has not been any significant research in this area. If such research did show a preference then it may justify an increased willingness to pay for cancer drugs.

And what about MS?

As somebody whose life has been affected by MS, but not by cancer, I may be bias. Or not. But I believe that expenditure on drugs should be based on the benefit they provide to an individual. Presumably the preference for cancer drugs, if not completely media-driven, is down to the large number of people affected by the disease. When it comes to the amount of money to be spent at an individual level it seems illogical to allow decisions about this to be guided by prevalence. Let’s remember we are not talking about research here, but the fact that an individual with cancer will be allowed to buy expensive (read: less cost-effective) drugs, while somebody with MS will not. I believe this is wrong. But then, I believe that the use of public preferences is not ideal.

Resources are scarce and for every expenditure there is an opportunity cost. An increase in our willingness to pay for the benefits of cancer drugs, at the extreme, leads to a decrease in spending on all other health care interventions. The cancer drug fund raises many questions, not least the possibility that a QALY may no longer be a QALY but may be a cancer-QALY. I believe this is dangerous territory.

Does this issue leave you questioning public preferences? Should we be prioritising treatment for cancer? Or is this all simply a fabrication by the media?

Is a QALY a QALY or not? The SVQ project and the value of life

Back in 2005, NICE and the Department of Health here in the UK set about trying to figure out the level at which society valued a QALY, and also whether different QALYs should be assigned different values. The results of the Social Value of a QALY (SVQ) project have recently been published, and last month the authors involved presented a summary of their findings along with their own interpretation of their results. A crucial read.

The SVQ project is certainly a noble cause and should be a key ambition for health economists to pursue. The authors of the project, in their recent paper, highlight a number of problems and controversies in their methodology. The next step is clearly to investigate these and other methods further before embarking upon a QALY valuation project of a greater magnitude. While the authors recognise the need to hone these methods, it seems to me that a number of other methodological problems have been missed. I would like to raise one here.

Mr QALY: “dead=zero” (Mr VPF: “dead=…..”)

The first part of the study sought to elicit society’s valuation of a QALY using VPF (value of preventing a fatality) and VSI (value of serious injury) figures, as used by the Department of Transport. The results showed that people valued different ‘types’ of QALY differently; that is, QALYs calculated based on life-saving, life-extending and quality-of-life-enhancing considerations. These were valued at £70,000, £35,000 and £10,000 per QALY respectively.

However, there is another way to think about this. It might be that, in reality, people actually value these different types of QALY equally. If this were the case then this discrepancy may arise because VPF respondents actually value being dead as being ‘less than zero’. At first glance this doesn’t make sense as, in the original valuation of QALYs, being dead was anchored at zero. However, to my knowledge, such a valuation of being dead (even if indirect) was not included in the calculation of the VPF. The result of this, in my opinion, is that individuals have to assign their own value to being dead, as it is not pre-determined for them.

It seems possible that, in the calculation of the VPF, individuals assigned an extra negative value to the act of being killed in an accident. This may be caused for a number of reasons – not least an individual’s immediate emotional reaction to a question about, for example, being killed in a road accident. It also seems possible that this is not simply a bias in the method of collecting data but a real dynamic in the overall effect of someone being killed in an accident. In essence, the VPF measures society’s view of the effect of an individual losing their life in an accident, and not the effect of an individual moving from 1 to 0 on an EQ-5D scale. This would mean that a year in “full health” in the QALY calculation is measured on a different scale to a year in “full health” in the VPF calculation. ie – death could result in a greater perceived ‘loss’ in the VPF than the perceived ‘change’ form 1 to 0 in the EQ-5D.

Formulaically I see the problem being that:

VPF=WTP(Y,L)

where WTP(Y) is the monetary value that an individual assigns to each life year lost(quality-adjusted or otherwise), and WTP(L) is a fixed value assigned to the fact that an individual is losing their life. The SVQ study then calculates the value of a QALY from this as:

VQ=VPF/R

where VQ is the value of a QALY and R is the expected number of remaining life years for that individual. This seems reasonable.

However, the VSI would not include this extra ‘L’ factor and thus the WTP will be lower, even if the QALY loss is equivalent. While the EQ-5D is not combined with the VPF data, it is later combined with VSI data, giving the figures for the value of different QALYs shown above. To me this makes the figures entirely incomparable as quality-of-life-enhancing QALYs are based on EQ-5D valuations, while life-saving QALYs are not.

For this reason I feel the valuations of different ‘types’ of QALYs needs to be taken with a pinch of salt. It seems to me that the VPF and VSI should not be used in trying to value the QALY in the future, as we are not comparing like-with-like.

Please share your thoughts on this matter in the comments box below, and please note that this is all conjecture and I may very well be wrong!