Review: The Passionate Economist (Sally Sheard)

Credit: Policy Press

Credit: Policy Press

The Passionate Economist: How Brian Abel-Smith shaped global health and social welfare

Hardcover, 581 pages, ISBN: 9781447314844, published 21 November 2013

Amazon / Google Books / Policy Press

I enjoy reading about the lives of effective academics. Sally Sheard’s biography of Brian Abel-Smith drew me in with its title: ‘The Passionate Economist’. It hints at a life to which some of us might aspire.

Brian Abel-Smith was an economist who straddled academia and politics. He spent much of his career with the LSE, but his global impact came through work with the WHO, Europe and developing nations’ governments.

Before embarking on this hefty hardback, my prior knowledge of Brian Abel-Smith was sparse. I delved into my reference manager – sure I’d read some of his work – to find a chapter in a book first published before I was born. The latest generation of health economists could easily miss Abel-Smith’s work. Sheard’s book reveals some reasons why. He never participated in the Health Economists’ Study Group and dedicated much of his career to practical work with an international focus. He was reluctant to engage with the theory-heavy work by the likes of Tony Culyer, which helps explain why many MSc courses don’t include him.

Sheard starts out by describing the early years of a boy with whom most readers will have little in common. Born in 1926 to a Brigadier-General and distant relation to the royal family, Brian was surrounded by people who were already – or were soon to be – key players in politics and academia. Like Brian, Clement Attlee had attended Haileybury school and promoted several Old Haileyburians in his government. At Cambridge University – where Brian was taught by the likes of Joan Robinson – Labour minister Hugh Dalton was trying to recruit promising students. He invited Brian for supper in 1951. Brian’s privilege is suitably framed and is not likely to alienate the reader, but the torrent of name-dropping might. It is difficult to keep up with so many acquaintances, and difficult to care. Though we at least observe Brian’s adept social skills.

It was charm (coupled with good connections) that enabled Brian to meet the father of social policy, Richard Titmuss. Theirs was to be a long and fruitful professional relationship and friendship, and the basis of Brian’s commitment to the LSE. The Beveridge Report was published when Brian was 16, and readers will find its principles reverberating through his life. Brian was dedicated to the NHS, and his first major research project involved costing the health service. His findings informed the 1956 Guillebaud Report, which concluded that the NHS was pretty good value for money. As Brian made quick progress in his academic career, he prudently maintained relationships with the political world.

It was Brian’s political writing that really got him noticed; his first publication was a pamphlet for the Fabian Society. Despite their incongruence, Brian handled the two worlds of politics and academia masterfully. Sheard likewise gives each their due attention in the retelling. The book is particularly enjoyable when it recounts episodes where Brian’s academic integrity shines through; possibly to the detriment of his political ties and socialist credentials. He regularly criticised Labour policy and shocked colleagues like Julian Tudor Hart when he wrote in support of competition, consumer choice and user fees. I rarely traverse political history as I find it pretty dull, but in staging this history as a backdrop to Brian’s life, Sheard was able to keep me engaged. My limited knowledge of the academic and political history of social policy in Britain left me with much to learn; better informed (or older) readers might not gain so much from the revision.

Brian’s interests extended beyond the ivory tower and beyond Westminster, and so he took roles in hospital management and governance. His work formed part of the basis for the formation of the Child Poverty Action Group, to which he dedicated a lot of time. He also had an entrepreneurial side, setting up a successful men’s clothing business, Just Men. His work is not shown to be of special relevance to the study of health economics, but rather to health and social policy more generally. Seasoned observers might not be surprised to read many parallels between the debates of Brian’s time and those currently storming on Twitter.

For me, the biography does not quite live up to its title. Abel-Smith is presented as many things – conscientious, charming, virtuous, humble, loyal – but his passion does not shine through. The book is written in a matter-of-fact style, and the fact of the matter seems to be that Brian was not particularly demonstrative. But a historical account – more a biography of global health policy than of Brian Abel-Smith – might be fitting. Brian’s life is a history of global health policy. His career tracks international developments and the book will be a treasure trove for historians.

In The Passionate Economist, Sheard has produced a valuable overview of the history of global health policy that many young health economists (like myself) might lack. Part of the joy in reading a biography – for me, at least – is identifying those tantalising gaps in the evidence, which require or encourage the author to use their knowledge of the subject to suggest what might have been. The Passionate Economist contains little of this and Sheard seems to struggle to get under the skin of her subject. But maybe that’s the point; Brian’s passion is veiled by his self-effacing nature. His impact on social policy and health services, both in the UK and internationally, was prodigious. And yet many health economists have never heard of him. There is wisdom in this.

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Posted by on August 10, 2015 in Reviews


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The economics of a 7-day NHS

The recently delivered Queen’s speech set out the government’s plan for “a 7-day NHS”. This vision is a reaction to alarming statistics that mortality rates are increased by 11% for patients admitted to hospital on a Saturday, and 16% if admitted on a Sunday, compared to patients admitted during the week. In a recent paper, I (along with my co-authors) examine the evidence base being used to support this policy move in more detail, and estimate the economic consequences in terms of the potential costs and benefits. The paper focuses on emergency hospital admissions, as this is the area in which the majority of these deaths occur and has been the focus of much of the policy debate.

The evidence base for seven day services

The highly quoted figure of a 16% increase in the risk of mortality is in fact a relative risk, which we all know too well can be misleading. When interpreting risk statistics the key piece of information is the baseline level of risk; figures which are omitted from the case for seven-day services. The most recent figures from England put the elevated mortality risk experienced by patients admitted to hospital in an emergency during the weekend at 0.3 percentage points. Whilst by no means trivial, it is doubtful that this alternative interpretation of the statistics would have summoned quite the same passion for a reorganisation of the entire English healthcare system.

The classic confusion between correlation and causation is the next mistake made when interpreting the ‘weekend effect’ literature. The association between reduced staffing levels in hospitals at weekends and elevated mortality has been cited as the root of the problem, despite a lack of causal evidence to this effect. In spite of this absence of supportive evidence, making routine services available seven days a week has been declared as the solution to tackling the observed weekend effect. The crucial question then, is what are the likely costs and benefits of such service extensions?

“it’s about saving lives”

As economists we are familiar with the concept of opportunity cost, yet sadly it appears that politicians and policy makers have yet to grasp this key notion. Regardless of whether seven-day services are funded through a redistribution of current NHS budgets or an injection of new cash, this decision implicitly diverts potential resources away from patients admitted during the week. The average daily volume of patients admitted to hospital in an emergency is significantly higher on weekdays than during weekends. This means that staff would be diverted away from working at times of high patient volumes to times when there are fewer patients needing treatment. Yet these patients from whom resources are diverted away are never mentioned in arguments of fairness or equity. If, as the government suggest, staffing levels really are the key to reducing mortality, then the introduction of seven-day services may well narrow the gap between weekday and weekend mortality rates. However, it could easily do so by causing the weekday death rate to rise.

Potential benefits and costs of seven-day services

As healthcare policies such as seven-day services are funded from the same NHS budget as new treatments, they should be subject to the same cost-effectiveness evaluation as technologies seeking NICE approval. This requires rigorous evaluation of hard evidence, something seemingly neglected in favour of headline-hitting policy promises. In the paper we use the available evidence, albeit somewhat rudimentary, on the costs and benefits of introducing seven-day services in this setting to assess whether the policy change would likely pass a NICE assessment. We do so under the most optimistic assumption that this service change has the potential to completely eradicate the weekend effect.

Using methods described in detail in the paper, we estimate that reducing the mortality rate experienced by patients admitted in an emergency at the weekends to that observed during the week would result in an annual reduction of between 4,355 and 5,353 deaths occurring nationally (ceteris paribus, of course). This translates into a potential health gain of 29,727 – 36,539 QALYs per year if all of these deaths could be averted. Using the NICE threshold of £20,000 per QALY, the NHS should spend no more than £595m – £731m to achieve a health gain of this size.

Whilst the potential benefits of extending services appear large, they must be compared with the additional costs of doing so. Although caution was emphasised when producing the figures, the best available estimates of the costs of implementing seven-day services are those published by the NHS Seven Days a Week Forum. They estimate this to be 1.5% to 2% of total hospital income, equivalent to a 5% to 6% increase in the cost of emergency admissions. This translates to an annual cost of between £1.07bn and £1.43bn, exceeding our estimates of the maximum amount that the NHS should spend to eradicate the weekend effect by a factor of 1.5 to 2.4, or between £339m and £831m. To make matters worse, all of these calculations take place under the rather optimistic assumption that benefits to patients admitted at the weekend could be achieved without any detrimental effect on outcomes for those admitted during the week.

The way forward

Although alarming, the statistics on elevated weekend mortality are insufficient by themselves to justify a policy change towards extending normal hours of operation into the weekend. There is as yet no clear evidence: that seven-day working will, in isolation, reduce the weekend death rate; that lower weekend mortality rates can be achieved without increasing weekday death rates; or that such reorganisation is cost-effective.

A move towards a fully operational NHS service seven days a week has the potential to have impacts beyond reducing mortality, but these must be evidenced if the policy is to be supported. Mere suggestions that it may reduce factors such as readmission rates and hospital length of stay are not enough to justify a policy change, just as the verbal reassurance of a drug manufacturer that their product was able to cure cancer would not alone secure them NICE approval. Rigorous evidence and evaluation is needed in the policy sphere if we are truly to get the best use from our limited NHS resources. Evaluations of the implementation of seven-day services in the thirteen early adopters should be performed before national implementation is considered, just as any potential new treatment would be trialled before approval.

Disclaimer: The views and opinions expressed are those of the author and do not necessarily reflect those of the HS&DR programme, NIHR, NHS or the Department of Health.


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Identifying the effect of expenditure on health outcomes: another small comment on Claxton et al

In a previous post I asked whether the study by Claxton et al can or should inform the cost-effectiveness threshold used by NICE. The authors argued that, “it is the expected health effects … of the average displacement within the current NHS … that is relevant to the estimate of the threshold.” Accepting this premise, the authors aimed to estimate the average net effect (in terms of QALYs) that has historically resulted from contraction and expansion of the healthcare budget. I want to explore here briefly whether their empirical estimates can indeed be interpreted as such.

When the healthcare budget contracts we may remove services or technologies with a low cost-effectiveness and when it expands we may implement services or technologies with a high cost-effectiveness. The argument is that we don’t want to reimburse a new technology that has a lower cost-effectiveness than what the healthcare service already achieves in practice when the budget changes, which is the net effect of contraction and expansion. The approach taken by Claxton and colleagues to estimate this effect was to use local healthcare authority level data on healthcare expenditure across different programmes of healthcare (e.g. respiratory healthcare or oncology) and examine how changes in this expenditure affected healthcare outcomes, such as mortality. Since healthcare expenditure is likely to be correlated with unobservable determinants of mortality, the authors adopted an instrumental variables approach.

At this point it is important to note that total healthcare expenditure may vary for two reasons. On the supply side, there may be changes in unit costs or shifts in the overall budget constraint; on the demand side, population health may change affecting the need for healthcare, the identity of the patients, and the types of services demanded as well as reductions in the use of healthcare by current patients. I would argue that it is the supply side changes that we are interested in here. Demand side changes may shift which programmes are utilised, and the resulting productivity of those programmes, since the characteristics of the patients will change.

The estimates from an instrumental variables estimator can be interpreted as the local average treatment effect (LATE) which is the average effect of a change in the variable of interest (in this case healthcare expenditure) resulting from a change in the instrumental variable (IV). The IVs utilised by Claxton et al are socio-economic variables (such as the index of multiple deprivation and the proportion of the population providing unpaid care). These variables are arguably on the demand and supply sides since they both affect population healthcare needs leading to different populations being treated and may affect the healthcare utilisation of current patients.

The empirical estimates of Claxton et al may therefore possibly be interpreted as the effect of both changes due to contractions and expansions of the budget (the effect of interest) and a change in the programmes of care provided, the treatments within them, and their productivity resulting from changes to population health needs and the identity of patients.*

Overall, I think that even if we accept the authors’ arguments about why they are trying to identify this effect, their empirical strategy may possibly not identify it.


*It may be argued that a test of over-identifying restrictions (OID), which tests if the instruments are correlated with the errors, would detect if these instruments were related to health needs. However, note that we are looking within a programme of care, for example, cancer expenditure on cancer mortality so that we are conditioning on having cancer (and being diagnosed with it) in this analysis. Socio-economic variables may be determinants of getting cancer or which type of cancer a patient gets but may not be determinants of (i.e. are independent of) the health outcomes from cancer once we’ve conditioned on having cancer and some other factors determining health outcomes. They may therefore pass the OID test.


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Do we really need to change the cost-effectiveness threshold?

The cost-effectiveness threshold utilised by health technology assessment agencies, such as NICE in the United Kingdom, below which new medical technologies and interventions are considered cost-effective, is frequently discussed. NICE currently use a threshold of £20,000 to £30,000 per quality adjusted life year (QALY) gained. However, this threshold was arrived at in somewhat of an ad hoc manner, being simply a reflection of past recommendations made by the agency. As a result, much time has been spent trying to identify what the threshold ought to be in order to best ensure the efficiency of the health service.

To much media attention, a study by Claxton et al was published recently, in which the authors attempt to estimate the returns currently being achieved by the NHS in England. The argument goes that the consideration to adopt a new medical technology should take into account the opportunity cost of doing so; any new technology, given a fixed budget, will displace resources used to achieve health benefits elsewhere in the healthcare service. If the new technology is not as cost-effective as the returns currently being achieved for the money, then the overall efficiency of the healthcare service will be reduced. Claxton and colleagues arrived at the figure of approximately £13,000 per QALY and have argued that NICE should adopt this as their threshold.

The opportunity cost is the benefit foregone by not spending a certain amount of money or deploying resources elsewhere. Within the health service we do not want to reimburse a new treatment when we could alternatively use those resources to achieve greater health gains otherwise; hence, the argument that the threshold should reflect the opportunity cost. What then is the opportunity cost in the health service? Assuming a fixed budget, it is the health gains made from increasing the expenditure on the most cost-effective programme of care minus the health losses from reducing the expenditure on the least cost-effective programme of care, when the healthcare budget is contracted and then expanded.

Does the Claxton et al study estimate this opportunity cost? Only if we assume that there is allocative efficiency in the healthcare service, i.e. that the most cost-effective programme funded when the budget is expanded has the same cost-effectiveness as the least cost-effective programme removed when the budget is contracted, and when there is optimal displacement, i.e. that the displaced technologies are the least cost-effective (Eckerman and Pekarsky, 2015). Neither of these conditions are likely to hold in the health service given the nature of the healthcare market, which may suggest that the Claxton et al results are underestimates of the true opportunity cost.

The above discussion assumes that the goal is the maximisation of population health. However, equity considerations play a role in reimbursement decisions such that we might be willing to maintain funding for a less cost-effective service if it preserves some measure of equity. Incorporation of equity concerns into economic evaluation is often not done in practice but methods do exist. In such a case, we may wish to adopt an equity weighted threshold that reflects an equity weighted opportunity cost. Alternatively, we could allow a different threshold for different patient groups, where the difference between the thresholds reflects society’s willingness to pay for benefits accruing to different persons. Either way we may prefer a threshold higher than the Claxton et al  figure to make room for equity considerations.

A final point is that profit-maximising manufacturers strategically price their products at the cost-effectiveness threshold. Under these conditions, even if displacement is optimal, then there will be no net gain to population health from adopting the new products despite them meeting the cost-effectiveness threshold.

What this all may suggest is that, methodological issues aside, the Claxton et al study does not provide us with strong enough evidence to change the cost-effectiveness threshold. Further research is required to understand which services are actually displaced, the cost-effectiveness of services currently utilised, and incorporation of equity considerations in reimbursement decisions.

Update: As an addendum and in response to a comment below, Claxton et al do write that, “Given NICE’s remit, it is the expected health effects … of the average displacement within the current NHS … that is relevant to the estimate of the threshold.” This average effect, they arguably do estimate; nevertheless, I think it is important to note that under allocative inefficiency and suboptimal displacement, setting this as the threshold may possibly lead us to either (i) reimburse technologies that are worse than the best alternative (the opportunity cost), or (ii) reject technologies that are more cost-effective than the least cost-effective technology removed under a budget contraction.


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#HEJC for 26/02/2015

The next #HEJC discussion will take place Thursday 26th February, at 11pm London time on Twitter. To see what this means for your time zone visit or join the Facebook event. For more information about the Health Economics Journal Club and how to take part, click here.

The paper for discussion is a working paper published by the Canadian Centre for Health Economics (CCHE). The authors are Koffi-Ahoto Kpelitse, Rose Anne Devlin and Sisira Sarma. The title of the paper is:

The effect of income on obesity among Canadian adults

Following the meeting, a transcript of the Twitter discussion can be downloaded here.

Links to the article



Summary of the paper

This is the first paper to examine the causal relationship between income and obesity in the Canadian context. To do so, they examined data from five biennial Canadian Community Health Survey (from 2000/01 to 2009/10), a nationally representative survey collecting information on over 100,000 individuals each survey.

Initially, the paper explored the Grossman model, which suggested increasing income would promote healthy lifestyle investments, and thus lead to a negative relationship between income and obesity. Previous studies that examined this link were discussed, some (eg. Lindahl (2005)) demonstrating a negative relationship; some (eg. Schmeiser (2009)) demonstrating a positive relationship; some (eg. Cawley (2010)) finding no evidence of a causal relationship.

Additionally, education and employment were explored. Again, the Grossman model was used as a basis, predicting i) a negative relationship between education level and obesity with a greater income effect amongst educated people and ii) a negative relationship between employment level and obesity. However, regarding education, prior studies discussed have shown “mixed results”, and regarding employment, the authors were not aware of any study to examine this causal relationship, but suggested the relationship was ambiguous.

Finally, the relationship between gender and obesity were discussed. Numerous studies have shown negative association between income and BMI amongst women, but for men, the relationship is unclear (some showing positive relationship, some negative, and some no significant relationship at all). The importance of the effect of obesity on labour market outcomes (outlining the “large” empirical literature showing obese women more likely to suffer discrimination in the labour market) was outlined.

In this study, the authors found that:

  • From 2000/01 to 2009/10, BMI and obesity rates amongst both men and women have risen.
    • For men, the obesity rate rises from 19.48% for those with income below $10k to 26.09% for those with income over $80k.
    • For women obesity falls from 26.71% for those below $10k to 17.38% for those with income over $80k.
  • For men, a 1% rise in household income leads to 0.027 point decrease in BMI (2SLS estimate); 0.084kg reduction and 0.27% point decrease in probability of being obese (linear IV procedure).
  • For women, a 1% rise in household income leads to 0.113 point decrease in BMI (much higher than for men; this used a 2SLS estimate); 0.300kg reduction; and 0.76% point decrease in probability of being obese (linear IV procedure).
  • For men the effect of income on BMI was only demonstrated at higher BMI distribution, while for women the effect of income on BMI was found throughout with a larger effect at higher BMI.
  • Education had a variable relationship amongst both men and women, not consistent with the theoretical prediction that the effect would be larger amongst educated people.
  • The effect of employment for men was mixed, with a negative effect of income on BMI only in employed men and a negative effect of income on obesity probability only in unemployed men.
  • The effect of employment for women was more consistent with theoretical predictions, showing negative effects of income on both BMI and on the probability of being obese across employment status.
  • Higher BMI and probability of obesity was associated with older age, marriage (much greater effect in women), household size (much greater effect in women) and home ownership.
  • Lower BMI and probability of obesity was associated with being widowed/separated/divorced, being an immigrant and living in urban area (in men).

In summary, this study supports the findings of Lindahl, and stands in contrast to Schmeiser, Cawley and other related studies.

Discussion points

  • Why might there be significant variation in findings between the different studies discussed?
  • Are there ways in which unemployment and neighbourhood income might directly influence BMI?
  • Is the set of control variables used in the authors’ models satisfactory?
  • Is it of concern that policies to increase household income could be regarded a pure, explicit public health policy?
  • Are there relevant studies from other countries?
  • To what extent are these findings generalisable?

Can’t join in with the Twitter discussion? Add your thoughts on the paper in the comments below.


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Health economics journals and negative findings

Recently, a number of health economics journals (henceforth HEJs) co-signed a statement about the publication of negative findings:

The Editors of the health economics journals named below believe that well-designed, well-executed empirical studies that address interesting and important problems in health economics, utilize appropriate data in a sound and creative manner, and deploy innovative conceptual and methodological approaches compatible with each journal’s distinctive emphasis and scope have potential scientific and publication merit regardless of whether such studies’ empirical findings do or do not reject null hypotheses that may be specified.

There was an outpouring of support for this statement; on Twitter, at least. Big deal. Welcome to the 21st century, health economics. Thanks for agreeing to not actively undermine scientific discourse. Don’t get me wrong, it is of course a good thing that this has been published. Inter-journal agreements are rare and valuable things. But is there really anything to celebrate?

Firstly, the statement has no real substance. The HEJs apparently wish to encourage the submission of negative findings, which is nice, but no real commitments are made. The final sentence reads, “As always, the ultimate responsibility for acceptance or rejection of a submission rests with each journal’s Editors.” So it’s business as usual.

Secondly, one has to wonder whether this is an admission that at least some of the HEJs have until now been refusing to publish negative findings. If they have then this statement is somewhat shameful, if they haven’t then it is just hot air.

Thirdly, is publication bias really a problem in the health economics literature? Generally I think health economists – or those publishing in health economics journals – are less committed to any intervention that they might be evaluating, and less rests on a ‘positive’ result. When it comes to econometric studies or issues specific to our sub-discipline I see plenty of contradictory and non-significant findings being published in the HEJs.

Finally, and most importantly for me, this highlights what I think is a great shame for the health economics literature. We exist mainly at the nexus between medical research and economics research. Medical journals have been at the forefront of publishing in a number of aspects: gold open access; transparency; systematic reporting of methods. Meanwhile, the field of economics is a leading light in green open access with the publication of working papers at RePEc, and journals like American Economic Review are committed to making data available for replication studies. Yet health economics has fallen somewhere between the two and is weak in respect to most of these. It isn’t good enough.

There are exceptions, of course. There are a growing number of working papers series. The likes of CHE and OHE have long been bastions in this regard. And there are some journals – including one of the signatories, Health Economics Review – that are ahead of their associates in some respects.

But in general, the HEJs are still on the wrong side of history. So rather than addressing (and in such a weak way) an issue that has been known about for at least 35 years, the HEJs should be taking bolder steps and pushing for progress in our mouldy old system of academic publishing. Here are a few things that I would have celebrated:

  • A commitment to an open-access-first policy. This could take various forms. For example, the BMJ makes all research articles open access. A policy that I have often thought useful would be for html versions of articles to be open access, possibly after a period of embargo, and for PDFs to remain behind a paywall. Journals could easily monetise this – most already deliver adverts. The journals should commit to providing reasonably priced open access options for authors. In fairness, most already do this, but firm commitments are valuable. Furthermore, the journals should commit to providing generous fee waivers for academics without the means to pay.
  • A commitment to transparency. For me, this is the most pressing issue that needs addressing in academic publishing. It’s a big one to address, but it can be tackled in stages. I’ve written before that decision models should be published. This is a no-brainer, and I remain dumbfounded by the fact that funders don’t insist on this. If you have written a paper based on a decision model I literally have no idea whether or not you are making the results up unless I have access to the model. The fact that reviewers tend not to be able to access the models is outrageous. The HEJs should also make the sorts of commitments to transparent reporting of methodologies that medical journals make. For example, most medical journals (at least in principle) do not publish trials that are not prospectively registered. The HEJs should encourage and facilitate the publication of protocols for empirical studies. And like some of the economics journals they should insist on raw data being made available. This would be progress.
  • Improving peer review. The system of closed pre-publication peer review is broken. It doesn’t work. It can function as part of a wider process of peer review, but as the sole means of review it stinks. There are a number of things the HEJs should do to address this. I am very much in favour of open peer review, which makes journals accountable and can expose any weaknesses in their review processes. The HEJs should also facilitate post-publication peer review native to their own journal’s pages. Only one of the signatories currently provides this.

If you are particularly enamoured of the HEJs’ statement then please share your thoughts in the comments below. My intention here is not to chastise the HEJs themselves, but rather the system in which they operate. I just wish that the HEJs would be more willing to take risks in the name of science, and I hope that this is simply a first baby step towards grander and more concrete commitments across the journals. Until then, I will save my praise.

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Posted by on February 9, 2015 in News


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Sofosbuvir: a fork in the road for NICE?

NICE recently completed their appraisal of the hepatitis C drug sofosbuvir. However, as has been reported in the media, NHS England will not be complying with the guidance within the normal time period.

The cost of a 24 week course of sofosbuvir is almost £70,000. Around 160,000 people are chronically infected with the hepatitis C virus in England, so that adds up to a fair chunk of the NHS budget. Yet the drug does appear to be cost-effective. ICERs differ for different patient groups, but for most scenarios the ICER is below £30,000 per QALY. In the NICE documentation, a number of reasons are listed for NHS England’s decision. But what they ultimately boil down to – it seems – is affordability.

The problem is that NICE doesn’t account for affordability in its guidance. One need only consider that the threshold has remained unchanged for over a decade to see that this is true. How to solve this problem really depends on what we believe the job of NICE should be. Should it be NICE’s job to consider what should and shouldn’t be purchased within the existing health budget? Or, rather, should it be NICE’s job simply to figure out what is ‘worth it’ to society, regardless of affordability? This isn’t the first time that an NHS organisation has appealed against a NICE decision in some way. Surely, it won’t be the last. These instances represent a failure in the system, not least on grounds of accountability for reasonableness. Here I’d like to suggest that NICE has 3 options for dealing with this problem; one easy, one hard and one harder.

The easy option

The simplest option involves the fewest changes to the NICE process. Indeed, it would involve doing pretty much what it does now, only with slightly different (and more transparent) reasoning. In this scenario NICE would explicitly ignore the problem of affordability. Its remit would cease to be the consideration of optimality on a national level and it would ignore the budget constraint. NICE’s remit would become figuring out which health technologies are ‘worth it’; i.e. would the public be willing to purchase a given technology with a given health benefit at a given cost. To some extent, therefore, NICE would become a threshold-setter. The threshold should be based on some definition of a social value of a QALY. This is the easy option for NICE as setting the threshold would be the only additional task to what they currently do. Its threshold might not change all that much, or may be a little higher.

However, even if NICE denies responsibility, clearly someone does need to take account of affordability. Given the events associated with sofosbuvir it seems that this could become the work of NHS England. NHS England could use a threshold based on the budget and current QALY-productivity in the NHS. One might expect NHS England to be in a better position to identify the local evidence necessary to determine appropriate thresholds, which would likely be much lower than NICE’s. It would also be responsible for disinvestment decisions. Given the nationwide remit of NHS England, this would still prevent postcode lotteries. The implication here, of course, is that NICE and NHS England might use different thresholds. Any number of decision rules could be used to determine the result for technologies falling between the two. Maybe this is where considerations for innovation or non-health-related equity concerns belong. It seems probable to me that NICE’s threshold would be higher than NHS England’s, in which case NICE would effectively be advising increases in the health budget. This is something that I quite like the sound of.

The hard option

Personally, I believe that NICE’s failure to justify their threshold(s) is quite a serious failing and undermines the enterprise. The hard option will involve them defining it properly, informed by current levels of QALY-productivity in the NHS. Thus properly adopting a position as a threshold-searcher, and doing the job prescribed to NHS England in the ‘easy option’. NICE guidance would therefore be informed by the current health budget and affordability, and therefore must include guidance on disinvestment. The first stage of this work has already been done. The disinvestment guidance would be the hard part. This argument has already been much discussed, and seems to be what many economists support.

I don’t find this argument entirely compelling, at least not as a solution to the affordability problem. To solve this issue NICE would need to regularly review the current threshold and revise it in light of current productivity and the prevailing health budget. It has no experience of doing this. I believe the task could be more effectively carried out by commissioning organisations (such as NHS England), who are in a better position to oversee the collection of the appropriate data and would have a public responsibility to do so. It might also be politically useful if decisions about affordability were made independently of decisions about value.

The harder option

The harder option is for there to be a paradigm shift in the way NICE – and health economics more generally – operates. It could involve programme budgeting and marginal analysis, or the Birch and Gafni approach. This might just be the best option, but it seems unlikely to happen nationally any time soon.

It’s possible that more cost-effective but unaffordable drugs are in the pipeline. Failure to address the affordability problem soon could seriously undermine NICE.

DOI: 10.6084/m9.figshare.1291123


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