Alastair Canaway’s journal round-up for 28th May 2018

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.

Information, education, and health behaviours: evidence from the MMR vaccine autism controversy. Health Economics [PubMed] Published 2nd May 2018

In 1998, Andrew Wakefield published (in the Lancet) his infamous and later retracted research purportedly linking the measles-mumps-rubella (MMR) vaccine and autism. Despite the thorough debunking and exposure of academic skulduggery, a noxious cloud of misinformation remained in the public mind, particularly in the US. This study examined several facets of the MMR fake news including: what impact did this have on vaccine uptake in the US (both MMR and other vaccines); how did state level variation in media coverage impact uptake; and what role did education play in subsequent decisions about whether to vaccinate or not. This study harnessed the National Immunization Survey from 1995 to 2006 to answer these questions. This is a yearly dataset of over 200,000 children aged between 19 to 35 months with detailed information on not just immunisation, but also maternal education, income and other sociodemographics. The NewsLibrary database was used to identify stories published in national and state media relating to vaccines and autism. Various regression methods were implemented to examine these data. The paper found that, unsurprisingly, for the year following the Wakefield publication the MMR vaccine take-up declined by between 1.1%-1.5% (notably less than 3% in the UK), likewise this fall in take-up spilled over into other vaccines take-up. The most interesting finding related to education: MMR take-up for children of college-educated mothers declined significantly compared to those without a degree. This can be explained by the education gradient where more-educated individuals absorb and respond to health information more quickly. However, in the US, this continued for many years beyond 2003 despite proliferation of research refuting the autism-MMR link. This contrasts to the UK where educational link closed soon after the findings were refuted, that is, in the UK, the educated responded to the new information refuting the MMR-Autism link. In the US, despite the research being debunked, MMR uptake was lower in the children of those with higher levels of education for many more years. The author speculates that this contrast to the UK may be a result of the media influencing parents’ decisions. Whilst the media buzz in the UK peaked in 2002, it had largely subsided by 2003. In the US however, the media attention was constant, if not increasing till 2006, and so this may have been the reason the link remained within the US. So, we have Andrew Wakefield and arguably fearmongering media to blame for causing a long-term reduction in MMR take-up in the US. Overall, an interesting study leaning on multiple datasets that could be of interest for those working with big data.

Can social care needs and well-being be explained by the EQ-5D? Analysis of the Health Survey for England. Value in Health Published 23rd May 2018

There is increasing discussion about integrating health and social care to provide a more integrated approach to fulfilling health and social care needs. This creates challenges for health economists and decision makers when allocating resources, particularly when comparing benefits from different sectors. NICE itself recognises that the EQ-5D may be inappropriate in some situations. With the likes of ASCOT, ICECAP and WEMWBS frequenting the health economics world this isn’t an unknown issue. To better understand the relationship between health and social care measures, this EuroQol Foundation funded study examined the relationship between social care needs as measured by the Barthel Index, well-being measured using WEMWBS and also the GGH-12, and the EQ-5D as the measure of health. Data was obtained through the Health Survey for England (HSE) and contained 3354 individuals aged over 65 years. Unsurprisingly the authors found that higher health and wellbeing scores were associated with an increased probability of no social care needs. Those who are healthier or at higher levels of wellbeing are less likely to need social care. Of all the instruments, it was the self-care and the pain/discomfort dimensions of the EQ-5D that were most strongly associated with the need for social care. No GHQ-12 dimensions were statistically significant, and for the WEMWBS only the ‘been feeling useful’ and ‘had energy to spare’ were statistically significantly associated with social care need. The authors also investigated various other associations between the measures with many unsurprising findings e.g. EQ-5D anxiety/depression dimension was negatively associated with wellbeing as measured using the GHQ-12. Although the findings are favourable for the EQ-5D in terms of it capturing to some extent social care needs, there is clearly still a gap whereby some outcomes are not necessarily captured. Considering this, the authors suggest that it might be appropriate to strap on an extra dimension to the EQ-5D (known as a ‘bolt on’) to better capture important ‘other’ dimensions, for example, to capture dignity or any other important social care outcomes. Of course, a significant limitation with this paper relates to the measures available in the data. Measures such as ASCOT and ICECAP have been developed and operationalised for economic evaluation with social care in mind, and a comparison against these would have been more informative.

The health benefits of a targeted cash transfer: the UK Winter Fuel Payment. Health Economics [PubMed] [RePEc] Published 9th May 2018

In the UK, each winter is accompanied by an increase in mortality, often known as ‘excess winter mortality’ (EWM). To combat this, the UK introduced the Winter Fuel Payment (WFP), the purpose of the WFP is an unconditional cash transfer to households containing an older person (those most vulnerable to EWM) above the female state pension age with the intent for this to used to help the elderly deal with the cost of keeping their dwelling warm. The purpose of this paper was to examine whether the WFP policy has improved the health of elderly people. The authors use the Health Surveys for England (HSE), the Scottish health Survey (SHeS) and the English Longitudinal Study of Ageing (ELSA) and employ a regression discontinuity design to estimate causal effects of the WFP. To measure impact (benefit) they focus on circulatory and respiratory illness as measured by: self-reports of chest infection, nurse measured hypertension, and two blood biomarkers for infection and inflammation. The authors found that for those living in a household receiving the payment there was a 6% point reduction (p<0.01) in the incidence of high levels of serum fibrinogen (biomarker) which are considered to be a marker of current infection and are associated with chronic pulmonary disease. For the other health outcomes, although positive, the estimated effects were less robust and not statistically significant. The authors investigated the impact of increasing the age of eligibility for the WFP (in line with the increase of women’s pension age). Their findings suggest there may be some health cost associated with the increase in age of eligibility for WFP. To surmise, the paper highlights that there may be some health benefits from the receipt of the WFP. What it doesn’t however consider is opportunity cost. With WFP costing about £2 billion per year, as a health economist, I can’t help but wonder if the money could have been better spent through other avenues.



Erik Tollefson’s journal round-up for 13th June 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.

A general method for decomposing the causes of socioeconomic inequality in health. Journal of Health Economics [PubMed] Published 7th April 2016

In this paper, Heckley, Gerdtham, and Kjellsson establish a new methodology for decomposing the causes of socioeconomic inequality in health. Currently, versions of the concentration index, using bivariate rank dependent indices, play a dominant methodological role. The index depends on a bivariate calculation assigning a negative (positive) value to an individual’s cumulative health and socioeconomic rank. The WDW method, developed by Wagstaff, is the main decomposition method to understand potential causes of a change in the index. Decomposition methods for the index face several limitations.  The main limitation is that although the bivariate rank index are two-dimensional indices that consider the covariance between health and rank, the decomposition method is only one-dimensional looking at health but not rank. Thus, it is difficult to understand what the parameters are for identification; decomposition has become an exercise in accounting rather than explanation. The authors propose a new decomposition method that aims to explain the causes of socioeconomic inequality by looking directly at the health and socioeconomic rank that composes the index. The authors apply RIF regression to accomplish this, deriving RIF for a general bivariate rank index. The decomposition method is thus able to explain potential causes of socioeconomic inequality by directly decomposing the weighted covariance of health and socioeconomic rank.

Understanding the improvement in disability free life expectancy in the US elderly population. NBER Working Paper [RePEcPublished June 2016

In this working paper, Chernew, Cutler, Ghosh, and Landrum explore two key questions. First, how have life expectancy disability-free lifespans changed in the US population in the elderly cohort (over the age of 65)? Second, what is responsible for the extension (diminution) of longevity and disability-free lifespans? In order to answer these questions, the authors build off previous work in which they used secondary mortality data and primary survey data to estimate the trajectory of longevity and disability-free living.  They extend the previous data, which ended in 2005, up to 2008 in the paper, finding that both longevity and disability-free living has increased over time. The authors then assess which medical conditions are (causally) responsible for the greatest additions to disability-free life expectancy through decomposing mortality and disability into fifteen different conditions (inclusive of acute and chronic diseases). The paper finds that the largest gains in disability-free years are due to improvements in two areas: cardiovascular disease and vision problems. Finally, the authors create a model to explore what percentage the improvement in these conditions is due to health care interventions. The authors use the IMPACT model to estimate that health care accounts for 50% of disability-free living in cardiovascular health and cataract surgery accounts for 25% improvement in disability free living for vision problems. Overall, the paper provides useful data looking at not only why longevity and disability-free lifespans are increasing, but also what percentage is due to health interventions versus social factors. Although the results of the causal contribution of health care are provisional they provide an interesting methodological window, particularly in the United States, to understand which medical procedures provide the greatest value for elderly beneficiaries.

Global differences in cancer drug prices: a comparative analysis. Journal of Clinical Oncology Published June 2016

Increasing public attention is paid to prices of cancer drugs. This is not only true in developed countries where access to expensive cancer drugs can be prohibitive, but also in developing countries where access to cancer drugs generally and generic cancer drugs specifically is an emerging problem. In this study, the authors looked at the differences of (listed) cancer drug prices for 23 cancer drugs (15 of which are available generically) across five continents and six countries: Australia, China, India, South Africa, United Kingdom, and the United States. The study estimated the price of the drugs on a monthly basis as a percentage of the respective country’s per-capita GDP. Overall, the study found tremendous variation in prices of cancer drugs, with greater affordability in developed countries compared to developing or poorer countries. This study is quite useful in providing a data-driven analysis of cancer drug prices. The public debate in developed countries on cancer drug prices is often times hijacked by two rhetorical extremes: drug companies touting the benefits of innovative therapies on the one hand and advocates calling for price guidance (controls) on the other hand. Little attention (and data) is available for cancer pricing, especially in developing countries. This study provides an excellent foundation for cross-country pricing comparisons, but could be improved by correcting for differences between listed prices and actually paid prices, as well as adjusting for differences in health insurance coverage across countries. Including drug access measures as part of a greater cancer drugs index would also help to understand drug availability.

The ethics of doing nothing

Can we reasonably consider ‘doing nothing’ as an alternative course of action? In many cost-effectiveness analyses the intervention under consideration is compared against a ‘doing nothing’ scenario, although frequently the next best alternative is used. Ultimately the health technology assessment carried out by NICE is an informative effort and the final decision is made by the budget holder. However, NICE makes each assessment in isolation of each other and so prioritising treatments is left to the budget holder. But can the budget holder choose a ‘do nothing’ option, and should this option be considered at all in cost-effectiveness analysis?

This may come down to an issue on the role of the health care system in general. One of the principle tenets of NICE and the NHS is justice (the others being beneficence, non-maleficence, and autonomy). This NHS justice, it seems, is a sense of justice as described by John Rawls – justice as fairness. Justice as fairness is founded on two points – liberty and equality, that everyone should have the same right to basic liberties, and that inequalities should be arranged to benefit the worst off in society to ensure distributive justice. Both of these principles are satisfied by the idea of access to health care based on need and regardless of ability to pay.

We use cost-effectiveness analysis to best allocate resources, so that we all get the greatest gain for our limited resources, but that does not necessarily ensure that the worst off get priority.

In the end it comes down to a deontologism versus consequentialism debate. Deontologism dictates that there are certain moral rules that must be followed, or as Kant described them ‘categorical imperatives’, and these rules can be reached through logical reasoning and must be universal. In this case, for example, if doing nothing were universally permissible for health care professionals then it would be permissible for no-one to be treated which would negate the existence of the health care professional in the first place. So, if we say that all those with needs must be treated, this may be a deontological stance. However, we do not provide services for all those with needs, and it may be practically impossible to do so. Health care provision is proportional to need, but those with the least needs generally have to pay for their own services, unless they are sufficiently poor, for example, dentistry.

Now, if we consider health care provision to be philosophically consequentialist, can we allow a ‘do nothing’ option? Many thought experiments exist to exercise consequentialist ethics. Consider a runaway train, it’s careering down the track towards a station in which there are ten people who will die if the train gets there, you are on the train and have the option to switch tracks to divert the train away from the station. However, there are three men working on the line on the other track who will die if you pull the lever. Do you pull the lever? One argument, the utilitarian one, would say yes. The total loss would be smaller on the other track, we would therefore be maximising the total utility from the situation. Another argument may say though that not pulling the lever is the only option since if you did the deaths of the three men would be your responsibility but in doing nothing you would be morally neutral. This is a form of egoistic consequentialism. Under both these arguments a health care provider could do nothing, in the first case if utility was maximised by treating others and in the second case because the health care provider is not morally responsible for a person’s health care state in the first place.

There are objections to this line of reasoning. Peter Singer describes a situation to illustrate an objection to this. Imagine you are walking home one day. As you walk you pass a pond in which a child is drowning. The pond is not very deep and you could walk in and save the child, bearing no tangible risk to your own life. In this case the choice of inaction would lead to the child’s death, and you surely could be held responsible for that. The choice of doing nothing, then, does not negate responsibility. Moreover, if the budget holder is the government, there are certainly arguments which may attribute to them a certain responsibility for poor health in the population (consider the relationship between the macroeconomy and health).

The key issue that remains is opportunity cost. The only reasonable argument for doing nothing is that the time and resources could be better spent elsewhere, and cost-effectiveness analysis provides us with the information to know where it is best spent. However, in reality, no patient would be left to die if they turned up to a hospital and could be saved, and many adult intensive care units intervene in ways that are not cost-effective as per the NICE definition. The end of life is the most difficult to deal with, research has shown that people value a change from 0.2-0.4 QALYs more than they value a change from 0.6-0.8 QALYs. Many expensive life prolonging cancer drugs are not funded by the NHS, but there are cases of successful lobbying to have these drugs reimbursed despite their lack of cost-effectiveness. This could lead us to conclude that doing nothing is fine as long as it does not kill the patient (or allow the patient to die, depending on your stance) in which case we should always intervene. It is unfair to ask a health care professional not to act, since, as detailed, it is their responsibility if their patient dies through inaction.

For the most part, everybody is provided with the necessary treatment when they are in need. It’s really only at the end of life the problem of opportunity cost is apparent due to the high cost of interventions. Perhaps the answer lies in allowing NICE to negotiate the price of drugs, although this would not necessarily lead to price reductions since companies would be incentivised to pitch drugs at an even higher price knowing that they will be negotiated down to their acceptable price. To the contrary though it may be argued that this constitutes inaction on the part of NICE, and by negotiating (or at least trying to) they could allow more people to survive. Another issue is that the few months that are gained by (usually expensive) end of life treatment are usually in very poor quality. From an Aristotelian perspective this would not be a virtuous choice, as we would not be achieving ‘the good life’, and what’s more, Aristotle says, no-one would actually choose this state of suffering unless they were defending a philosophical position.

In the end we may defend ‘doing nothing’ as a choice as it may be necessary in the face of opportunity cost, and it is always better to know the outcomes from as many scenarios as possible when modelling it in simulation based studies. However, in practice ‘doing nothing’ may not be realisable, since the fear of death may prohibit people from accepting this option. Perhaps there is a case for allocating more resources to health care from other areas of public spending, which there certainly is a case for. What would be ideal would be a quantifiable way of measuring the benefit from all government spending and then choosing the health care budget based on this. But this is definitely a long way from reality.