Brendan Collins’s journal round-up for 22nd July 2019

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.

Making hard choices in local public health spending with a cost-benefit analysis approach. Frontiers in Public Health Published 29th June 2019

In this round-up I have chosen three papers which look broadly at public health economics.

While NHS healthcare funding has been relatively preserved in the UK (in financial terms at least, though not keeping up with demographic change), funding for local government public health departments has been cut. These departments commission early years services, smoking cessation, drug and alcohol treatment, sexual health, and lots of other services. A recent working paper suggests that marginal changes in Public Health funding produce a more favourable ICER than changes in NHS funding.

This is a neat paper looking at the cost-benefit for a subset of £14 million investment in public health programmes in Dorset, a county on the south coast of England, whose population is slightly older and more affluent than the England average. I try to go to Dorset every year, it has beautiful beaches with traditional Punch and Judy shows, and nice old towns where you can get out on a mackerel fishing trip.

This paper looks at the potential financial savings for each public health programme across different sectors of the economy. One of the big issues with public health as opposed to clinical interventions is the cross sector flow problem – you spend money on drug and alcohol treatment, but the majority of benefits are through prevented crime; or you prevent teenage pregnancy, and a lot of the benefits are to the welfare system (because women delay pregnancy until they are more likely to be in a stable relationship and working). This makes it hard when local councillors might say, ‘what’s in it for us?’

Figure 2 in this paper shows the cross sector flow issue clearly – the spend comes from local authority public health, but 94% of the financial benefits are in the NHS.

I think this study has a good blueprint that other local authorities could follow. The study applies an optimism bias reduction, so it is not just assuming that programmes will be as effective as the research evidence suggests. This is important as there may be a big drop off in effectiveness when something is implemented locally. Of course, sometimes local implementation might be more effective. But it would be nice to see this kind of study carried out with more real-world data. Although the optimism bias reduction makes it less likely to overestimate the cost-benefit, it doesn’t necessarily make the estimate any more precise. National outcomes data collection for public health programmes is weak or absent; better data collection might mean more evidence that prevention interventions provide value for money.

Impact of sugar‐sweetened beverage taxes on purchases and dietary intake: systematic review and meta‐analysis. Obesity Reviews [PubMed] Published 19th June 2019

A lot of health economics focuses on healthcare interventions. But, upstream, structural policy interventions have the capacity to be a lot more cost effective in preventing ill health. Sugary drinks (sugar sweetened beverages – SSBs) are a source of excess empty calories and increase the risk of cardiovascular disease, diabetes and early death. One of the first pieces of work I did as a grown-up academic was looking at a sugary drinks tax, which resulted in me getting up early one day and seeing this. At the time I thought it had roughly zero chance of being implemented. But the sugary drinks industry levy (SDIL) was implemented in the UK in April last year, and had a huge effect in terms of motivating the industry to reformulate below the thresholds of 5g and 8g of sugar per 100ml. Milk-based drinks like Frijj and Yazoo are exempt and still often have nearly 10g sugar per 100ml so there has been talk of extending the tax to these drinks. But Boris Johnson, the likely next UK Prime Minister, has come out against these ‘nanny state’ ‘sin taxes’ and said he will review them, seemingly despite there being a large scale evaluation of the SDIL, and a growing evidence base. There is a good twitter thread on this by Adam Briggs here.

Policies like the SDIL rely on price elasticity of demand (PED). But this PED varies depending, for instance, on how addictive something is and the availability of substitutes. For tobacco, because it is addictive, a 10% price increase might only produce a 5% reduction in demand.

This systematic review and meta-analysis looked at data from 17 studies in 6 jurisdictions and found that, on average, sugar consumption is unit elastic – a 10% price increase produces a 10% reduction in purchases. However, there was considerable variation between studies. The authors designed a bespoke risk of bias tool for this, as the traditional tools used for health interventions did not include all of the potential biases for an SSB tax evaluation; this checklist may be useful for future analyses of similar policies.

If the SSB duty produced a unit elastic response in the UK, it means that people aren’t spending more on SSBs, they are merely buying less of something that they don’t need and which damages their health. And maybe a few people, over many years, consume a bit less sugar, don’t get type 2 diabetes, don’t have to give up work, and are actually better off and can provide for their families for a bit longer. Of course, in the UK the picture is complex because of the different tiers of the duty, but reformulation has meant that people are consuming less sugar even if they don’t reduce their sugary drink consumption. Also, the revenue from the SDIL is spent on healthier schools, so it could be argued that the policy is a win-win.

The cost of not breastfeeding: global results from a new tool. Health Policy & Planning [PubMed] Published 24th June 2019

This study looks at the potential worldwide cost savings if breastfeeding rates were improved. Breastfeeding prevents cases of diarrhoea, obesity, maternal cancer, and other diseases and adverse outcomes. Low breastfeeding rates are a big problem in developing countries where formula costs a huge proportion of income (nearly 20% of average household income in India and Pakistan according to this paper) and water supplies may be contaminated. This study includes healthcare costs, and economic losses from early deaths and reduced IQ through sub-optimal breastfeeding, which total $341 billion per year worldwide.

The authors have said there is also going to be an online, and Excel-based, results tool.

I love reading such ambitious studies that cover the whole world. Producing worldwide estimates for costs is a difficult exercise and can have a danger of losing meaning. For instance, in developing countries, medical costs may be very low if health coverage is very sparse. If a country doesn’t spend anything on healthcare and you measure public health interventions in healthcare cost savings, then it looks like these public health interventions are not worth doing. That is why it is sometimes better to focus on DALYs (and potentially put a financial value on them, although this can be controversial) rather than financial costs. The study found the biggest absolute costs of not breastfeeding were in North America ($115bn), while biggest costs as a proportion of gross national income (GNI) were for sub-Saharan Africa, where not breastfeeding cost 2.6% of GNI.

It looks like two out of the three authors are men. Is there a problem with men being pro-breastfeeding? Why should a man tell women what to do with their bodies? Women shouldn’t feel stigmatised about their infant feeding choices. But for me it is not about telling women what to do. It is making sure the structures and social norms are there to support breastfeeding and that formula companies are regulated in how they market themselves and their products. Maybe men not caring enough about breastfeeding is what has got us to where we are now. 

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Chris Gibbons’s journal round-up for 1st July 2019

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 economic case for the prevention of mental illness. Annual Review of Public Health [PubMed] [RePEc] Published April 2019

I’m a big fan of these annual reviews in public health, partly because they provide a really useful overview of a topic and plenty of links for further reading, but mostly because what they don’t contain usually ends up being a really good back and forth in our office that ends with strategising about what we could do better, locally, to inform the delivery of services. So it was with this article, which does a pretty comprehensive job of setting out the economic case for prevention of mental illness, but also makes the case for framing arguments in an economic context using health economics evidence rather than burden of morbidity alone.

The article is structured across several domains based on where there is both quantity and quality of studies, but also makes clear that the natural history of mental health problems and the intervention opportunities to prevent them occur across the entire life course (which will please local authorities who have adopted a life-course approach to health and wellbeing). There is a short section on the barriers to implementation of programmes to prevent mental illness despite the evidence of their effectiveness. One of the suggested solutions is to make use of economic models to highlight short-, mid-, and long-term costs and benefits of prevention, which is OK as far as it goes. I think that one of the biggest barriers with this kind of evidence is the challenge of communicating it to commissioners and decision makers in local authorities, who are far less familiar with health economic methods and approaches than colleagues in health. Modelling is often viewed as a dark art that is impenetrable and difficult to trust, and you cannot fix that by developing more models. I was also surprised at the lack of discussion of the growing evidence of physical health inequalities in people with mental health conditions compared to the general population, which manifests in stark contrasts in healthy life expectancy between these groups and oftentimes differences in underlying health behaviours such as smoking, alcohol consumption and self-medication.

The health effects of Sure Start. Report by the Institute for Fiscal Studies Published 3rd June 2019

Sure Start offers families with children under the age of 5 a ‘one-stop shop’ for childcare and early education, health services, parenting support, and employment advice, with the aim of improving children’s school readiness, health, and social and emotional development. Sure Start is not a new programme and has considerable history of implementation and funding from initial targeting of deprived areas, through to universal provision via the 10-year Strategy for Childcare, with £1.8 billion of public investment. The last ten years have seen substantial cuts and rationalisation with a reduction of funding in the order of 33%. The IFS report is interesting because it stands out as one of the vanishingly small bits of evaluative evidence into the programme’s effectiveness and cost effectiveness, and because early reviews of Sure Start were contradictory in their findings about whether health benefits were being delivered.

The IFS report uses ‘big data’ in an ecological study framework that tracked, spatially and temporally, access to Sure Start centres (which varied within and between neighbourhoods and nationwide from one year to the next) and cross-referenced health data and outcomes for children and their mothers who accessed the service. Using a difference-in-differences methodology, the IFS compared the outcomes of children in the same neighbourhood with more or less access to Sure Start, after accounting for both permanent differences between neighbourhoods and nationwide differences between years.

The results suggest that Sure Start reduced the likelihood of hospital admissions for children of primary school age, and that there was a persistence to this benefit which increased with age, so a 5% reduction in probability at age 5 became an 18% reduction by age 11. For the younger kids, the admissions avoided were largely those associated with infections, whilst for older kids it was a reduction in admissions for injuries. From an inequalities standpoint, the poorest 30% of areas saw the probability of any hospitalisation fall by 11% at age 10 and 19% at age 11. Those in more affluent neighbourhoods saw smaller benefits, and those in the richest 30% of neighbourhoods saw practically no impact at all. There were no recorded benefits to maternal mental health, or to childhood obesity by age 5.

In a simple cost-benefit analysis, Sure Start was able to offset 6% of its programme costs through NHS savings. For me, this is the most disappointing aspect of the report, and perhaps the most misleading. I think it is a disservice to Sure Start that the benefits were evaluated through a very narrow resource utilisation view of ‘health’ as health care. So much of the rationale for setting up Sure Start and the policy narratives along the way have been grounded in a much wider definition of health and the view on the ground is that Sure Start has impacted many more ‘softer’ (but no less important) outcomes. I hope there will be parallel reports on the impact of Sure Start on school readiness, educational attainment, crime, adverse childhood experiences, employment and the economy. If not I worry that this evaluation from a value for money perspective could be used by Whitehall to justify further cuts.

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Simon McNamara’s journal round-up for 24th June 2019

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.

Manipulating the 5 dimensions of the EuroQoL instrument: the effects on self-reporting actual health and valuing hypothetical health states. Medical Decision Making [PubMed] Published 4th June 2019

EQ-5D is the Rocky Balboa of health economics. A left-hook here, a jab there, vicious undercuts straight to the chin – it takes the hits, it never stays down. Every man and his dog is ganging up on it, yet, it still stands, proudly resolute in its undefeated record.

When you are the champ” it thinks to itself, “everyone wants a piece you”. The door opens. Out the darkness emerges four mysterious figures. “No… not…”, the instrument stumbles over its words. A bead of sweat rolls slowly down its glistening forehead. Its thumping heartbeat pierces the silence like a drum being thrashed by spear-wielding members of an ancient tribe. “It can’t beNo.” A clear, precise, voice emerges from the darkness, “taken at face value” it states, “our results suggest that economic evaluations that use EQ-5D-5L are systematically biased.” EQ-5D stares blankly, its pupils dilated. It responds, “I’ve been waiting for you”. The gloom clears. Tsuchiya et al (2019) stand there proudly: “bring it on… punk”.

The first paper in this week’s round-up is a surgical probing of a sample of potential issues with EQ-5D. Whilst the above paragraph contains a fair amount of poetic license (read: this is the product of an author who would rather be writing dystopian health-economics short stories than doing their actual work), this paper by Tsuchiya et al. does seems to land a number of strong blows squarely on the chin of EQ-5D. The authors employ a large discrete choice experiment (n=2,494 members of the UK general public), in order to explore the impact of three issues on the way people both report and value health. Specifically: (1) the order the five dimensions are presented; (2) the use of composite dimensions (dimensions that pool two things – e.g. pain or discomfort) rather than separate dimensions; (3) “bolting-off” domains (the reverse of a bolt-on: removing domains from the EQ-5D).

If you are interested in these issues, I suggest you read the paper in full. In brief, the authors find that splitting anxiety/depression into two dimensions had a significant effect on the way people reported their health; that splitting level 5 of the pain/discomfort and anxiety/depression dimensions (e.g. I have extreme pain or discomfort) into individual dimensions significantly impacted the way people valued health; and, that “bolting off” dimensions impacted valuation of the remaining dimensions. Personally, I think the composite domain findings are most interesting here. The authors find that that extreme pain/discomfort is perceived as being a more severe state than extreme discomfort alone, and similarly, that being extremely depressed/anxious is perceived as a more severe state than simply being extremely anxious. The authors suggest this means the EQ-5D-5L may be systematically biased, as an individual who reports extreme discomfort (or anxiety) will have their health state valued based upon the composite domains for each of these, and subsequently have the severity of their health-state over-estimated.

I like this paper, and think it has a lot to contribute to the refinement of EQ-5D, and the development of new instruments. I suggest the champ uses Tsuchiya et al as a sparring partner, gets back to the gym and works on some new moves – I sense a training montage coming on.

Methods for public health economic evaluation: A Delphi survey of decision makers in English and Welsh local government. Health Economics [PubMed] Published 7th June 2019

Imagine the government in your local city is considering a major new public health initiative. Politicians plan to destroy a number of out of date social housing blocks in deprived communities, and building 10,000 new high-quality homes in their place. This will cost a significant amount of money and, as a result, you have been asked to do an economic evaluation of this intervention. How would you go about doing this?

This is clearly a complicated task. You are unlikely to find a randomised controlled trial on which to base your evaluation, the costs and benefits of the programme are likely to fall on multiple sectors, and you will likely have to balance health gains with a wide range of other non-health outcomes (e.g. reductions in crime). If you somehow managed to model the impact of the intervention perfectly, you would then be faced with the challenge of how to value these benefits. Equally, you would have to consider whether or not to weight the benefits of this programme more highly than programmes in alternative parts of the city, because it benefits people in deprived communities – note that inequalities in health seem to be a much larger issue in public health than in ‘normal health’ (e.g. the bread and butter of health economics evaluation). This complexity, and concern for inequalities, makes public health economic evaluation a completely different beast to traditional economic evaluation. This has led some to question the value of QALY-based cost-utility analysis in public health, and to calls for methods that better meet the needs of the field.  

The second paper in this week’s round-up contributes to the development of these methods, by providing information on what public health decision makers in England and Wales think about different economic evaluation methodologies. The authors fielded an online, two-round, Delphi-panel study featuring 26 to 36 statements (round 1 and 2 respectively). For each statement, participants were asked to rank their level of agreement with the statement on a five-point scale (e.g. 1 = strongly agree and 5 = strongly disagree). In the first round, participants (n=66) simply responded to the statements, and in the second, they (n=29) were presented with the median response from the prior round, and asked to consider their response in light of this feedback. The statements tested covered a wide range of issues, including: the role distributional concerns should play in public health economic evaluation (e.g. economic evaluation should formally weight outcomes by population subgroup); the type of outcomes considered (e.g. economic evidence should use a single outcome that captures length of life and quality of life); and, the budgets to be considered (e.g. economic evaluation should take account of multi-sectoral budgets available).

Interestingly, the decision-makers rejected the idea of focusing solely on maximising outcomes (the current norm for health economic evaluations), and supported placing an equal focus on minimising inequality and maximising outcomes. Furthermore, they supported formal weighting of outcomes by population subgroup, the use of multiple outcomes to capture health, wellbeing and broader outcomes, and failed to support use of a single outcome that captures well-being gain. These findings suggest cost-consequence analysis may provide a better fit to the needs of these decision makers than simply attempting to apply the QALY model in public health – particularly if augmented by some form of multi-criteria decision analysis (MCDA) that can reflect distributional concerns and allow comparison across outcome types. I think this is a great paper and expect to be citing it for years to come.

I AM IMMORTAL. Economic Enquiry [RePEc] Published 16th November 2016

I love this paper. It isn’t a recent one, but it hasn’t been covered in the AHE blog before, and I think everyone should know about it, so – luckily for you – it has made it in to this week’s round-up.

In this groundbreaking work, Riccardo Trezzi fits a series of “state of the art”, complex, econometric models to his own electrocardiogram (ECG) signal – a measure of the electrical function of the heart. He then compares these models, identifies the one that best fits his data, and uses the model to predict his future ECG signal, and subsequently his life expectancy. This provides an astonishing result  – “the n steps ahead forecast remains bounded and well above zero even after one googol period, implying that my life expectancy tends to infinite. I therefore conclude that I am immortal”.

I think this is genius. If you haven’t already realised the point of the paper by the time you have reached this part of my write-up, I suggest you think very carefully about the face-validity of this result. If you still don’t get it after that, have a look at the note on the front page – specifically the bit that says “this paper is intended to be a joke”. If you still don’t get it – the author measured their heart activity for 10 seconds, and then applied lots of complex statistical methods, which (obviously) when extrapolated suggested his heart would keep beating forever, and subsequently that he would live forever.

Whilst the paper is a parody, it makes an important point. If we fit models to data, and attempt to predict the future without considering external evidence, we may well make a hash of that prediction – despite the apparent sophistication of our econometric methods. This is clearly an extreme example, but resonates with me, because this is what many people continue to do when modelling oncology data. This is certainly less prevalent than it was a few years ago, and I expect it will become a thing of the past, but for now, whenever I meet someone who does this, I will be sure to send them a copy of this paper. That being said, as far as I am aware the author is still alive, so maybe he will have the last laugh – perhaps even the last laugh of all of humankind if his model is to be believed.

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