Chris Sampson’s journal round-up for 11th June 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.

End-of-life healthcare expenditure: testing economic explanations using a discrete choice experiment. Journal of Health Economics Published 7th June 2018

People incur a lot of health care costs at the end of life, despite the fact that – by definition – they aren’t going to get much value from it (so long as we’re using QALYs, anyway). In a 2007 paper, Gary Becker and colleagues put forward a theory for the high value of life and high expenditure on health care at the end of life. This article sets out to test a set of hypotheses derived from this theory, namely: i) higher willingness-to-pay (WTP) for health care with proximity to death, ii) higher WTP with greater chance of survival, iii) societal WTP exceeds individual WTP due to altruism, and iv) societal WTP may exceed individual WTP due to an aversion to restricting access to new end-of-life care. A further set of hypotheses relating to the ‘pain of risk-bearing’ is also tested. The authors conducted an online discrete choice experiment (DCE) with 1,529 Swiss residents, which asked respondents to suppose that they had terminal cancer and was designed to elicit WTP for a life-prolonging novel cancer drug. Attributes in the DCE included survival, quality of life, and ‘hope’ (chance of being cured). Individual WTP – using out-of-pocket costs – and societal WTP – based on social health insurance – were both estimated. The overall finding is that the hypotheses are on the whole true, at least in part. But the fact is that different people have different preferences – the authors note that “preferences with regard to end-of-life treatment are very heterogeneous”. The findings provide evidence to explain the prevailing high level of expenditure in end of life (cancer) care. But the questions remain of what we can or should do about it, if anything.

Valuation of preference-based measures: can existing preference data be used to generate better estimates? Health and Quality of Life Outcomes [PubMed] Published 5th June 2018

The EuroQol website lists EQ-5D-3L valuation studies for 27 countries. As the EQ-5D-5L comes into use, we’re going to see a lot of new valuation studies in the pipeline. But what if we could use data from one country’s valuation to inform another’s? The idea is that a valuation study in one country may be able to ‘borrow strength’ from another country’s valuation data. The author of this article has developed a Bayesian non-parametric model to achieve this and has previously applied it to UK and US EQ-5D valuations. But what about situations in which few data are available in the country of interest, and where the country’s cultural characteristics are substantially different. This study reports on an analysis to generate an SF-6D value set for Hong Kong, firstly using the Hong Kong values only, and secondly using the UK value set as a prior. As expected, the model which uses the UK data provided better predictions. And some of the differences in the valuation of health states are quite substantial (i.e. more than 0.1). Clearly, this could be a useful methodology, especially for small countries. But more research is needed into the implications of adopting the approach more widely.

Can a smoking ban save your heart? Health Economics [PubMed] Published 4th June 2018

Here we have another Swiss study, relating to the country’s public-place smoking bans. Exposure to tobacco smoke can have an acute and rapid impact on health to the extent that we would expect an immediate reduction in the risk of acute myocardial infarction (AMI) if a smoking ban reduces the number of people exposed. Studies have already looked at this effect, and found it to be large, but mostly with simple pre-/post- designs that don’t consider important confounding factors or prevailing trends. This study tests the hypothesis in a quasi-experimental setting, taking advantage of the fact that the 26 Swiss cantons implemented smoking bans at different times between 2007 and 2010. The authors analyse individual-level data from Swiss hospitals, estimating the impact of the smoking ban on AMI incidence, with area and time fixed effects, area-specific time trends, and unemployment. The findings show a large and robust effect of the smoking ban(s) for men, with a reduction in AMI incidence of about 11%. For women, the effect is weaker, with an average reduction of around 2%. The evidence also shows that men in low-education regions experienced the greatest benefit. What makes this an especially nice paper is that the authors bring in other data sources to help explain their findings. Panel survey data are used to demonstrate that non-smokers are likely to be the group benefitting most from smoking bans and that people working in public places and people with less education are most exposed to environmental tobacco smoke. These findings might not be generalisable to other settings. Other countries implemented more gradual policy changes and Switzerland had a particularly high baseline smoking rate. But the findings suggest that smoking bans are associated with population health benefits (and the associated cost savings) and could also help tackle health inequalities.


Chris Sampson’s journal round-up for 19th March 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.

Using HTA and guideline development as a tool for research priority setting the NICE way: reducing research waste by identifying the right research to fund. BMJ Open [PubMed] Published 8th March 2018

As well as the cost-effectiveness of health care, economists are increasingly concerned with the cost-effectiveness of health research. This makes sense, given that both are usually publicly funded and so spending on one (in principle) limits spending on the other. NICE exists in part to prevent waste in the provision of health care – seeking to maximise benefit. In this paper, the authors (all current or ex-employees of NICE) consider the extent to which NICE processes are also be used to prevent waste in health research. The study focuses on the processes underlying NICE guideline development and HTA, and the work by NICE’s Science Policy and Research (SP&R) programme. Through systematic review and (sometimes) economic modelling, NICE guidelines identify research needs, and NICE works with the National Institute for Health Research to get their recommended research commissioned, with some research fast-tracked as ‘NICE Key Priorities’. Sometimes, it’s also necessary to prioritise research into methodological development, and NICE have conducted reviews to address this, with the Internal Research Advisory Group established to ensure that methodological research is commissioned. The paper also highlights the roles of other groups such as the Decision Support Unit, Technical Support Unit and External Assessment Centres. This paper is useful for two reasons. First, it gives a clear and concise explanation of NICE’s processes with respect to research prioritisation, and maps out the working groups involved. This will provide researchers with an understanding of how their work fits into this process. Second, the paper highlights NICE’s current research priorities and provides insight into how these develop. This could be helpful to researchers looking to develop new ideas and proposals that will align with NICE’s priorities.

The impact of the minimum wage on health. International Journal of Health Economics and Management [PubMed] Published 7th March 2018

The minimum wage is one of those policies that is so far-reaching, and with such ambiguous implications for different people, that research into its impact can deliver dramatically different conclusions. This study uses American data and takes advantage of the fact that different states have different minimum wage levels. The authors try to look at a broad range of mechanisms by which minimum wage can affect health. A major focus is on risky health behaviours. The study uses data from the Behavioral Risk Factor Surveillance System, which includes around 300,000 respondents per year across all states. Relevant variables from these data characterise smoking, drinking, and fruit and vegetable consumption, as well as obesity. There are also indicators of health care access and self-reported health. The authors cut their sample to include 21-64-year-olds with no more than a high school degree. Difference-in-differences are estimated by OLS according to individual states’ minimum wage changes. As is often the case for minimum wage studies, the authors find several non-significant effects: smoking and drinking don’t seem to be affected. Similarly, there isn’t much of an impact on health care access. There seems to be a small positive impact of minimum wage on the likelihood of being obese, but no impact on BMI. I’m not sure how to interpret that, but there is also evidence that a minimum wage increase leads to a reduction in fruit and vegetable consumption, which adds credence to the obesity finding. The results also demonstrate that a minimum wage increase can reduce the number of days that people report to be in poor health. But generally – on aggregate – there isn’t much going on at all. So the authors look at subgroups. Smoking is found to increase (and BMI decrease) with minimum wage for younger non-married white males. Obesity is more likely to be increased by minimum wage hikes for people who are white or married, and especially for those in older age groups. Women seem to benefit from fewer days with mental health problems. The main concerns identified in this paper are that minimum wage increases could increase smoking in young men and could reduce fruit and veg consumption. But I don’t think we should overstate it. There’s a lot going on in the data, and though the authors do a good job of trying to identify the effects, other explanations can’t be excluded. Minimum wage increases probably don’t have a major direct impact on health behaviours – positive or negative – but policymakers should take note of the potential value in providing public health interventions to those groups of people who are likely to be affected by the minimum wage.

Aligning policy objectives and payment design in palliative care. BMC Palliative Care [PubMed] Published 7th March 2018

Health care at the end of life – including palliative care – presents challenges in evaluation. The focus is on improving patients’ quality of life, but it’s also about satisfying preferences for processes of care, the experiences of carers, and providing a ‘good death’. And partly because these things can be difficult to measure, it can be difficult to design payment mechanisms to achieve desirable outcomes. Perhaps that’s why there is no current standard approach to funding for palliative care, with a lot of variation between countries, despite the common aspiration for universality. This paper tackles the question of payment design with a discussion of the literature. Traditionally, palliative care has been funded by block payments, per diems, or fee-for-service. The author starts with the acknowledgement that there are two challenges to ensuring value for money in palliative care: moral hazard and adverse selection. Providers may over-supply because of fee-for-service funding arrangements, or they may ‘cream-skim’ patients. Adverse selection may arise in an insurance-based system, with demand from high-risk people causing the market to fail. These problems could potentially be solved by capitation-based payments and risk adjustment. The market could also be warped by blunt eligibility restrictions and funding caps. Another difficulty is the challenge of achieving allocative efficiency between home-based and hospital-based services, made plain by the fact that, in many countries, a majority of people die in hospital despite a preference for dying at home. The author describes developments (particularly in Australia) in activity-based funding for palliative care. An interesting proposal – though not discussed in enough detail – is that payments could be made for each death (per mortems?). Capitation-based payment models are considered and the extent to which pay-for-performance could be incorporated is also discussed – the latter being potentially important in achieving those process outcomes that matter so much in palliative care. Yet another challenge is the question of when palliative care should come into play, because, in some cases, it’s a matter of sooner being better, because the provision of palliative care can give rise to less costly and more preferred treatment pathways. Thus, palliative care funding models will have implications for the funding of acute care. Throughout, the paper includes examples from different countries, along with a wealth of references to dig into. Helpfully, the author explicitly states in a table the models that different settings ought to adopt, given their prevailing model. As our population ages and the purse strings tighten, this is a discussion we can expect to be having more and more.



Sam Watson’s journal round-up for 2nd October 2017

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 path to longer and healthier lives for all Africans by 2030: the Lancet Commission on the future of health in sub-Saharan Africa. The Lancet [PubMedPublished 13th September 2017

The African continent has the highest rates of economic growth, the fastest growing populations and rates of urbanisation, but also the highest burden of disease. The challenges for public health and health care provision are great. It is no surprise then that this Lancet commission on the future of health in Sub-Saharan Africa runs to 57 pages yet still has some notable absences. In the space of a few hundred words, it would be impossible to fully discuss the topics in this tome, these will appear in future blog posts. For now, I want to briefly discuss a lack of consideration of the importance of political economy in the Commission’s report. For example, the report notes the damaging effects of IMF and World Bank structural adjustment programs in the 70s and 80s. These led to a dismantling of much of the public sector in indebted African nations in order for them to qualify for further loans. However, these issues have not gone away. Despite strongly emphasizing that countries in Africa must increase their health spending, it does not mention that many countries spend much more servicing debt than on public health and health care. Kenya, for example, will soon no longer qualify for aid as it becomes a middle-income country, and yet it spends almost double (around $6 billion) servicing its debt than it does on health care (around $3 billion). Debt reform and relief may be a major step towards increasing health expenditure. The inequalities in access to basic health services reflect the disparities in income and wealth both between and within countries. The growth of slums across the continent is stark evidence of this. Residents of these communities, despite often facing the worst exposure to major disease risk factors, are often not recognised by authorities and cannot access health services. Even where health services are available there are still difficulties with access. A lack of regulation and oversight can lead the growth of a rentier class within slums as those with access to small amounts of capital, land, or property act as petty landlords. So while some in slum areas can afford the fees for basic health services, the poorest still face a barrier even when services are available. These people are also those who have little access to decent water and sanitation or education and have the highest risk of disease. Finally, the lack of incentives for trained doctors and medical staff to work in poor or rural areas is also identified as a key problem. Many doctors either leave for wealthier countries or work in urban areas. Doctors are often a powerful interest group and can influence macro health policy, distorting it to favour richer urban areas. Political solutions are required, as well as the public health interventions more widely discussed. The Commission’s report is extensive and worth the time to read for anyone with an interest in the subject matter. What also becomes clear upon reading it is the lack of solid evidence on health systems and what works and does not work. From an economic perspective, much of the evidence pertaining to health system functioning and efficiency is still just the results from country-level panel data regressions, which tell us very little about what is actually happening. This results in us being able to identify areas needed for reform with very little idea of how.

The relationship of health insurance and mortality: is lack of insurance deadly? Annals of Internal Medicine [PubMedPublished 19th September 2017

One sure-fire way of increasing your chances of publishing in a top-ranked journal is to do something on a hot political topic. In the UK this has been seven-day services, as well as other issues relating to deficiencies of supply. In the US, health insurance is right up there with the Republicans trying to repeal the Affordable Care Act, a.k.a. Obamacare. This paper systematically reviews the literature on the relationship between health insurance coverage and the risk of mortality. The theory being that health insurance permits access to medical services and therefore treatment and prevention measures that reduce the risk of death. Many readers will be familiar with the Oregon Health Insurance Experiment, in which the US state of Oregon distributed access to increased Medicaid expansion by lottery, therein creating an RCT. This experiment, which takes a top spot in the review, estimated that those who had ‘won’ the lottery had a mortality rate 0.032 percentage points lower than the ‘losers’, whose mortality rate was 0.8%; a relative reduction of around 4%. Similar results were found for the quasi-experimental studies included, and slightly larger effects were found in cohort follow-up studies. These effects are small. But then so is the baseline. Most of these studies only examined non-elderly, non-disabled people, who would otherwise not qualify for any other public health insurance. For people under 45 in the US, the leading cause of death is unintentional injury, and its only above this age that cancer becomes the leading cause of death. If you suffer major trauma in the US you will (for the most part) be treated in an ER insured or uninsured, even if you end up with a large bill afterwards. So it’s no surprise that the effects of insurance coverage on mortality are very small for these people. This is probably the inappropriate endpoint to be looking at for this study. Indeed, the Oregon experiment found that the biggest differences were in reduced out-of-pocket expenses and medical debt, and improved self-reported health. The review’s conclusion that, “The odds of dying among the insured relative to the uninsured is 0.71 to 0.97,” is seemingly unwarranted. If they want to make a political point about the need for insurance, they’re looking in the wrong place.

Smoking, expectations, and health: a dynamic stochastic model of lifetime smoking behavior. Journal of Political Economy [RePEcPublished 24th August 2017

I’ve long been sceptical of mathematical models of complex health behaviours. The most egregious of which is often the ‘rational addiction’ literature. Originating with the late Gary Becker, the rational addiction model, in essence, assumes that addiction is a rational choice made by utility maximising individuals, whose preferences alter with use of a particular drug. The biggest problem I find with this approach is that it is completely out of touch with the reality of addiction and drug dependence, and makes absurd assumptions about the preferences of addicts. Nevertheless, it has spawned a sizable literature. And, one may argue that the model is useful if it makes accurate predictions, regardless of the assumptions underlying it. On this front, I have yet to be convinced. This paper builds a rational addiction-type model for smoking to examine whether learning of one’s health risks reduces smoking. As an illustration of why I dislike this method of understanding addictive behaviours, the authors note that “…the model cannot explain why individuals start smoking. […] The estimated preference parameters in the absence of a chronic illness suggest that, for a never smoker under the age of 25, there is no incentive to begin smoking because the marginal utility of smoking is negative.” But for many, social and cultural factors simply explain why young people start smoking. The weakness of the deductive approach to social science seems to rear its head, but like I said, the aim here may be the development of good predictive models. And, the model does appear to predict smoking behaviour well. However, it is all in-sample prediction, and with the number of parameters it is not surprising it predicts well. This discussion is not meant to be completely excoriating. What is interesting is the discussion and attempt to deal with the endogeneity of smoking – people in poor health may be more likely to smoke and so the estimated effects of smoking on longevity may be overestimated. As a final point of contention though, I’m still trying to work out what the “addictive stock of smoking capital” is.