Paul Mitchell’s journal round-up for 17th April 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.

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach. Social Science & Medicine [PubMed] Published 28th March 2017

Foreign direct investment (FDI) is considered a key benefit of globalisation in the economic development of countries with developing economies. The effect FDI has on the population health of countries is less well understood. In this paper, the authors draw from a large panel of data, primarily World Bank and UN sources, for 85 low and middle income countries between 1974 and 2012 to assess the relationship between FDI and population health, proxied by life expectancy at birth, as well as child and adult mortality data. They explain clearly the problem of using basic regression analysis in trying to explain this relationship, given the problem of endogeneity between FDI and health outcomes. By introducing two instrumental variables, using grossed fixed capital formation and volatility of exchange rates in FDI origin countries, as well as controlling for GDP per capita, education, quality of institutions and urban population, the study shows that FDI is weakly statistically associated with life expectancy, estimated to amount to 4.15 year increase in life expectancy during the study period. FDI also appears to have an effect on reducing adult mortality, but a negligible effect on child mortality. They also produce some evidence that FDI linked to manufacturing could lead to reductions in life expectancy, although these findings are not as robust as the other findings using instrumental variables, so they recommend this relationship between FDI type and population health to be explored further. The paper also clearly shows the benefit of robust analysis using instrumental variables, as the results without the introduction of these variables to the regression would have led to misleading inferences, where no relationship between life expectancy and FDI would have been found if the analysis did not adjust for the underlying endogeneity bias.

Uncovering waste in US healthcare: evidence from ambulance referral patterns. Journal of Health Economics [PubMed] Published 22nd March 2017

This study looks to unpick some of the reasons behind the estimated waste in US healthcare spending, by focusing on mortality rates across the country following an emergency admission to hospital through ambulances. The authors argue that patients admitted to hospital for emergency care using ambulances act as a good instrument to assess hospital quality given the nature of emergency admissions limiting the selection bias of what type of patients end up in different hospitals. Using linear regressions, the study primarily measures the relationship between patients assigned to certain hospitals and the 90-day spending on these patients compared to mortality. They also consider one-year mortality and the downstream payments post-acute care (excluding pharmaceuticals outside the hospital setting) has on this outcome. Through a lengthy data cleaning process, the study looks at over 1.5 million admissions between 2002-2011, with a high average age of patients of 82 who are predominantly female and white. Approximately $27,500 per patient was spent in the first 90 days post-admission, with inpatient spending accounting for the majority of this amount (≈$16,000). The authors argue initially that the higher 90-day spending in some hospitals only produces modestly lower mortality rates. Spending over 1 year is estimated to cost more than $300,000 per life year, which the authors use to argue that current spending levels do not lead to improved outcomes. But when the authors dig deeper, it seems clear there is an association between hospitals who have higher spending on inpatient care and reduced mortality, approximately 10% lower. This leads to the authors turning their attention to post-acute care as their main target of reducing waste and they find an association between mortality and patients receiving specialised nursing care. However, this target seems somewhat strange to me, as post-acute care is not controlled for in the same way as their initial, insightful approach to randomising based on ambulatory care. I imagine those in such care are likely to be a different mix from those receiving other types of care post 90 days after the initial event. I feel there really is not enough to go on to make recommendations about specialist nursing care being the key waste driver from their analysis as it says nothing, beyond mortality, about the quality of care these elderly patients are receiving in the specialist nurse facilities. After reading this paper, one way I would suggest in reducing inefficiency related to their primary analysis could be to send patients to the most appropriate hospital for what the patient needs in the first place, which seems difficult given the complexity of the private and hospital provided mix of ambulatory care offered in the US currently.

Population health and the economy: mortality and the Great Recession in Europe. Health Economics [PubMed] Published 27th March 2017

Understanding how economic recessions affect population health is of great research interest given the recent global financial crisis that led to the worst downturn in economic performance in the West since the 1930s. This study uses data from 27 European countries between 2004 and 2010 collected by WHO and the World Bank to study the relationship between economic performance and population health by comparing national unemployment and mortality rates before and after 2007. Regression analyses appropriate for time-series data are applied with a number of different specifications applied. The authors find that the more severe the economic downturn, the greater the increase in life expectancy at birth. Additional specific health mortality rates follow a similar trend in their analysis, with largest improvements observed in countries where the severity of the recession was the highest. The only exception the authors note is data on suicide, where they argue the relationship is less clear, but points towards higher rates of suicide with greater unemployment. The message the authors were trying to get across in this study was not very clear throughout most of the paper and some lay readers of the abstract alone could easily be misled in thinking recessions themselves were responsible for better population health. Mortality rates fell across all six years, but at a faster rate in the recession years. Although the results appeared consistent across all models, question marks remain for me in terms of their initial variable selection. Although the discussion mentions evidence that suggests health care may not have a short-term effect on mortality, they did not consider any potential lagged effect record investment in healthcare as a proportion of GDP up until 2007 may have had on the initial recession years. The authors rule out earlier comparisons with countries in the post-Soviet era but do not consider the effect of recent EU accession for many of the countries and more regulated national policies as a consequence. Another issue is the potential of countries’ mortality rates to improve, where countries with existing lower life expectancy have more room for moving in the right direction. However, one interesting discussion point raised by the authors in trying to explain their findings is the potential impact of economic activity on pollution levels and knock-on health impacts from this (and to a lesser extent occupational health levels), that may have some plausibility in better mortality rates linked to physical health during recessions.

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Chris Sampson’s journal round-up for 3rd April 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.

Return on investment of public health interventions: a systematic review. Journal of Epidemiology & Community Health [PubMed] Published 29th March 2017

Cost-effectiveness analysis in the context of public health is tricky. Often the health benefits are small at the individual level and the returns to investment might be cross-sectoral. Lots of smart people believe that spending on public health is low in proportion to other health spending. Here we have a systematic review of studies reporting cost-benefit ratios (CBR) or return on investment (ROI) estimates for public health interventions. The stated aim of the paper is to demonstrate the false economy associated with cuts to public health spending. 52 titles were included from a search that identified 2957. The inclusion and exclusion criteria are not very clear, with some studies rejected on the basis of ‘poor generalisability to the UK’. There’s a bit too much subjectivity sneaking around in the methods for my liking.  Results for CBR and ROI estimates are presented according to local or national level and grouped by ‘specialism’. From all studies, the median CBR was 8.3 and the median ROI was 14.3. As we might have suspected, public health interventions are cost-saving in a big way. National health protection and legislative interventions offered the greatest return on investment. While there is wide variation in the results, all specialism groupings showed a positive return on average. I don’t doubt the truth of the study’s message – that cuts to public health spending are foolish. But the review doesn’t really demonstrate what the authors want it to demonstrate. We don’t know what (if any) disinvestment is taking place with respect to the interventions identified in the review. The results presented in the study represent a useful reference point for discussion and further analysis, but they aren’t a sufficient basis for supporting general increases in public health spending. That said, the study adds to an already resounding call and may help bring more attention to the issue.

Acceptable health and priority weighting: discussing a reference-level approach using sufficientarian reasoning. Social Science & Medicine Published 27th March 2017

In some ways, the moral principle of sufficiency is very attractive. It acknowledges a desire for redistribution from the haves to the have-nots and may also make for a more manageable goal than all-out maximisation. It may also be particularly useful in specific situations, such as evaluating health care for the elderly, for whom ‘full health’ is never achievable and not a meaningful reference point. This paper presents a discussion of the normative issues at play, drawing insights from the distributive justice literature. We’re reminded of the fair innings argument as a familiar sufficientarian flavoured allocation principle. The sufficientarian approach is outlined in contrast to egalitarianism and prioritarianism. Strict sufficientarian value weighting is not a good idea. If we suppose a socially ‘acceptable’ health state value of 0.7, such an approach would – for example – value an improvement from 0.69 to 0.71 for one person as infinitely more valuable than an improvement from 0.2 to 0.6 for the whole population. The authors go on to outline some more relaxed sufficiency weightings, whereby improvements below the threshold are attributed a value greater than 0 (though still less than those achieving sufficiency). The sufficientarian approach alone is (forgive me) an insufficient framework for the allocation of health care resources and cannot represent the kind of societal preferences that have been observed in the literature. Thus, hybrids are proposed. In particular, a sufficientarian-prioritarian weighting function is presented and the authors suggest that this may be a useful basis for priority setting. One can imagine a very weak form of the sufficientarian approach that corresponds to a prioritarian weighting function that is (perhaps) concave below the threshold and convex above it. Still, we have the major problem of identifying a level of acceptable health that is not arbitrary. The real question you need to ask yourself is this: do you really want health economists to start arguing about another threshold?

Emotions and scope effects in the monetary valuation of health. The European Journal of Health Economics [PubMed] Published 24th March 2017

It seems obvious that emotions could affect the value people attach to goods and services, but little research has been conducted with respect to willingness to pay for health services. This study considers the relationship between a person’s self-reported fear of being operated on and their willingness to pay for risk-reducing drug-eluting stents. A sample of 1479 people in Spain made a series of choices between bare-metal stents at no cost and drug-eluting stents with some out-of-pocket cost, alongside a set of sociodemographic questions and a fear of surgery Likert scale. Each respondent provided 8 responses with 4 different risk reductions and 2 different willingness to pay ‘bids’. The authors outline what they call a ‘cognitive-emotional random utility model’ including an ’emotional shift effect’. Four different models are presented to demonstrate the predictive value of the emotion levels interacting with the risk reduction levels. The sample was split roughly in half according to whether people reported high emotion (8, 9 or 10 on the fear Likert) or low emotion (<8). People who reported more fear of being operated on were willing to pay more for risk reductions, which is the obvious result. More interesting is that the high emotion group exhibited a lower sensitivity to scope – that is, there wasn’t much difference in their valuation of the alternative magnitudes of risk reduction. This constitutes a problem for willingness to pay estimates in this group as it may prevent the elicitation of meaningful values, and it is perhaps another reason why we usually go for collective approaches to health state valuation. The authors conclude that emotional response is a bias that needs to be corrected. I don’t buy this interpretation and would tend to the view that the bias that needs correcting here is that of the economist. Emotions may be a justifiable reflection of personality traits that ought to determine preferences, at least at the individual level. But I do agree with the authors that this is an interesting field for further research if only to understand possible sources of heterogeneity in health state valuation.

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Chris Sampson’s journal round-up for 6th February 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.

A review of NICE methods and processes across health technology assessment programmes: why the differences and what is the impact? Applied Health Economics and Health Policy [PubMed] Published 27th January 2017

Depending on the type of technology under consideration, NICE adopts a variety of different approaches in coming up with their recommendations. Different approaches might result in different decisions, which could undermine allocative efficiency. This study explores this possibility. Data were extracted from the manuals and websites for 5 programmes, under the themes of ‘remit and scope’, ‘process of assessment’, ‘methods of evaluation’ and ‘appraisal of evidence’. Semi-structured interviews were conducted with 5 people with expertise in each of the 5 programmes. Results are presented in a series of tables – one for each theme – outlining the essential characteristics of the 5 programmes. In their discussion, the authors then go on to consider how the identified differences might impact on efficiency from either a ‘utilitarian’ health-maximisation perspective or NICE’s egalitarian aim of ensuring adequate levels of health care. Not all programmes deliver recommendations with mandatory funding status, and it is only the ones that do that have a formal appeals process. Allowing for local rulings on funding could be good or bad news for efficiency, depending on the capacity of local decision makers to conduct economic evaluations (so that means probably bad news). At the same time, regional variation could undermine NICE’s fairness agenda. The evidence considered by the programmes varies, from a narrow focus on clinical and cost-effectiveness to the incorporation of budget impact and wider ethical and social values. Only some of the programmes have reference cases, and those that do are the ones that use cost-per-QALY analysis, which probably isn’t a coincidence. The fact that some programmes use outcomes other than QALYs obviously has the potential to undermine health-maximisation. Most differences or borne of practicality; there’s no point in insisting on a CUA if there is no evidence at all to support one – the appraisal would simply not happen. The very existence of alternative programmes indicates that NICE is not simply concerned with health-maximisation. Additional weight is given to rare conditions, for example. And NICE want to encourage research and innovation. So it’s no surprise that we need to take into account NICE’s egalitarian view to understand the type of efficiency for which it strives.

Economic evaluations alongside efficient study designs using large observational datasets: the PLEASANT trial case study. PharmacoEconomics [PubMed] Published 21st January 2017

One of the worst things about working on trial-based economic evaluations is going to lots of effort to collect lots of data, then finding that at the end of the day you don’t have much to show for it. Nowadays, the health service routinely collects many data for other purposes. There have been proposals to use these data – instead of prospectively collecting data – to conduct clinical trials. This study explores the potential for doing an economic evaluation alongside such a trial. The study uses CPRD data, including diagnostic, clinical and resource use information, for 8,608 trial participants. The intervention was the sending out of a letter in the hope of reducing unscheduled medical contacts due to asthma exacerbation in children starting a new school year. QALYs couldn’t be estimated using the CPRD data, so values were derived from the literature and estimated on the basis of exacerbations indicated by changes in prescriptions or hospitalisations. Note here the potentially artificial correlation between costs and outcomes that this creates, thus somewhat undermining the benefit of some good old bootstrapping. The results suggest the intervention is cost-saving with little impact on QALYs. Lots of sensitivity analyses are conducted, which are interesting in themselves and say something about the concerns around some of the structural assumptions. The authors outline the pros and cons of the approach. It’s an important discussion as it seems that studies like this are going to become increasingly common. Regarding data collection, there’s little doubt that this approach is more efficient, and it should be particularly valuable in the evaluation of public health and service delivery type interventions. The problem is that the study is not able to use individual-level cost and outcome data from the same people, which is what sets a trial-based economic evaluation apart from a model-based study. So for me, this isn’t really a trial-based economic evaluation. Indeed, the analysis incorporates a Markov-type model of exacerbations. It’s a different kind of beast, which incorporates aspects of modelling and aspects of trial-based analysis, along with some unique challenges of its own. There’s a lot more methodological work that needs to be done in this area, but this study demonstrates that it could be fruitful.

“Too much medicine”: insights and explanations from economic theory and research. Social Science & Medicine [PubMed] Published 18th January 2017

Overconsumption of health care represents an inefficient use of resources, and so we wouldn’t recommend it. But is that all we – as economists – have to say on the matter? This study sought to dig a little deeper. A literature search was conducted to establish a working definition of overconsumption. Related notions such as overdiagnosis, overtreatment, overuse, low-value care, overmedicalisation and even ‘pharmaceuticalisation’ all crop up. The authors introduce ‘need’ as a basis for understanding overconsumption; it represents health care that should never be considered as “needed”. A useful distinction is identified between misconsumption – where an individual’s own consumption is detrimental to their own well-being – and overconsumption, which can be understood as having a negative effect on social welfare. Note that in a collectively funded system the two concepts aren’t entirely distinguishable. Misconsumption becomes the focus of the paper, as avoiding harm to patients has been the subject of the “too much medicine” movement. I think this is a shame, and not really consistent with an economist’s usual perspective. The authors go on to discuss issues such as moral hazard, supplier-induced demand, provider payment mechanisms, ‘indication creep’, regret theory, and physicians’ positional consumption, and whether or not such phenomena might lead to individual welfare losses and thus be considered causes of misconsumption. The authors provide a neat diagram showing the various causes of misconsumption on a plane. One dimension represents the extent to which the cause is imperfect knowledge or imperfect agency, and the other the degree to which the cause is at the individual or market level. There’s a big gap in the top right, where market level causes meet imperfect knowledge. This area could have included patent systems, research fraud and dodgy Pharma practices. Or maybe just a portrait of Ben Goldacre for shorthand. There are some warnings about the (limited) extent to which market reforms might address misconsumption, and the proposed remedy for overconsumption is not really an economic one. Rather, a change in culture is prescribed. More research looking at existing treatments rather than technology adoption, and to investigate subgroup effects, is also recommended. The authors further suggest collaboration between health economists and ecological economists.

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