Thesis Thursday: Estela Capelas Barbosa

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Estela Capelas Barbosa who graduated with a PhD from the University of York. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Overall unfair inequality in health care: an application to Brazil
Richard Cookson
Repository link

What’s the difference between fair and unfair inequality, and why is it important to distinguish the two?

Not all inequality is the same. Whilst most inequality in health and health care is unwanted, one could argue that some inequality is even desirable. For example, we all agree that women should receive more care than men because they have a higher need for health care. The same argument could be used for children. Therefore, when looking into inequality, from a philosophical point of view, it is important to distinguish between inequality that is deemed fair (as in my women’s example) and that considered unfair. But there is a catch! Because ‘fair’ and ‘unfair’ are normative value judgements, different people may have different views as to what is fair or unfair. That’s why, in the thesis, I worked hard to come up with a framework that was flexible enough to allow for different views of fair and unfair.

Your thesis describes a novel way of thinking about inequality. What led you to believe that other conceptualisations were inadequate?

Previously, inequality in health care was either dealt with in overall terms, using a Gini coefficient type of analysis, or focused on income and socioeconomic inequality (see Wagstaff and Van Doorslaer, 2004). As a field researcher in Brazil, I had first-hand experience that there was more to unfair inequality than income. I remember personally meeting a very wealthy man that had many difficulties in accessing the healthcare system simply because he lived in a very remote rural area of the country. I wanted to better understand this and look beyond income to explain inequality in Brazil. Thus, neither of the well-established methods seemed really appropriate for my analysis. I knew I could adjust my Gini for need, but this type of analysis did not explicitly allow for a distinction between unfair and fair inequality. At the other extreme, income-related inequality was just a very narrow definition of unfairness. Although the established methods were my starting point, I agreed with Fleurbaey and Schokkaert that there could be yet another way of looking at inequality in health care, and I drew inspiration from their proposed method for health and made adjustments and modifications for the application to health care.

What were some of your key findings about the sources of inequality, and how were they measured in your data?

I guess my most important finding is that the sources of unfair inequality have changed between 1998 and 2013. For example, the contribution of income to unfair inequality decreased in this time for physician visits and mammography screening, yet for cervical screening it nearly doubled between 2003 and 2013. I have also found that there are other sources of inequality which are important (sometimes even more than income), as for example having private health insurance, education, living in urban areas and region.

As to my data, it came from Health Supplement of the Brazilian National Household Sample Survey for the years 1998, 2003 and 2008 and the first National Health Survey, conducted in 2013 (see The surveys use standardised questionnaires and rely on self-report for most questions, particularly those related to health care coverage and health status.

Your analysis looks at a relatively long period of time. What can you tell us about long-term trends in Brazil?

It is difficult to talk about long-term trends in Brazil at the moment. Our (universal) healthcare system has only been in place since 1988 and, since the last wave of data (in 2013), there has been a strong political movement to dismantle the national system and sell it to the private sector. I guess the movement to reduce and/or privatise the NHS also exists here, but, unlike in the UK, our national system has always been massively under-resourced, so it is not as highly-regarded by the population.

Having said that, it is fair to say that in its first 25 years of existence, Brazil has accomplished a lot in terms of healthcare (I have described – in Portuguese – some of the achievements and challenges). The Brazilian National Health System covers over 200 million people and accounts for nearly 500 thousand hospital beds. In terms of inequality, over time, it has decreased for physician visits and cervical screening, though for mammography there is no clear trend.

What would you like to see policymakers in Brazil prioritise in respect to reducing inequality?

First and foremost, I would like policymakers to understand that over three-quarters of the Brazilian population relies on the national system as their one and only health care provider. Second, I would like to reinforce the idea that social inequality in health care in Brazil is not only and indeed not primarily related to income. In fact, other social variables such as education, region, urban or rural residency and health insurance status are as important or even more important than income. This implies that there are supply side actions that can be taken, which should be much easier to implement. For example, more health care equipment, such as MRIs and CT scanners could be purchased for the North and Northeast regions. This could potentially reduce unfair inequality. Policies can also be directed at improving access to care in rural regions, although this factor is not as important a contributor to inequality as it used to be. I guess the overall message is: there are several things that can be done to reduce unfair inequality in Brazil, but all depend on political will and understanding the importance of the healthcare system for the health of the population.


Sam Watson’s journal round-up for 7th August 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.

Financing transformative health systems towards achievement of the health Sustainable Development Goals: a model for projected resource needs in 67 low-income and middle-income countries. Lancet: Global Health [PubMedPublished 17th July 2017

Achieving universal health coverage is a key aspect of the UN’s sustainable development goals. However, what this means in practice is complicated. People need to be able to access health services free at the point of use, but once those services are accessed there needs to be sufficient labour, capital, skill, and quality to correctly diagnose and treat them. For many health systems worldwide, this will require large investments in infrastructure and staffing, but the potential cost of achieving these goals is unclear. This article sets out to estimate these costs. Clearly, this is a complicated task – health care systems are incredibly complex. From a basic microeconomic standpoint, one might need some understanding of the production function of different health care systems, and the marginal productivity of labour and capital inputs to these systems. There is generally good evidence of what is effective and cost-effective for the treatment of different diseases, and so given the amenable disease burden for a particular country, we could begin to understand what would be required to combat it. This is how this article tackles this question, more or less. They take a bottom-up costing approach to a wide range of interventions, governance requirements, and, where required, other interventions such as water and sanitation. However, there are other mechanisms at play. At national levels, economies of scale and scope play a role. Integration of care programs can reduce the costs, improve the quality, or both, of the individual programs. Similarly, the levels of investment considered are likely to have relevant macroeconomic effects, boosting employment, income, and subsequent socioeconomic indicators. Credit is due to the authors, they do consider financing and health impacts of investment, and their paper is the most comprehensive to date on the topic. However, their projections (~$300 billion annually) are perhaps more uncertain than they let on, a criticism I made of similar papers recently. While I should remind myself not to let the perfect be the enemy of the good, detailed case studies of particular countries may help me to see how the spreadsheet model may actually translate into real-world changes.

Precommitment, cash transfers, and timely arrival for birth: evidence from a randomized controlled trial in Nairobi Kenya. American Economic Review [RePEcPublished May 2017

A great proportion of the gains in life expectancy in recent years has been through the reduction of childhood mortality. The early years of life are some of the most precarious. A newborn child, if she survives past five years of age, will not face the same risk of dying until late adulthood. Many of the same risk factors that contribute to childhood mortality also contribute to maternal death rates and many low-income countries still face unacceptably high rates of dying for both mother and child. One way of tackling this is to ensure mothers have access to adequate antenatal and postnatal care. In Kenya, for example, the government legislated to provide free delivery services in government health facilities in 2013. However, Kenya still has some of the highest death rates for mother and child in the world. It is speculated that one reason for this is the delay in receiving services in the case of complications with a pregnancy. A potential cause of this delay in Nairobi is a lack of adequate planning from women who face a large number of heterogeneous treatment options for birth. This study presents an RCT in which pregnant women were offered a “precommitment transfer package”, which consisted of a cash transfer of 1000 KSh (~£7) during pregnancy and a further 1000 KSh if women stuck to a delivery plan they had earlier committed to. The transfer was found to increase the proportion of women arriving early to delivery facilities. The study was a fairly small pilot study and the results somewhat uncertain, but the intervention appears promising. Cost-effectiveness comparisons are warranted with other interventions aiming to achieve the same ends.

Bans on electronic cigarette sales to minors and smoking among high school students. Journal of Health Economics [PubMedPublished July 2017

E-cigarettes have provoked quite a debate among public health researchers and campaigners as we’ve previously discussed. E-cigarettes are a substitute for tobacco smoking and are likely to be significantly less harmful. They may have contributed to large declines in the use of tobacco in the UK in the last few years. However, some have taken a “think of the children!” position. While e-cigarette use per se among adolescents may not be a significant public health issue, it could lead to increased use of tobacco. Others have countered that those young people using e-cigarettes would have been those that used tobacco anyway, so banning e-cigarettes among minors may lead them to go back to the tobacco. This paper takes data from repeated surveys of high school students in the US to estimate the effects of banning the sale of e-cigarettes to minors on the prevalence of tobacco smoking. Interestingly, bans appear to reduce tobacco smoking prevalence; the results appear fairly robust and the modelling is sensible. This conflicts with other recent similar studies. The authors argue that this shows that e-cigarettes and tobacco smoking are complements, so reducing one reduces the other. But I am not sure this explains the decline since no increase in youth smoking was observed as e-cigarettes became more popular. Certainly, such a ban would not have reduced smoking prevalence years ago. At the very least e-cigarettes have clearly had a significant effect on attitudes towards smoking. Perhaps smoking was on the decline anyway – but the authors estimate a model with state-specific time trends, and no declines were seen in control states. Whatever our prior beliefs about the efficacy of regulating or banning e-cigarettes, the evidence is complex, reflecting the complex behaviour of people towards drugs, alcohol, and tobacco.


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

What goes wrong with the allocation of domestic and international resources for HIV? Health Economics [PubMedPublished 7th July 2017

Investment in foreign aid is coming under considered scrutiny as a number of leading western economies re-evaluate their role in the world and their obligations to countries with developing economies. Therefore, it is important for those who believe in the benefits of such investments to show that they are being done efficiently. This paper looks at how funding for HIV is distributed both domestically and internationally across countries, using multivariate regression analysis with instruments to control for reverse causality between financing and HIV prevalence, and domestic and international financing. The author is also concerned about countries free riding on international aid and estimates how countries ought to be allocating national resources to HIV using quintile regression to estimate what countries have fiscal space for expanding their current spending domestically. The results of the study show that domestic expenditure relative to GDP per capita is almost unit elastic, whereas it is inelastic with regards to HIV prevalence. Government effectiveness (as defined by the World Bank indices) has a statistically significant effect on domestic expenditure, although it is nonlinear, with gains more likely when moving up from a lower level of government effectiveness. International expenditure is inversely related to GDP per capita and HIV prevalence, and positively with government effectiveness, albeit the regression models for international expenditure had poor explanatory power. Countries with higher GDP per capita tended to dedicate more money towards HIV, however, the author reckons there is $3bn of fiscal space in countries such as South Africa and Nigeria to contribute more to HIV, freeing up international aid for other countries such as Cameroon, Ghana, Thailand, Pakistan and Columbia. The author is concerned that countries with higher GDP should be able to allocate more to HIV, but feels there are improvements to be made in how international aid is distributed too. Although there is plenty of food for thought in this paper, I was left wondering how this analysis can help in aiding a better allocation of resources. The normative model of what funding for HIV ought to be is from the viewpoint that this is the sole objective of countries of allocating resources, which is clearly contestable (the author even casts doubt as to whether this is true for international funding of HIV). Perhaps the other demands faced by national governments (e.g. funding for other diseases, education etc.) can be better reflected in future research in this area.

Can pay-for-performance to primary care providers stimulate appropriate use of antibiotics? Health Economics [PubMed] [RePEcPublished 7th July 2017

Antibiotic resistance is one of the largest challenges facing global health this century. This study from Sweden looks to see whether pay for performance (P4P) can have a role in the prescription practices of GPs when it comes to treating children with respiratory tract infection. P4P was introduced on a staggered basis across a number of regions in Sweden to incentivise primary care to use narrow spectrum penicillin as a first line treatment, as it is said to have a smaller impact on resistance. Taking advantage of data from the Swedish Prescribed Drug Register between 2006-2013, the authors conducted a difference in difference regression analysis to show the effect P4P had on the share of the incentivised antibiotic. They find a positive main effect of P4P on drug prescribing of 1.1 percentage points, that is also statistically significant. Of interest, the P4P in Sweden under analysis here was not directly linked to salaries of GPs but the health care centre. Although there are a number of limitations with the study that the authors clearly highlight in the discussion, it is a good example of how to make the most of routinely available data. It also highlights that although the share of the less resistant antibiotic went up, the national picture of usage of antibiotics did not reduce in line with a national policy aimed at doing so during the same time period. Even though Sweden is reported to be one of the lower users of antibiotics in Europe, it highlights the need to carefully think through how targets are achieved and where incentives might help in some areas to meet such targets.

Econometric modelling of multiple self-reports of health states: the switch from EQ-5D-3L to EQ-5D-5L in evaluating drug therapies for rheumatoid arthritis. Journal of Health Economics Published 4th July 2017

The EQ-5D is the most frequently used health state descriptive system for the generation of utility values for quality-adjusted life years (QALYs) in economic evaluation. To improve sensitivity and reduce floor and ceiling effects, the EuroQol team developed a five level version (5L) compared to the previous three level (3L) version. This study adds to recent evidence in this area of the unforeseen consequences of making this change to the descriptive system and also the valuation system used for the 5L. Using data from the National Data Bank for Rheumatic Diseases, where both 3L and 5L versions were completed simultaneously alongside other clinical measures, the authors construct a mapping between both versions of EQ-5D, informed by the response levels and the valuation systems that have been developed in the UK for the measures. They also test their mapping estimates on a previous economic evaluation for rheumatoid arthritis treatments. The descriptive results show that although there is a high correlation between both versions, and the 5L version achieves its aim of greater sensitivity, there is a systematic difference in utility scores generated using both versions, with an average 87% of the score of the 3L recorded compared to the 5L. Not only are there differences highlighted between value sets for the 3L and 5L but also the responses to dimensions across measures, where the mobility and pain dimensions do not align as one would expect. The new mapping developed in this paper highlights some of the issues with previous mapping methods used in practice, including the assumption of independence of dimension levels from one another that was used while the new valuation for the 5L was being developed. Although the case study they use to demonstrate the effect of using the different approaches in practice did not result in a different cost-effectiveness result, the study does manage to highlight that the assumption of 3L and 5L versions being substitutes for one another, both in terms of descriptive systems and value sets, does not hold. Although the authors are keen to highlight the benefits of their new mapping that produces a smooth distribution from actual to predicted 5L, decision makers will need to be clear about what descriptive system they now want for the generation of QALYs, given the discrepancies between 3L and 5L versions of EQ-5D, so that consistent results are obtained from economic evaluations.