Simon McNamara’s journal round-up for 8th April 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.

National Institute for Health and Care Excellence, social values and healthcare priority setting. Journal of the Royal Society of Medicine [PubMed] Published 2nd April 2019

As is traditional, this week’s round-up starts with an imaginary birthday party. After much effort, we have finally managed to light the twenty candles, have agreed our approach to the distribution of the cake, and are waiting in anticipation of the entrance of the birthday “quasi-autonomous non-governmental body”. The door opens. You clear your throat. Here we go…

Happy Birthday to you,

Happy Birthday to you,

Happy Birthday dear National Institute for Health and Care Excellence,

Happy Birthday to you.

NICE smiles happily. It is no longer a teenager. It has made it to 20 – despite its parents challenging it a few times (cough, Cancer Drug Fund, cough). After the candles have been blown out, someone at the back shouts: “Speech! Speech!”. NICE coughs, thanks everyone politely, and (admittedly slight strangely) takes the opportunity to announce that they are revising their “Social Value Judgements” paper – a document that outlines the principles they use to develop guidance. They then proceed to circle the room, proudly handing out draft copies of the new document- “The principles that guide the development of NICE guidance and standards” (PDF). They look excited. Your fellow guests start to read.

“Surely not?”, “What the … ?”, “Why?” – they don’t seem pleased. You jump into the document. All of this is about process. Where are all the bits about justice, and inequalities, and bioethics, and the rest? “Why have you taken out loads of the good stuff?” you ask. “This is too vague, too procedural”. Your disappointment is obvious to those in the room.

Your phone pings – it’s your favourite WhatsApp group. One of the other guests has already started drafting a “critical friend” paper in the corner of the room. They want to know if you want to be involved. “I’m in”, you respond, “This is important, we need to make sure NICE knows what we think”. Your phone pings again. Another guest is in: “I want to be involved, this matters. Also, this is exactly the kind of paper that will get picked up by the AHE blog. If we are lucky, we might even be the first paper in one of their journal round-ups”. You pause, think, and respond hopefully: “Fingers crossed”.

I don’t know if NICE had an actual birthday party – if they did I certainly wasn’t invited. I also highly doubt that the authors of this week’s first paper, or indeed any paper, had the AHE blog in mind when writing. What I do know, is that the first article is indeed a “critical friend” paper which outlines the authors’ concerns with NICE’s proposal to “revise” (read: delete) their social value judgements guidance. This paper is relatively short, so if you are interested in these changes I suggest you read it, rather than relying on my imaginary birthday party version of their concerns.

I am highly sympathetic to the views expressed in this paper. The existing “social value judgements” document is excellent, and (to me at least) seems to be the gold standard in setting the values by which an HTA body should develop guidance. Reducing this down to solely procedural elements seems unnecessary, and potentially harmful if the other core values are forgotten, or deprioritised.

As I reflect on this paper, I can’t help think of the old adage: “If it ain’t broke, don’t fix it”. NICE – this ain’t broke.

Measuring survival benefit in health technology assessment in the presence of nonproportional hazards. Value in Health Published 22nd March 2019

Dear HTA bodies that don’t routinely look for violations of proportional hazards in oncology data: 2005 called, they want their methods back.

Seriously though, it’s 2019. Things have moved on. If a new drug has a different mode of action to its comparator, is given for a different duration, or has differing levels of treatment effect in different population subgroups, there are good reasons to think that the trial data for that drug might violate proportional hazards. So why not look? It’s easy enough, and could change the way you think about both the costs and the benefits of that medicine.

If you haven’t worked in oncology before, there is a good chance you are currently asking yourself two questions: “what does proportional hazards mean?” and “why does it matter?”. In massively simplified terms, when we say the hazards in a trial are “proportional” we mean that the treatment effect of the new intervention (typically on survival) is constant over time. If a treatment takes some time to work (e.g. immunotherapies), or is given for only a few weeks before being stopped (e.g. some chemotherapies), there are good reasons to think that the treatment effect of that intervention may vary over time. If this is the case, there will be a violation of proportional hazards (they will be “nonproportional”).

If you are an HTA body, this is important for at least three reasons. First, if hazards are non-proportional, this can mean that the average hazard ratio (treatment effect) from the trial is a poor representation of what is likely to happen beyond the trial period – a big issue if you are extrapolating data in an economic model. Second, if hazards are non-proportional, this can mean that the median survival benefit from the trial is a poor representation of the mean benefit (e.g. in the case of a curve with a “big tail”). If you don’t account for this, and rely on medians (as some HTA bodies do), this can result in your evaluation under-estimating, or over-estimating, the true benefits and costs of the medicine. Third, most approaches to including indirect comparison in economic models rely on proportionality so, if this doesn’t hold, your model might be a poor representation of reality. Given these issues, it makes sense that HTA bodies should be looking for violations in proportional hazards when evaluating oncology data.

In this week’s second paper, the authors review the way different HTA bodies approach the issue of non-proportionality in their methods guides, and in a sample of their appraisals. Of the HTA bodies considered, they find that only NICE (UK), CADTH (Canada), and PBAC (Australia) recommend testing for proportional hazards. Notably, the authors report that the Transparency Committee (France), IQWiG (Germany), and TLV (Sweden) don’t recommend testing for proportionality. Interestingly, despite these recommendations, the authors find that solely the majority of NICE appraisals they reviewed included these tests, and that only 20% of the PBAC appraisals and 8% of the CADTH appraisals did. This suggests that the vast majority of oncology drug evaluations do not include consideration of non-proportionality – a big concern given the issues outlined above.

I liked this paper, although I was a bit shocked at the results. If you work for an HTA body that doesn’t recommend testing for non-proportionality, or doesn’t enforce their existing recommendations, I suggest you think very carefully about this issue – particularly if you rely on the extrapolation of survival curves in your assessments. If you aren’t looking for violations of proportional hazards, there is a good chance that you aren’t reflecting the true costs and benefits of many medicines in your evaluations. So, why not look for them?

The challenge of antimicrobial resistance: what economics can contribute. Science Published 5th April 2019

Health Economics doesn’t normally make it into Science (the journal). If it does, it probably means the paper is an important one. This one certainly is.

Antimicrobial resistance (AMR) is scary – really scary. One source cited in this paper predicts that by 2050, 10 million people a year will die due to AMR. I don’t know about you, but I find this pretty worrying (how’s that for a bit of British understatement?). Given these predicted consequences, you would think that there would be quite a lot of work from economists on this issue. Well, there isn’t. According to this article, there are only 55 papers on EconLit that “broadly relate” to AMR.

This paper contributes to this literature in two important ways. First, it is a call to arms to economists to do more work on AMR. If there are only 55 papers on this topic, this suggests we are only scratching the surface of the issue and could do more as a field contribute to helping solve the problem. Second, it neatly demonstrates how economics could be applied to the problem of AMR – including analysis of both the supply side (not enough new antibiotics being developed) and demand side (too much antibiotic use) of the problem.

In the main body of the paper, the authors draw parallels between the economics of AMR and the economics of climate change: both are global instances of the ‘tragedy of the commons’, both are subject to significant uncertainty about the future, and both are highly sensitive to inter-temporal discounting. They then go on to suggest that many of the ideas developed in the context of climate change could be applied to AMR – including the potential for use of antibiotic prescribing quotas (analogous to carbon quotas) and taxation of antibiotic prescriptions (analogous to the idea of a carbon tax). There are many other ideas in the paper, and if you are interested in these I suggest you take the time to read it in full.

I think this is an important paper and one that has made me think more about the economics of both AMR and, inadvertently, climate change. With both issues, I can’t help but think we might be sleepwalking into a world where we have royally screwed over future generations because we didn’t take the actions we needed to take. If economists can help stop these things happening, we need to act. If we don’t, what will you say in 2050 when you turn on the news and see that 10 million people are dying from AMR each year? That is, assuming you aren’t one of those who has died as a result. Scary stuff indeed.

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Simon McNamara’s journal round-up for 21st January 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.

Assessing capability in economic evaluation: a life course approach? The European Journal of Health Economics [PubMed] Published 8th January 2019

If you have spent any time on social media in the last week there is a good chance that you will have seen the hashtag #10yearchallenge. This hashtag is typically accompanied by two photos of the poster; one recent, and one from 10 years ago. Whilst the minority of these posts suggest that the elixir of permanent youth has been discovered and is being hidden away by a select group of people, the majority show clear signs of ageing. As time passes, we change. Our skin becomes wrinkled, our hair may become grey, and we may become heavier. What these pictures don’t show, is how we change internally – and I don’t mean biologically. As we become older, and we experience life, so the things we think are important change. Our souls become wrinkled, and our minds become heavier.

The first paper in this week’s round-up is founded on this premise, albeit grounded in the measurement of capability well-being across the life course, rather than a hashtag. The capabilities approach is grounded in the normative judgement that the desirability of policy outcomes should be evaluated by what Sen called the ‘capabilities’ they provide – “the functionings, or the capabilities to function” they give people, where functionings for a person are defined as “the various things that he or she manages to do or be in leading a good life” (Sen, 1993). The author (Joanna Coast) appeals to her, and others’, work on the family of ICECAP measures (capability measures), in order to argue that the capabilities we value changes across the stage of life we are experiencing. For example, she notes that the development work for the ICECAP-A (adults) resulted in the choice of an ‘achievement’ attribute in that instrument, whilst for ICECAP-O (older people) an alternative ‘role’ attribute was used – with the achievement attribute primarily linked to having the ability to make progress in life, and the role attribute linked to having the ability to do things that make you feel valued. Similarly, she notes that the attributes that emerged from development work on the ICECAP-SCM (supportive care – a term for the end of life) are different to those from ICECAP-A (adults), with dignity coming to the forefront as a valued attribute towards the end of life. The author then goes on to suggest that it would be normatively desirable to capture how the capabilities we value changes over the life-course, suggests this could be done with a range of different measures, and highlights a number of problems associated with this (e.g. when does a life-stage start and finish?).

You should read this paper. It is only four pages long and definitely worth your time. If you have spent enough time on social media to know what the #10yearchallenge is, then you definitely have time to read it. I think this is a really interesting topic and a great paper. It has certainly got me thinking more about capabilities, and I will be keeping an eye out for future papers on this in future.

Future directions in valuing benefits for estimating QALYs: is time up for the EQ-5D? Value in Health Published 17th January 2019

If EQ-5D were a person, I think I would be giving it a good hug right now. Every time my turn to write this round-up comes up there seems to be a new article criticising it, pointing out potential flaws in the way it has been valued, or proposing a new alternative. If it could speak, I imagine it would tell us it is doing its best – perhaps with a small tear in its eye. It has done what it can to evolve, it has tried to change, but as we approach its 30th birthday, and exciting new instruments are under development, the authors of the second paper in this week’s round-up question – “Is time up for the EQ-5D?”

If you are interested in the valuation of outcomes, you should probably read this paper. It is a really neat summary of recent developments in the assessment and valuation of the benefits of healthcare, and gives a good indication of where the field may be headed. Before jumping into reading the paper, it is worth dwelling on its title. Note that the authors have used the term “valuing benefits for estimating QALYs” and not “valuing health states for estimating QALYs”. This is telling, and reflects the growing interest in measuring, and valuing, the benefits of healthcare based upon a broader conception of well-being, rather than simply health as represented by the EQ-5D. It is this issue that rests at the heart of the paper, and is probably the biggest threat to the long-term domination of EQ-5D. If it wasn’t designed to capture the things we are now interested in, then why not modify it further, or go back to the drawing board and start again?

I am not going to attempt to cover all the points made in the paper, as I can’t do it justice in this blog; but in summary, the authors review a number of ways this could be done, outline recent developments in the way the subsequent instrument could be valued, and detail the potential advantages, disadvantages, and challenges of moving to a new instrument. Ultimately, the authors conclude that the future of the valuation of outcomes – be that with EQ-5D or something else, depends upon a number of judgements, including whether non-health factors are considered to be relevant when valuing the benefits of healthcare. If they are then EQ-5D isn’t fit for purpose, and we need a new instrument. Whilst the paper doesn’t provide a definitive answer to the question “Is Time Up for the EQ-5D?”, the fact that NICE, the EuroQol group, two of the authors of this paper, and a whole host of others, are currently collaborating on a new measure, which captures both health and non-health outcomes, indicates that EQ-5D may well be nearing the end of its dominance. I look forward to seeing how this work progresses over the next few years.

The association between economic uncertainty and suicide in the short-run. Social Science and Medicine [PubMed] [RePEc] Published 24th November 2018

As I write this, the United Kingdom is 10 weeks away from the date we are due to leave the European Union, and we are still uncertain about how, and potentially even whether, we will finally leave. The uncertainty created by Brexit covers both economic and social spheres, and impacts many of those in the United Kingdom, and many beyond who have ties to us. I am afraid the next paper isn’t a cheery one, but given this situation, it is a timely one.

In the final paper in this round-up, the authors explore the link between economic uncertainty and short-term suicide rates. This is done by linking the UK EPU index of economic uncertainty – an index generated based upon the articles published in 650 UK newspapers – to the daily suicide rates in England and Wales between 2001 and 2015. The authors find evidence of an increase in suicide rates on the days on which the EPU index was higher, and also of a lagged effect on the day after a spike in the index. Over the course of a year, this effect means a one standard deviation increase in the EPU is expected to lead to 11 additional deaths in that year. In comparison to the number of deaths per year from cardiovascular disease, and cancer, this effect is relatively modest, but is nevertheless concerning given the nature of the way in which these people are dying.

I am not going to pretend I enjoyed reading this paper. Technically it is good, and it is an interesting paper, but the topic was just a bit too dark and too relevant to our current situation. Whilst reading I couldn’t help but wonder whether I am going to be reading a similar paper linking Brexit uncertainty to suicide at some point in the future. Fingers crossed this isn’t the case.

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Thesis Thursday: Firdaus Hafidz

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 Firdaus Hafidz who has a PhD from the University of Leeds. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Assessing the efficiency of health facilities in Indonesia
Supervisors
Tim Ensor, Sand Tubeuf
Repository link
http://etheses.whiterose.ac.uk/id/eprint/21575

What are some of the key features of health and health care in Indonesia?

Indonesia is a diverse country, with more than 17 thousand islands and 500 districts. Thus, there is a wide discrepancy of health outcomes across Indonesia, which also reflects the country’s double burden of both communicable and emerging non-communicable diseases. Communicable diseases such as tuberculosis, diarrhoea and lower respiratory tract infections remain as significant issues in Indonesia, especially in remote areas. At the same time, non-communicable diseases are becoming a major public health problem, especially in urban areas.

Total healthcare expenditure per capita grew rapidly, but in certain outcomes, such as maternal mortality rate, Indonesia performs less well than other low- and middle-income countries. Health facilities represent the largest share of healthcare expenditures, but utilisation is still considered low in both hospitals and primary healthcare facilities. Given the scarcity of public healthcare resources, out-of-pocket expenditure remains considerably higher than the global average.

To reduce financial barriers, the Government of Indonesia introduced health insurance in 1968. Between 2011 and 2014, there were three major insurance schemes: 1) Jamkesmas – poor scheme; 2) Jamsostek – formal sector workers scheme; and 3) Askes – civil servant scheme. In 2014, the three schemes were combined into a single-entity National Health Insurance scheme.

What methods can be used to measure the efficiency of health care in low and middle-income countries?

We reviewed measurements of efficiency in empirical analyses conducted in low- and middle-income countries. Methods, including techniques, variables, and efficiency indicators were summarised. There was no consensus on the most appropriate technique to measure efficiency, though most existing studies have relied on ratio analysis and data envelopment analysis because it is simple, easy to compute, low-cost and can be performed on small samples. The physical inputs included the type of capital (e.g. the number of beds and size of health facilities) and the type of labour (e.g. the number of medical and non-medical staff). Most of the published literature used health services as outputs (e.g. the number of outpatient visits, admission and inpatient days). However, because of poor data availability, fewer studies used case-mix and quality indicators to adjust outputs. So most of the studies in the literature review assumed that there was no difference in the severity and effectiveness of healthcare services. Despite the complexity of the techniques, researchers are responsible to provide interpretable results to the policymakers to guide their decisions for a better health policy on efficiency. Adopting appropriate methods that have been used globally would be beneficial to benchmark empirical studies.

Were you able to identify important sources of inefficiency in Indonesia?

We used several measurement techniques including frontier analysis and ratio analysis. We explored contextual variables to assess factors determining efficiency. The range of potential models produced help policymakers in the decision-making process according to their priority and allow some control over the contextual variables. The results revealed that the efficiency of primary care facilities can be explained by population health insurance coverage, especially through the insurance scheme for the poor. Geographical factors, such as the main islands (Java or Bali), better access to health facility, and location in an urban area also have a strong impact on efficiency. At the hospitals, the results highlighted higher efficiency levels in larger hospitals; they were more likely to present in deprived areas with low levels of education; and they were located on Java or Bali. Greater health insurance coverage also had a positive and significant influence on efficiency.

How could policymakers improve the efficiency of health care in Indonesia or other similar settings?

I think there are several ideas. First, we need to have a careful tariff adjustment as we found an association between low unit costs and high efficiency scores. Case base group tariffs need to account for efficiency scores to prevent unnecessary incentives for the providers, exacerbating inefficiency in the health system.

Secondly, we need flexibility in employment contracts, particularly for the less productive civil servant worker so the less productive worker could be reallocated. We also need a better remuneration policy to attract skilled labour and improve health facilities efficiency.

From the demand side, reducing physical barriers by improving infrastructure could increase efficiency in the rural health care facilities through higher utilisation of care. Facilities with very low utilisation rates still incur a fixed cost and thus create inefficiency. Through the same argument we also need to reduce financial barriers using incentives programmes and health insurance, thus patients who are economically disadvantaged can access healthcare services.

How would you like to see other researchers build on your work?

Data quality is crucial in secondary data analysis research, and it was quite a challenge in an Indonesian setting. Meticulous data management is needed to mitigate data errors such as inconsistency, outliers and missing values.

As this study used a 2011 cross-sectional dataset, replicating this study using a more recent and even longitudinal data would highlight changes in efficiency due to policy changes or interventions. Particularly interesting is the effect of the 2014 implementation of Indonesian national health insurance.

My study has some limitations and thus warrants further investigation. The stochastic frontier analysis failed to identify any inefficiency at hospitals when outpatient visits were included. The statistical errors of the frontier function cannot be distinguished from the inefficiency effect of the model. It might be related to the volume and heterogeneity of outpatient services which swamps the total volume of services and masks any inefficiency.