Chris Sampson’s journal round-up for 6th January 2020

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.

Child sleep and mother labour market outcomes. Journal of Health Economics [PubMed] [RePEc] Published January 2020

It’s pretty clear that sleep is important to almost all aspects of our lives and our well-being. So it is perhaps surprising that economists have paid relatively little attention to the ways in which the quality of sleep influences the ‘economic’ aspects of our lives. Part of the explanation might be that almost anything that you can imagine having an effect on your sleep is also likely to be affected by your sleep. Identifying causality is a challenge. This paper shows us how it’s done.

The study is focussed on the relationship between sleep and labour market outcomes in new mothers. There’s good reason to care about new mothers’ sleep because many new mothers report that lack of sleep is a problem and many suffer from mental and physical health problems that might relate to this. But the major benefit to this study is that the context provides a very nice instrument to help identify causality – children’s sleep. The study uses data from the Avon Longitudinal Study of Parents and Children (ALSPAC), which seems like an impressive data set. The study recruited 14,541 pregnant women with due dates between 1991 and 1993, collecting data on mothers’ and children’s sleep quality and mothers’ labour market activity. The authors demonstrate that children’s sleep (in terms of duration and disturbances) affects the amount of sleep that mothers get. No surprise there. They then demonstrate that the amount of sleep that mothers get affects their labour market outcomes, in terms of their likelihood of being in employment, the number of hours they work, and household income. The authors also demonstrate that children’s sleep quality does not have a direct impact on mothers’ labour market outcomes except through its effect on mothers’ sleep. The causal mechanism seems difficult to refute.

Using a two-stage least squares model with a child’s sleep as an instrument for their mother’s sleep, the authors estimate the effect of mothers’ sleep on labour market outcomes. On average, a 30-minute increase in a mother’s sleep duration increases the number of hours she works by 8.3% and increases household income by 3.1%. But the study goes further (much further) by identifying the potential mechanisms for this effect, with numerous exploratory analyses. Less sleep makes mothers more likely to self-report having problems at work. It also makes mothers less likely to work full-time. Going even further, the authors test the impact of the UK Employment Rights Act 1996, which gave mothers the right to request flexible working. The effect of the Act was to reduce the impact of mothers’ sleep duration on labour market outcomes, with a 6 percentage points lower probability that mothers drop out of the labour force.

My only criticism of this paper is that the copy-editing is pretty poor! There are so many things in this study that are interesting in their own right but also signal need for further research. Unsurprisingly, the study identifies gender inequalities. No wonder men’s wages increase while women’s plateau. Personally, I don’t much care about labour market outcomes except insofar as they affect individuals’ well-being. Thanks to the impressive data set, the study can also show that the impact on women’s labour market outcomes is not simply a response to changing priorities with respect to work, implying that it is actually a problem. The study provides a lot of food for thought for policy-makers.

Health years in total: a new health objective function for cost-effectiveness analysis. Value in Health Published 23rd December 2019

It’s common for me to complain about papers on this blog, usually in relation to one of my (many) pet peeves. This paper is in a different category. It’s dangerous. I’m angry.

The authors introduce the concept of ‘health years in total’. It’s a simple idea that involves separating the QA and the LY parts of the QALY in order to make quality of life and life years additive instead of multiplicative. This creates the possibility of attaching value to life years over and above their value in terms of the quality of life that is experienced in them. ‘Health years’ can be generated at a rate of two per year because each life year is worth 1 and that 1 is added to what the authors call a ‘modified QALY’. This ‘modified QALY’ is based on the supposition that the number of life years in its estimation corresponds to the maximum number of life years available under any treatment scenario being considered. So, if treatment A provides 2 life years and treatment B provides 3 life years, you multiply the quality of life value of treatment A by 3 years and then add the number of actual life years (i.e. 2). On the face of it, this is as stupid as it sounds.

So why do it? Well, some people don’t like QALYs. A cabal of organisations, supposedly representing patients, has sought to undermine the use of cost-effectiveness analysis. For whatever reason, they have decided to pursue the argument that the QALY discriminates against people with disabilities, or anybody else who happens to be unwell. Depending on the scenario this is either untrue or patently desirable. But the authors of this paper seem happy to entertain the cabal. The foundation for the development of the ‘health years in total’ framework is explicitly based in the equity arguments forwarded by these groups. It’s designed to be a more meaningful alternative to the ‘equal value of life’ measure; a measure that has been used in the US context, which adds a value of 1 to life years regardless of their quality.

The paper does a nice job of illustrating the ‘health years in total’ approach compared with the QALY approach and the ‘equal value of life’ approach. There’s merit in considering alternatives to the QALY model, and there may be value in an ‘additive’ approach that in some way separates the valuation of life years from the valuation of health states. There may even be some ethical justification for the ‘health years in total’ framework. But, if there is, it isn’t provided by this paper. To frame the QALY as discriminatory in the way that the authors do, describing this feature as a ‘limitation’ of the QALY approach, and to present an alternative with no basis in ethics is, at best, foolish. In practice, the ‘health years in total’ calculation would favour life-extending treatments over those that improve health. There are some organisations with vested interests in this. Expect to see ‘health years in total’ obscuring decision-making in the United States in the near future.

The causal effect of education on chronic health conditions in the UK. Journal of Health Economics Published 23rd December 2019

Since the dawn of health economics, researchers have been interested in the ways in which education and health outcomes depend on one another. People with more education tend to be healthier. But identifying causal relationships in this context is almost impossible. Some studies have claimed that education has a positive (causal) effect on both general and specific health outcomes. But there are just as many studies that show no impact. This study attempts to solve the problem by throwing a lot of data at it.

The authors analyse the impact of two sets of reforms in the UK. First, the raising of the school leaving age in 1972, from 15 to 16 years. Second, the broader set of reforms that were implemented in the 1990s that resulted in a major increase in the number of people entering higher education. The study’s weapon is the Quarterly Labour Force Survey (QLFS), which includes over 5 million observations from 1.5 million people. Part of the challenge of identifying the impact of education on health outcomes is that the effects can be expected to be observed over the long-term and can therefore be obscured by other long-term trends. To address this, the authors limit their analyses to people in narrow age ranges in correspondence with the times of the reforms. Thanks to the size of the data set, they still have more than 350,000 observations for each reform. The QLFS asks people to self-report having any of a set of 17 different chronic health conditions. These can be grouped in a variety of ways, or looked at individually. The analysis uses a regression discontinuity framework to test the impact of raising the school leaving age, with birth date acting as an instrument for the number of years spent in education. The analysis of the second reform is less precise, as there is no single discontinuity, so the model identifies variation between the relevant cohorts over the period. The models are used to test a variety of combinations of the chronic condition indicators.

In short, the study finds that education does not seem to have a causal effect on health, in terms of the number of chronic conditions or the probability of having any chronic condition. But, even with their massive data set, the authors cannot exclude the possibility that education does have an effect on health (whether positive or negative). This non-finding is consistent across both reforms and is robust to various specifications. There is one potentially important exception to this. Diabetes. Looking at the school leaving age reform, an additional year of schooling reduces the likelihood of having diabetes by 3.6 percentage points. Given the potential for diabetes to depend heavily on an individual’s behaviour and choices, this seems to make sense. Kids, stay in school. Just don’t do it for the good of your health.

Credits

Rita Faria’s journal round-up for 4th March 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.

Cheap and dirty: the effect of contracting out cleaning on efficiency and effectiveness. Public Administration Review Published 25th February 2019

Before I was a health economist, I used to be a pharmacist and worked for a well-known high street chain for some years. My impression was that the stores with in-house cleaners were cleaner, but I didn’t know if this was a true difference, my leftie bias or my small sample size of 2! This new study by Shimaa Elkomy, Graham Cookson and Simon Jones confirms my suspicions, albeit in the context of NHS hospitals, so I couldn’t resist to select it for my round-up.

They looked at how contracted-out services fare in terms of perceived cleanliness, costs and MRSA rate in NHS hospitals. MRSA is a type of hospital-associated infection that is affected by how clean a hospital is.

They found that contracted-out services are cheaper than in-house cleaning, but that perceived cleanliness is worse. Importantly, contracted-out services increase the MRSA rate. In other words, contracting-out cleaning services could harm patients’ health.

This is a fascinating paper that is well worth a read. One wonders if the cost of managing MRSA is more than offset by the savings of contracting-out services. Going a step further, are in-house services cost-effective given the impact on patients’ health and costs of managing infections?

What’s been the bang for the buck? Cost-effectiveness of health care spending across selected conditions in the US. Health Affairs [PubMed] Published 1st January 2019

Staying on the topic of value for money, this study by David Wamble and colleagues looks at the extent to which the increased spending in health care in the US has translated into better health outcomes over time.

It’s clearly reassuring that, for 6 out of the 7 conditions they looked at, health outcomes have improved in 2015 compared to 1996. After all, that’s the goal of investing in medical R&D, although it remains unclear how much of this difference can be attributed to health care versus other things that have happened at the same time that could have improved health outcomes.

I wasn’t sure about the inflation adjustment for the costs, so I’d be grateful for your thoughts via comments or Twitter. In my view, we would underestimate the costs if we used medical price inflation indices. This is because these indices reflect the specific increase in prices in health care, such as due to new drugs being priced high at launch. So I understand that the main results use the US Consumer Price Index, which means that this reflects the average increase in prices over time rather than the increase in health care.

However, patients may not have seen their income rise with inflation. This means that the cost of health care may represent a disproportionally greater share of people’s income. And that the inflation adjustment may downplay the impact of health care costs on people’s pockets.

This study caught my eye and it is quite thought-provoking. It’s a good addition to the literature on the cost-effectiveness of US health care. But I’d wager that the question remains: to what extent is today’s medical care better value for money that in the past?

The dos and don’ts of influencing policy: a systematic review of advice to academics. Palgrave Communications Published 19th February 2019

We all would like to see our research findings influence policy, but how to do this in practice? Well, look no further, as Kathryn Oliver and Paul Cairney reviewed the literature, summarised it in 8 key tips and thought through their implications.

To sum up, it’s not easy to influence policy; advice about how to influence policy is rarely based on empirical evidence, and there are a few risks to trying to become a mover-and-shaker in policy circles.

They discuss three dilemmas in policy engagement. Should academics try to influence policy? How should academics influence policy? What is the purpose of academics’ engagement in policy making?

I particularly enjoyed reading about the approaches to influence policy. Tools such as evidence synthesis and social media should make evidence more accessible, but their effectiveness is unclear. Another approach is to craft stories to create a compelling case for the policy change, which seems to me to be very close to marketing. The third approach is co-production, which they note can give rise to accusations of bias and can have some practical challenges in terms of intellectual property and keeping one’s independence.

I found this paper quite refreshing. It not only boiled down the advice circulating online about how to influence policy into its key messages but also thought through the practical challenges in its application. The impact agenda seems to be here to stay, at least in the UK. This paper is an excellent source of advice on the risks and benefits of trying to navigate the policy world.

Credits

Meeting round-up: Health Economists’ Study Group (HESG) Winter 2018

Last week’s biannual intellectual knees-up for UK health economists took place at City, University of London. We’ve written before about HESG, but if you need a reminder of the format you can read Lucy Abel’s blog post on the subject. This was the first HESG I’ve been to in a while that took place in an actual university building.

The conference kicked off for me with my colleague Grace Hampson‘s first ever HESG discussion. It was an excellent discussion of Toby Watt‘s paper on the impact of price promotions for cola, in terms of quantities purchased (they increase) and – by extension – sugar consumption. It was a nice paper with a clear theoretical framework and empirical strategy, which generated a busy discussion. Nutrition is a subject that I haven’t seen represented much at past HESG meetings, but there were several on the schedule this time around with other papers by Jonathan James and Ben Gershlick. I expect it’s something we’ll see becoming more prevalent as policymaking becomes more insistent.

The second and third sessions I attended were on the relationship between health and social care, which is a pressing matter in the UK, particular with regard to achieving integrated care. Ben Zaranko‘s paper considered substitution effects arising from changes in the relative budgets of health and social care. Jonathan Stokes and colleagues attempted to identify whether the Better Care Fund has achieved its goal of reducing secondary care use. That paper got a blazing discussion from Andrew Street that triggered an insightful discussion in the room.

A recurring theme in many sessions was the challenge of communicating with local decision-makers, and the apparent difficulty in working without a reference case to fall back on (such as that of NICE). This is something that I have heard regularly discussed at least since the Winter 2016 meeting in Manchester. At City, this was most clearly discussed in Emma Frew‘s paper describing the researchers’ experiences working with local government. Qualitative research has clearly broken through at HESG, including Emma’s paper and a study by Hareth Al-Janabi on the subject of treatment spillovers on family carers.

I also saw a few papers that related primarily to matters of research conduct and publishing. Charitini Stavropoulou‘s paper explored whether highly-cited researchers are more likely to receive public funding, while the paper I chaired by Anum Shaikh explored the potential for recycling cost-effectiveness models. The latter was a joy for me, with much discussion of model registries!

There were plenty of papers that satisfied my own particular research interests. Right up my research street was Mauro Laudicella‘s paper, which used real-world data to assess the cost savings associated with redirecting cancer diagnoses to GP referral rather than emergency presentation. I wasn’t quite as optimistic about the potential savings, with the standard worries about lead time bias and selection effects. But it was a great paper nonetheless. Also using real-world evidence was Ewan Gray‘s study, which supported the provision of adjuvant chemotherapy for early stage breast cancer but delivered some perplexing findings about patient-GP decision-making. Ewan’s paper explored technical methodological challenges, though the prize for the most intellectually challenging paper undoubtedly goes to Manuel Gomes, who continued his crusade to make health economists better at dealing with missing data – this time for the case of quality of life data. Milad Karimi‘s paper asked whether preferences over health states are informed. This is the kind of work I enjoy thinking about – whether measures like the EQ-5D capture what really matters and how we might do better.

As usual, many delegates worked hard and played hard. I took a beating from the schedule at this HESG, with my discussion taking place during the first session after the conference dinner (where we walked in the footsteps of the Spice Girls) and my chairing responsibilities falling on the last session of the last day. But in both cases, the audience was impressive.

I’ll leave the final thought for the blog post with Peter Smith’s plenary, which considered the role of health economists in a post-truth world. Happily, for me, Peter’s ideas chimed with my own view that we ought to be taking our message to the man on the Clapham omnibus and supporting public debate. Perhaps our focus on (national) policymakers is too strong. If not explicit, this was a theme that could be seen throughout the meeting, whether it be around broader engagement with stakeholders, recognising local decision-making processes, or harnessing the value of storytelling through qualitative research. HESG members are STRETCHing the truth.

Credit