Rita Faria’s journal round-up for 13th May 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.

Communicating uncertainty about facts, numbers and science. Royal Society Open Science Published 8th May 2019

This remarkable paper by Anne Marthe van der Bles and colleagues, including the illustrious David Spiegelhalter, covers two of my most favourite topics: communication and uncertainty. They focused on epistemic uncertainty. That is, the uncertainty about facts, numbers and science due to limited knowledge (rather than due to the randomness of the world). This is what we could know more about, if we spent more resources in finding it out.

The authors propose a framework for communicating uncertainty and apply it to two case studies, one in climate change and the other in economic statistics. They also review the literature on the effect of communicating uncertainty. It is so wide-ranging and exhaustive that, if I have any criticism, its 42 pages are not conducive to a leisurely read.

I found the distinction between direct and indirect uncertainty fascinating and incredibly relevant to health economics. Direct uncertainty is about the precision of the evidence whilst indirect uncertainty is about its quality. For example, evidence based on a naïve comparison of patients in a Phase 2 trial with historical controls in another country (yup, this happens!).

So, how should we communicate the uncertainty in our findings? I’m afraid that this paper is not a practical guide but rather a brilliant ground clearing exercise on how to start thinking about this. Nevertheless Box 5 (p35) does give some good advice! I do hope this paper kick-starts research on how to explain uncertainty beyond an academic audience. Looking forward to more!

Was Brexit triggered by the old and unhappy? Or by financial feelings? Journal of Economic Behavior & Organization [RePEc] Published 18th April 2019

Not strictly health economics – although arguably Brexit affects our health – is this impressive study about the factors that contributed to the Leave win in the Brexit referendum. Federica Liberini and colleagues used data from the Understanding Society survey to look at the predictors of people’s views about whether or not the UK should leave the EU. The main results are from a regression on whether or not a person was pro-Brexit, regressed on life satisfaction, their feelings on their financial situation, and other characteristics.

Their conclusions are staggering. They found that people’s views were generally unrelated to their age, their life satisfaction or their income. Instead, it was a person’s feelings about their financial situation that was the strongest predictor. For economists, it may be a bit cringe-worthy to see OLS used for a categorical dependent variable. But to be fair, the authors mention that the results are similar with non-linear models and they report extensive supplementary analyses. Remarkably, they’re making the individual level data available on the 18th of June here.

As the authors discuss, it is not clear if we’re looking at predictive estimates of characteristics related to pro-Brexit feeling or at causal estimates of factors that led to the pro-Brexit feeling. That is, if we could improve someone’s perceived financial situation, would we reduce their probability of feeling pro-Brexit? In any case, the message is clear. Feelings matter!

How does treating chronic hepatitis C affect individuals in need of organ transplants in the United Kingdom? Value in Health Published 8th March 2019

Anupam Bapu Jena and colleagues looked at the spillover benefits of curing hepatitis C given its consequences on the supply and demand of liver and other organs for transplant in the UK. They compare three policies: the status quo, in which there is no screening for hepatitis C and organ donation by people with hepatitis C is rare; universal screen and treat policy where cured people opt-in for organ donation; and similarly, but with opt-out for organ donation.

To do this, they adapted a previously developed queuing model. For the status quo, the model inputs were estimated by calibrating the model outputs to reported NHS performance. They then changed the model inputs to reflect the anticipated impact of the new policies. Importantly, they assumed that all patients with hepatitis C would be cured and no longer require a transplanted organ; conversely, that cured patients would donate organs at similar rates to the general population. They predict that curing hepatitis C would directly reduce the waiting list for organ transplants by reducing the number of patients needing them. Also, there would be an indirect benefit via increasing their availability to other patients. These consequences aren’t typically included in the cost-effectiveness analysis of treatments for hepatitis C, which means that their comparative benefits and costs may not be accurate.

Keeping in the theme of uncertainty, it was disappointing that the paper does not include some sort of confidence bounds on its results nor does it present sensitivity analysis to their assumptions, which in my view, were quite favourable towards a universal screen and test policy. This is an interesting application of a queuing model, which is something I don’t often see in cost-effectiveness analysis. It is also timely and relevant, given the recent drive by the NHS to eliminate hepatitis C. In a few years’ time, we’ll hopefully know to what extent the predicted spillover benefits were realised.

Credits

Rita Faria’s journal round-up for 15th 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.

Emulating a trial of joint dynamic strategies: an application to monitoring and treatment of HIV‐positive individuals. Statistics in Medicine [PubMed] Published 18th March 2019

Have you heard about the target trial approach? This is a causal inference method for using observational evidence to compare strategies. This outstanding paper by Ellen Caniglia and colleagues is a great way to get introduced to it!

The question is: what is the best test-and-treat strategy for HIV-positive individuals? Given that patients weren’t randomised to each of the 4 alternative strategies, chances are that their treatment was informed by their prognostic factors. And these also influence their outcome. It’s a typical situation of bias due to confounding. The target trial approach consists of designing the RCT which would estimate the causal effect of interest, and to think through how its design can be emulated by the observational data. Here, it would be a trial in which patients would be randomly assigned to one of the 4 joint monitoring and treatment strategies. The goal is to estimate the difference in outcomes if all patients had followed their assigned strategies.

The method is fascinating albeit a bit complicated. It involves censoring individuals, fitting survival models, estimating probability weights, and replicating data. It is worthy of a detailed read! I’m very excited about the target trial methodology for cost-effectiveness analysis with observational data. But I haven’t come across any application yet. Please do get in touch via comments or Twitter if you know of a cost-effectiveness application.

Achieving integrated care through commissioning of primary care services in the English NHS: a qualitative analysis. BMJ Open [PubMed] Published 1st April 2019

Are you confused about the set-up of primary health care services in England? Look no further than Imelda McDermott and colleagues’ paper.

The paper starts by telling the story of how primary care has been organised in England over time, from its creation in 1948 to current times. For example, I didn’t know that there are new plans to allow clinical commissioning groups (CCGs) to design local incentive schemes as an alternative to the Quality and Outcomes Framework pay-for-performance scheme. The research proper is a qualitative study using interviews, telephone surveys and analysis of policy documents to understand how the CCGs commission primary care services. CCG Commissioning is intended to make better and more efficient use of resources to address increasing demand for health care services, staff shortage and financial pressure. The issue is that it is not easy to implement in practice. Furthermore, there seems to be some “reinvention of the wheel”. For example, from one of the interviewees: “…it’s no great surprise to me that the three STPs that we’ve got are the same as the three PCT clusters that we broke up to create CCGs…” Hum, shall we just go back to pre-2012 then?

Even if CCG commissioning does achieve all it sets out to do, I wonder about its value for money given the costs of setting it up. This paper is an exceptional read about the practicalities of implementing this policy in practice.

The dark side of coproduction: do the costs outweight the benefits for health research? Health Research Policy and Systems [PubMed] Published 28th March 2019

Last month, I covered the excellent paper by Kathryn Oliver and Paul Cairney about how to get our research to influence policy. This week I’d like to suggest another remarkable paper by Kathryn, this time with Anita Kothari and Nicholas Mays, on the costs and benefits of coproduction.

If you are in the UK, you have certainly heard about public and patient involvement or PPI. In this paper, coproduction refers to any collaborative working between academics and non-academics, of which PPI is one type, but it includes working with professionals, policy makers and any other people affected by the research. The authors discuss a wide range of costs to coproduction. From the direct costs of doing collaborative research, such as organising meetings, travel arrangements, etc., to the personal costs on an individual researcher to manage conflicting views and disagreements between collaborators, of having research products seen to be of lower quality, of being seen as partisan, etc., and costs to the stakeholders themselves

As a detail, I loved the term “hit-and-run research” to describe the current climate: get funding, do research, achieve impact, leave. Indeed, the way that research is funded, with budgets only available for the period that the research is being developed, does not help academics to foster relationships.

This paper reinforced my view that there may well be benefits to coproduction, but that there are also quite a lot of costs. And there tends to be not much attention to the magnitude of those costs, in whom they fall, and what’s displaced. I found the authors’ advice about the questions to ask oneself when thinking about coproduction to be really useful. I’ll keep it to hand when writing my next funding application, and I recommend you do too!

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