Chris Sampson’s journal round-up for 19th March 2018

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.

Using HTA and guideline development as a tool for research priority setting the NICE way: reducing research waste by identifying the right research to fund. BMJ Open [PubMed] Published 8th March 2018

As well as the cost-effectiveness of health care, economists are increasingly concerned with the cost-effectiveness of health research. This makes sense, given that both are usually publicly funded and so spending on one (in principle) limits spending on the other. NICE exists in part to prevent waste in the provision of health care – seeking to maximise benefit. In this paper, the authors (all current or ex-employees of NICE) consider the extent to which NICE processes are also be used to prevent waste in health research. The study focuses on the processes underlying NICE guideline development and HTA, and the work by NICE’s Science Policy and Research (SP&R) programme. Through systematic review and (sometimes) economic modelling, NICE guidelines identify research needs, and NICE works with the National Institute for Health Research to get their recommended research commissioned, with some research fast-tracked as ‘NICE Key Priorities’. Sometimes, it’s also necessary to prioritise research into methodological development, and NICE have conducted reviews to address this, with the Internal Research Advisory Group established to ensure that methodological research is commissioned. The paper also highlights the roles of other groups such as the Decision Support Unit, Technical Support Unit and External Assessment Centres. This paper is useful for two reasons. First, it gives a clear and concise explanation of NICE’s processes with respect to research prioritisation, and maps out the working groups involved. This will provide researchers with an understanding of how their work fits into this process. Second, the paper highlights NICE’s current research priorities and provides insight into how these develop. This could be helpful to researchers looking to develop new ideas and proposals that will align with NICE’s priorities.

The impact of the minimum wage on health. International Journal of Health Economics and Management [PubMed] Published 7th March 2018

The minimum wage is one of those policies that is so far-reaching, and with such ambiguous implications for different people, that research into its impact can deliver dramatically different conclusions. This study uses American data and takes advantage of the fact that different states have different minimum wage levels. The authors try to look at a broad range of mechanisms by which minimum wage can affect health. A major focus is on risky health behaviours. The study uses data from the Behavioral Risk Factor Surveillance System, which includes around 300,000 respondents per year across all states. Relevant variables from these data characterise smoking, drinking, and fruit and vegetable consumption, as well as obesity. There are also indicators of health care access and self-reported health. The authors cut their sample to include 21-64-year-olds with no more than a high school degree. Difference-in-differences are estimated by OLS according to individual states’ minimum wage changes. As is often the case for minimum wage studies, the authors find several non-significant effects: smoking and drinking don’t seem to be affected. Similarly, there isn’t much of an impact on health care access. There seems to be a small positive impact of minimum wage on the likelihood of being obese, but no impact on BMI. I’m not sure how to interpret that, but there is also evidence that a minimum wage increase leads to a reduction in fruit and vegetable consumption, which adds credence to the obesity finding. The results also demonstrate that a minimum wage increase can reduce the number of days that people report to be in poor health. But generally – on aggregate – there isn’t much going on at all. So the authors look at subgroups. Smoking is found to increase (and BMI decrease) with minimum wage for younger non-married white males. Obesity is more likely to be increased by minimum wage hikes for people who are white or married, and especially for those in older age groups. Women seem to benefit from fewer days with mental health problems. The main concerns identified in this paper are that minimum wage increases could increase smoking in young men and could reduce fruit and veg consumption. But I don’t think we should overstate it. There’s a lot going on in the data, and though the authors do a good job of trying to identify the effects, other explanations can’t be excluded. Minimum wage increases probably don’t have a major direct impact on health behaviours – positive or negative – but policymakers should take note of the potential value in providing public health interventions to those groups of people who are likely to be affected by the minimum wage.

Aligning policy objectives and payment design in palliative care. BMC Palliative Care [PubMed] Published 7th March 2018

Health care at the end of life – including palliative care – presents challenges in evaluation. The focus is on improving patients’ quality of life, but it’s also about satisfying preferences for processes of care, the experiences of carers, and providing a ‘good death’. And partly because these things can be difficult to measure, it can be difficult to design payment mechanisms to achieve desirable outcomes. Perhaps that’s why there is no current standard approach to funding for palliative care, with a lot of variation between countries, despite the common aspiration for universality. This paper tackles the question of payment design with a discussion of the literature. Traditionally, palliative care has been funded by block payments, per diems, or fee-for-service. The author starts with the acknowledgement that there are two challenges to ensuring value for money in palliative care: moral hazard and adverse selection. Providers may over-supply because of fee-for-service funding arrangements, or they may ‘cream-skim’ patients. Adverse selection may arise in an insurance-based system, with demand from high-risk people causing the market to fail. These problems could potentially be solved by capitation-based payments and risk adjustment. The market could also be warped by blunt eligibility restrictions and funding caps. Another difficulty is the challenge of achieving allocative efficiency between home-based and hospital-based services, made plain by the fact that, in many countries, a majority of people die in hospital despite a preference for dying at home. The author describes developments (particularly in Australia) in activity-based funding for palliative care. An interesting proposal – though not discussed in enough detail – is that payments could be made for each death (per mortems?). Capitation-based payment models are considered and the extent to which pay-for-performance could be incorporated is also discussed – the latter being potentially important in achieving those process outcomes that matter so much in palliative care. Yet another challenge is the question of when palliative care should come into play, because, in some cases, it’s a matter of sooner being better, because the provision of palliative care can give rise to less costly and more preferred treatment pathways. Thus, palliative care funding models will have implications for the funding of acute care. Throughout, the paper includes examples from different countries, along with a wealth of references to dig into. Helpfully, the author explicitly states in a table the models that different settings ought to adopt, given their prevailing model. As our population ages and the purse strings tighten, this is a discussion we can expect to be having more and more.

Credits

 

Thesis Thursday: Thomas Allen

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 Thomas Allen who graduated with a PhD from the University of Manchester. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
The impact of provider incentives on professionals and patients
Supervisors
Matt Sutton, William Whittaker
Repository link
https://www.escholar.manchester.ac.uk/item/?pid=uk-ac-man-scw:296844

Let’s dive straight in: what was the most important or overarching finding of your research?

My thesis focused on a large financial incentive scheme for UK GPs. So the thesis is a collection of UK studies, but I think the main findings can be generalised reasonably well.

Two of these studies actually looked at how the non-financial incentives of the scheme affected GPs, namely reputation and peer effects. I found reputation became more important, compared to revenue, a few years into the scheme. My explanation for this: reputation matters once you can observe performance benchmarks.

As for peer effects, the focus was on how practices react to their peer groups getting larger, this was caused by mergers in PCTs (groups of practices). You might expect peer effects to shrink when the group gets larger and this is what I found. Practice performance is also pulled down by poor peers more than it is pulled up by good peers. An analogy to merging a good classroom with a bad classroom is helpful to imagine.

There is quite a lot of variation (at GP level) in the amount of income that was linked to performance, 10-30% in most cases, so the third study exploits this variation. The size of this exposure to performance pay does affect GPs working lives – their job satisfaction, working hours, intentions to quit etc.

The final study was pretty novel as it linked patient reported quality with practice reported quality. It seemed to be the case that as practices improved on the incentivised areas of quality (e.g. blood pressure test) they got worse on the non-incentivised areas (communication).

What were the main methodologies that you used and which researchers’ work did your study most depend on?

It was a quantitative thesis so various regression methods were used. I’ll admit there was nothing particularly special or new with the methods used, they were standard methods but I think they were applied in interesting ways. For example, two studies linked existing datasets in new ways so I could answer questions which would have otherwise been impossible, probably. One method used which is not so common was the continuous difference in differences from the job satisfaction chapter. It’s been used before by David Card and Carol Propper. It can be used when you have a continuous treatment variable, instead of the typical treatment vs control situation. Everyone is treated but there is some exogenous factor deciding the amount of treatment.

I’m not sure there is one researcher that my study most depended on. The four different empirical chapters were influenced by slightly different literatures. Two big influences were systematic reviews of financial incentives (Scott et al. 2011) and of the scheme which I studied (Steel & Willems 2010). Both helped to identify areas where I could add to the existing literature.

What was the most surprising thing that you discovered; was there anything odd or unexpected?

Lots of theories would suggest an effect of pay for performance on job satisfaction and working lives. For example, large financial incentives should crowd out internal motivation and so reduce job satisfaction. Pay for performance appeals more to risk seeking individuals; those who are risk averse should feel uncomfortable as more income is linked to performance. Pay for performance can often result in wage dispersion, where incomes differ because some individuals perform better, this is usually linked to lower job satisfaction. A section of Chapter 6 is dedicated to these theories but I found no effect of pay for performance on GPs’ job satisfaction or working lives. Even specific areas you would expect to be affected weren’t, like satisfaction with choice of working methods or levels of autonomy.

This was certainly an unexpected result but I think still very interesting. I was able to publish this quite recently in Social Science & Medicine.

What was the biggest challenge that you encountered during your PhD, and did it change the direction of your research?

I started to answer this saying I didn’t have any big challenges but then a few came to me. I guess looking back they don’t seem as significant as they were at the time.

In the first few weeks I realised one of the studies from the PhD proposal couldn’t be done – basically I wanted to use PROMs to analyse a policy but had glossed over the difference between hip fractures and hip replacements, which seems very obvious now. I had to think of Plan B.

Plan B turned into Plan C around the end of my second year. I was going to try linking three datasets to measure the impact of pay for performance using administrative data, patient data and GP data. Imagine a Venn diagram of the overlapping samples from these three datasets. In the end the sample covered by all three was too small.

I’m pleased with how the thesis turned out, these challenges ended up improving the finished product.

Have you any words of wisdom for any researchers who might be embarking on a similar programme of research?

On this research area… The incentive scheme I focused on, the QOF, has been around for 12 years. If you have a new research question maybe someone else already tried it and it doesn’t work. Review the literature well and talk to those who have done work on the scheme. My internal examiner was a GP. She gave some great insight which would have been helpful at the start of the PhD not the end! So if you can, talk with those affected by the incentive or policy you are evaluating – it might not work in the way described in policy documents.

On PhDs generally… Choose your supervisors wisely – they are more than just a boss/manager, so try and find someone you think you can work with, not for. If you can, have a professor and a less senior person. Matt and Will were a great combo. In the end you might find you are sick of the PhD topic, so make sure you at least start off liking it. Don’t just pick it because it is the only one going. Try and do some extra work: teaching, collaborate with others, blogs. But make sure you gain from it in some way. Plan your time well at the start. You won’t stick to it, but at least you’ll know how far you are behind.

Chris Sampson’s journal round-up for 3rd October 2016

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.

Using discrete choice experiments with duration to model EQ-5D-5L health state preferences: testing experimental design strategies. Medical Decision Making [PubMedPublished 28th September 2016

DCEs are a bit in vogue for the purpose of health state valuation, so it was natural that EuroQol turned to it for valuation of the EQ-5D-5L. But previous valuation studies have highlighted challenges  associated with this approach, some of which this paper now investigates. Central to the use of DCE in this way is the inclusion of a duration attribute to facilitate anchoring from 1 to dead. This study looks at the effect of increasing the options when it comes to duration, as previous studies were limited in this regard. In this study, possible durations were 6 months or 1, 2, 4, 7 or 10 years. 802 online survey respondents we presented with 10 DCE choice sets, and the resulting model had generally logically ordered coefficients. So the approach looks feasible, but it isn’t clear whether or not there are any real advantages to including more durations. Another issue is that the efficiency of the DCE design might be improved by introducing prior information from previous studies to inform the selection of health profiles – that is, by introducing non-zero prior values. With 800 respondents, this design resulted in more disordering with – for example – a positive coefficient on level 2 for the pain/discomfort dimension. This was not the expected result. However, the design included a far greater proportion of more difficult choices, which the authors suggest may have resulted in inconsistencies. An alternative way of increasing efficiency might be to use a 2-stage approach, whereby health profiles are selected and then durations are selected based on information from previous studies. Using the same number of pairs but a sample half the size (400), the 2-stage design seemed to work a treat. It’s a promising design that will no doubt see further research in this context.

Is the distribution of care quality provided under pay-for-performance equitable? Evidence from the Advancing Quality programme in England. International Journal for Equity in Health [PubMedPublished 23rd September 2016

Suppose a regional health care quality improvement initiative worked, but only for the well-off. Would we still support it? Maybe not, so it’s important to uncover for whom the policy is working. QOF is the most-studied pay-for-performance programme in England and it does not seem to have reduced health inequalities in the context of primary care. There is less evidence regarding P4P in hospital care, which is where this study comes in by looking at the Advancing Quality initiative across five different health conditions. Using individual-level data for 73,002 people, the authors model the probability of receiving a quality indicator according to income deprivation in their local area. There were 23 indicators altogether, across which the results were not consistent. Poorer patients were more likely to receive pre-surgical interventions for hip and knee replacements and for coronary artery bypass grafting (CABG). And poorer people were less likely to receive advice at discharge. On the other hand, for hip and knee replacement and CABG, richer people were more likely to receive diagnostic tests. The main finding is that there is no obvious systematic pro-poor or pro-rich bias in the effects of this pay-for-performance initiative in secondary care. This may not be a big surprise due to the limited amount of self-selection and self-direction for patients in secondary care, compared with primary care.

The impact of social security income on cognitive function at older ages. American Journal of Health Economics [RePEc] Published 19th September 2016

Income correlates with health, as we know. But it’s useful to be more specific – as this article is – in order to inform policy. So does more social security income improve cognitive function at older ages? The short answer is yes. And that wasn’t a foregone conclusion as there is some evidence that higher income leads to earlier retirement, which in turn can be detrimental to cognitive function. In this study the authors use changes in the Social Security Act in the US in the 1970s. Between 1972 and 1977, Congress messed up a bit and temporarily introduced a policy that made payments increase at a rate faster than inflation, which was therefore enjoyed by people born between 1910 and 1916, with a 5 year gradual transition until 1922. Unsurprisingly, this study follows many others that have made the most of this policy quirk. Data are taken from a longitudinal survey of older people, which includes a set of scores relating to cognition, with a sample of 4139 people. Using an OLS model, the authors estimate the association between Social Security income and cognition. Cognition is measured using a previously developed composite score with 3 levels: ‘normal’, ‘cognitively impaired’ and ‘demented’. To handle the endogeneity of income, an instrumental variable is constructed on the basis of year of birth to tie-in with the peak in benefit from the policy (n=673). In today’s money the beneficiary cohort received around $2000 extra. It’s also good to see the analysis extended to a quantile regression to see whereabouts in the cognition score distribution effects accrue. The additional income resulted in improvements in working memory, knowledge, languages and orientation and overall cognition. The effects are strong and clinically meaningful. A $1000 (in 1993 prices) increase in annual income lead to a 1.9 percentage point reduction in the likelihood of being classified as cognitively impaired. The effect is strongest for those with higher levels of cognition. The key take-home message here is that even in older populations, policy changes can be beneficial to health. It’s never too late.

Credits