Alastair Canaway’s journal round-up for 29th January 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.

Is “end of life” a special case? Connecting Q with survey methods to measure societal support for views on the value of life-extending treatments. Health Economics [PubMed] Published 19th January 2018

Should end-of-life care be treated differently? A question often asked and previously discussed on this blog: findings to date are equivocal. This question is important given NICE’s End-of-Life Guidance for increased QALY thresholds for life-extending interventions, and additionally the Cancer Drugs Fund (CDF). This week’s round-up sees Helen Mason and colleagues attempt to inform the debate around societal support for views of end-of-life care, by trying to determine the degree of support for different views on the value of life-extending treatment. It’s always a treat to see papers grounded in qualitative research in the big health economics journals and this month saw the use of a particularly novel mixed methods approach adding a quantitative element to their previous qualitative findings. They combined the novel (but increasingly recognisable thanks to the Glasgow team) Q methodology with survey techniques to examine the relative strength of views on end-of-life care that they had formulated in a previous Q methodology study. Their previous research had found that there are three prevalent viewpoints on the value of life-extending treatment: 1. ‘a population perspective: value for money, no special cases’, 2. ‘life is precious: valuing life-extension and patient choice’, 3. ‘valuing wider benefits and opportunity cost: the quality of life and death’. This paper used a large Q-based survey design (n=4902) to identify societal support for the three different viewpoints. Viewpoints 1 and 2 were found to be dominant, whilst there was little support for viewpoint 3. The two supported viewpoints are not complimentary: they represent the ethical divide between the utilitarian with a fixed budget (view 1), and the perspective based on entitlement to healthcare (view 2: which implies an expanding healthcare budget in practice). I suspect most health economists will fall into camp number one. In terms of informing decision making, this is very helpful, yet unhelpful: there is no clear answer. It is, however, useful for decision makers in providing evidence to balance the oft-repeated ‘end of life is special’ argument based solely on conjecture, and not evidence (disclosure: I have almost certainly made this argument before). Neither of the dominant viewpoints supports NICE’s End of Life Guidance nor the CDF. Viewpoint 1 suggests end of life interventions should be treated the same as others, whilst viewpoint 2 suggests that treatments should be provided if the patient chooses them; it does not make end of life a special case as this viewpoint believes all treatments should be available if people wish to have them (and we should expand budgets accordingly). Should end of life care be treated differently? Well, it depends on who you ask.

A systematic review and meta-analysis of childhood health utilities. Medical Decision Making [PubMed] Published 7th October 2017

If you’re working on an economic evaluation of an intervention targeting children then you are going to be thankful for this paper. The purpose of the paper was to create a compendium of utility values for childhood conditions. A systematic review was conducted which identified a whopping 26,634 papers after deduplication – sincere sympathy to those who had to do the abstract screening. Following abstract screening, data were extracted for the remaining 272 papers. In total, 3,414 utility values were included when all subgroups were considered – this covered all ICD-10 chapters relevant to child health. When considering only the ‘main study’ samples, 1,191 utility values were recorded and these are helpfully separated by health condition, and methodological characteristics. In short, the authors have successfully built a vast catalogue of child utility values (and distributions) for use in future economic evaluations. They didn’t, however, stop there, they then built on the systematic review results by conducting a meta-analysis to i) estimate health utility decrements for each condition category compared to general population health, and ii) to examine how methodological factors impact child utility values. Interestingly for those conducting research in children, they found that parental proxy values were associated with an overestimation of values. There is a lot to unpack in this paper and a lot of appendices and supplementary materials are included (including the excel database for all 3,414 subsamples of health utilities). I’m sure this will be a valuable resource in future for health economic researchers working in the childhood context. As far as MSc dissertation projects go, this is a very impressive contribution.

Estimating a cost-effectiveness threshold for the Spanish NHS. Health Economics [PubMed] [RePEc] Published 28th December 2017

In the UK, the cost-per-QALY threshold is long-established, although whether it is the ‘correct’ value is fiercely debated. Likewise in Spain, there is a commonly cited threshold value of €30,000 per QALY with a dearth of empirical justification. This paper sought to identify a cost-per-QALY threshold for the Spanish National Health Service (SNHS) by estimating the marginal cost per QALY at which the SNHS currently operates on average. This was achieved by exploiting data on 17 regional health services between the years 2008-2012 when the health budget experienced considerable cuts due to the global economic crisis. This paper uses econometric models based on the provoking work by Claxton et al in the UK (see the full paper if you’re interested in the model specification) to achieve this. Variations between Spanish regions over time allowed the authors to estimate the impact of health spending on outcomes (measured as quality-adjusted life expectancy); this was then translated into a cost-per-QALY value for the SNHS. The headline figures derived from the analysis give a threshold between €22,000 and €25,000 per QALY. This is substantially below the commonly cited threshold of €30,000 per QALY. There are, however (as to be expected) various limitations acknowledged by the authors, which means we should not take this threshold as set in stone. However, unlike the status quo, there is empirical evidence backing this threshold and it should stimulate further research and discussion about whether such a change should be implemented.


Chris Sampson’s journal round-up for 8th January 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.

An empirical comparison of the measurement properties of the EQ-5D-5L, DEMQOL-U and DEMQOL-Proxy-U for older people in residential care. Quality of Life Research [PubMed] Published 5th January 2018

There is now a condition-specific preference-based measure of health-related quality of life that can be used for people with cognitive impairment: the DEMQOL-U. Beyond the challenge of appropriately defining quality of life in this context, cognitive impairment presents the additional difficulty that individuals may not be able to self-complete a questionnaire. There’s some good evidence that proxy responses can be valid and reliable for people with cognitive impairment. The purpose of this study is to try out the new(ish) EQ-5D-5L in the context of cognitive impairment in a residential setting. Data were taken from an observational study in 17 residential care facilities in Australia. A variety of outcome measures were collected including the EQ-5D-5L (proxy where necessary), a cognitive bolt-on item for the EQ-5D, the DEMQOL-U and the DEMQOL-Proxy-U (from a family member or friend), the Modified Barthel Index, the cognitive impairment Psychogeriatric Assessment Scale (PAS-Cog), and the neuropsychiatric inventory questionnaire (NPI-Q). The researchers tested the correlation, convergent validity, and known-group validity for the various measures. 143 participants self-completed the EQ-5D-5L and DEMQOL-U, while 387 responses were available for the proxy versions. People with a diagnosis of dementia reported higher utility values on the EQ-5D-5L and DEMQOL-U than people without a diagnosis. Correlations between the measures were weak to moderate. Some people reported full health on the EQ-5D-5L despite identifying some impairment on the DEMQOL-U, and some vice versa. The EQ-5D-5L was more strongly correlated with clinical outcome measures than were the DEMQOL-U or DEMQOL-Proxy-U, though the associations were generally weak. The relationship between cognitive impairment and self-completed EQ-5D-5L and DEMQOL-U utilities was not in the expected direction; people with greater cognitive impairment reported higher utility values. There was quite a lot of disagreement between utility values derived from the different measures, so the EQ-5D-5L and DEMQOL-U should not be seen as substitutes. An EQ-QALY is not a DEM-QALY. This is all quite perplexing when it comes to measuring health-related quality of life in people with cognitive impairment. What does it mean if a condition-specific measure does not correlate with the condition? It could be that for people with cognitive impairment the key determinant of their quality of life is only indirectly related to their impairment, and more dependent on their living conditions.

Resolving the “cost-effective but unaffordable” paradox: estimating the health opportunity costs of nonmarginal budget impacts. Value in Health Published 4th January 2018

Back in 2015 (as discussed on this blog), NICE started appraising drugs that were cost-effective but implied such high costs for the NHS that they seemed unaffordable. This forced a consideration of how budget impact should be handled in technology appraisal. But the matter is far from settled and different countries have adopted different approaches. The challenge is to accurately estimate the opportunity cost of an investment, which will depend on the budget impact. A fixed cost-effectiveness threshold isn’t much use. This study builds on York’s earlier work that estimated cost-effectiveness thresholds based on health opportunity costs in the NHS. The researchers attempt to identify cost-effectiveness thresholds that are in accordance with different non-marginal (i.e. large) budget impacts. The idea is that a larger budget impact should imply a lower (i.e. more difficult to satisfy) cost-effectiveness threshold. NHS expenditure data were combined with mortality rates for different disease categories by geographical area. When primary care trusts’ (PCTs) budget allocations change, they transition gradually. This means that – for a period of time – some trusts receive a larger budget than they are expected to need while others receive a smaller budget. The researchers identify these as over-target and under-target accordingly. The expenditure and outcome elasticities associated with changes in the budget are estimated for the different disease groups (defined by programme budgeting categories; PBCs). Expenditure elasticity refers to the change in PBC expenditure given a change in overall NHS expenditure. Outcome elasticity refers to the change in PBC mortality given a change in PBC expenditure. Two econometric approaches are used; an interaction term approach, whereby a subgroup interaction term is used with the expenditure and outcome variables, and a subsample estimation approach, whereby subgroups are analysed separately. Despite the limitations associated with a reduced sample size, the subsample estimation approach is preferred on theoretical grounds. Using this method, under-target PCTs face a cost-per-QALY of £12,047 and over-target PCTs face a cost-per-QALY of £13,464, reflecting diminishing marginal returns. The estimates are used as the basis for identifying a health production function that can approximate the association between budget changes and health opportunity costs. Going back to the motivating example of hepatitis C drugs, a £772 million budget impact would ‘cost’ 61,997 QALYs, rather than the 59,667 that we would expect without accounting for the budget impact. This means that the threshold should be lower (at £12,452 instead of £12,936) for a budget impact of this size. The authors discuss a variety of approaches for ‘smoothing’ the budget impact of such investments. Whether or not you believe the absolute size of the quoted numbers depends on whether you believe the stack of (necessary) assumptions used to reach them. But regardless of that, the authors present an interesting and novel approach to establishing an empirical basis for estimating health opportunity costs when budget impacts are large.

First do no harm – the impact of financial incentives on dental x-rays. Journal of Health Economics [RePEc] Published 30th December 2017

If dentists move from fee-for-service to a salary, or if patients move from co-payment to full exemption, does it influence the frequency of x-rays? That’s the question that the researchers are trying to answer in this study. It’s important because x-rays always present some level of (carcinogenic) risk to patients and should therefore only be used when the benefits are expected to exceed the harms. Financial incentives shouldn’t come into it. If they do, then some dentists aren’t playing by the rules. And that seems to be the case. The authors start out by establishing a theoretical framework for the interaction between patient and dentist, which incorporates the harmful nature of x-rays, dentist remuneration, the patient’s payment arrangements, and the characteristics of each party. This model is used in conjunction with data from NHS Scotland, with 1.3 million treatment claims from 200,000 patients and 3,000 dentists. In 19% of treatments, an x-ray occurs. Some dentists are salaried and some are not, while some people pay charges for treatment and some are exempt. A series of fixed effects models are used to take advantage of these differences in arrangements by modelling the extent to which switches (between arrangements, for patients or dentists) influence the probability of receiving an x-ray. The authors’ preferred model shows that both the dentist’s remuneration arrangement and the patient’s financial status influences the number of x-rays in the direction predicted by the model. That is, fee-for-service and charge exemption results in more x-rays. The combination of these two factors results in a 9.4 percentage point increase in the probability of an x-ray during treatment, relative to salaried dentists with non-exempt patients. While the results do show that financial incentives influence this treatment decision (when they shouldn’t), the authors aren’t able to link the behaviour to patient harm. So we don’t know what percentage of treatments involving x-rays would correspond to the decision rule of benefits exceeding harms. Nevertheless, this is an important piece of work for informing the definition of dentist reimbursement and patient payment mechanisms.


Alastair Canaway’s journal round-up for 10th 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.

Use-of-time and health-related quality of life in 10- to 13-year-old children: not all screen time or physical activity minutes are the same. Quality of life Research [PubMedPublished 3rd July 2017

“If you watch too much TV, it’ll make your eyes square” – something I heard a lot as a child. This first paper explores whether this is true (sort of) by examining associations between aspects of time use and HRQL in children aged 10-13 (disclaimer: I peer reviewed it and was pleased to see them incorporate my views). This paper aims to examine how different types of time use are linked to HRQL. Time use was examined by the Multimedia Activity Recall for Children and Adolescents (MARCA) which separates out time into physical activity (sport, active transport, and play), screen time (TV, videogames, computer use), and sleep. The PedsQL was used to assess HRQL, whilst dual x-ray absorptiometry was used to accurately assess fatness. There were a couple of novel aspects to this study, first, the use of absorptiometry to accurately measure body fat percentage rather than the problematic BMI/skin folds in children; second, separating time out into specific components rather than just treating physical activity or screen time as homogeneous components. The primary findings were that for both genders, fatness (negative), sport (positive) and development stage (negative) were associated with HRQL. For boys, the most important other predictor of HRQL was videogames (negative) whilst predictors for girls included television (negative), active transport (negative) and household income (positive). With the exception of ‘active travel’ for girls, I don’t think any of these findings are particularly surprising. As with all cross-sectional studies of this nature, the authors give caution to the results: inability to demonstrate causality. Despite this, it opens the door for various possibilities for future research, and ideas for shaping future interventions in children this age.

Raise the bar, not the threshold value: meeting patient preferences for palliative and end-of-life care. PharmacoEconomics – Open Published 27th June 2017

Health care ≠ end of life care. Whilst health care seeks to maximise health, can the same be said for end of life care? Probably not. This June saw an editorial elaborating on this issue. Health is an important facet of end of life care. However, there are other substantial objects of value in this context e.g. preferences for place of care, preparedness, reducing family burdens etc. Evidence suggests that people at end of life can value these ‘other’ objects more than health status or life extension. Thus there is value beyond that captured by health. This is an issue for the QALY framework where health and length of life are the sole indicators of benefit. The editorial highlights that this is not people wishing for higher cost-per-QALY thresholds at end of life, instead, it is supporting the valuation of key elements of palliative care within the end of life context. It argues that palliative care interventions often are not amenable to integration with survival time in a QALY framework, this effectively implies that end of life care interventions should be evaluated in a separate framework to health care interventions altogether. The editorial discusses the ICECAP-Supportive Care Measure (designed for economic evaluation of end of life measures) as progress within this research context. An issue with this approach is that it doesn’t address allocative efficiency issues (and comparability) with ‘normal’ health care interventions. However, if end of life care is evaluated separately to regular healthcare, it will lead to better decisions within the EoL context. There is merit to this justification, after all, end of life care is often funded via third parties and arguments could, therefore, be made for adopting a separate framework. This, however, is a contentious area with lots of ongoing interest. For balance, it’s probably worth pointing out Chris’s (he did not ask me to put this in!) book chapter which debates many of these issues, specifically in relation to defining objects of value at end of life and whether the QALY should be altogether abandoned at EoL.

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis. European Journal of Health Economics [PubMedPublished 24th June 2017

Payment systems that incentivise cost control and quality improvements are increasingly used. In England, until recently, mental health services have been funded via block contracts that do not necessarily incentivise cost control and payment has not been linked to outcomes. The National Tariff Payment System for reimbursement has now been introduced to mental health care. This paper harnesses the MHMDS (now called MHSDS) using multi-level bivariate regression to investigate whether it is possible to control costs without negatively affecting outcomes. It does this by examining the relationship between costs and outcomes for mental health providers. Due to the nature of the data, an appropriate instrumental variable was not available, and so it is important to note that the results do not imply causality. The primary results found that after controlling for key variables (demographics, need, social and treatment) there was a minuscule negative correlation between residual costs and outcomes with little evidence of a meaningful relationship. That is, the data suggest that outcome improvements could be made without incurring a lot more cost. This implies that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment systems. Something to bear in mind when interpreting the results is that there was a rather large list of limitations associated with the analysis, most notably that the analysis was conducted at a provider level. Although it’s continually improving, there still remain issues with the MHMDS data: poor diagnosis coding, missing outcome data, and poor quality of cost data. As somebody who is yet to use MHMDS data, but plans to in the future, this was a useful paper for generating ideas regarding what is possible and the associated limitations.