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.

Credits

Paul Mitchell’s journal round-up for 25th December 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.

Consensus-based cross-European recommendations for the identification, measurement and valuation of costs in health economic evaluations: a European Delphi study. European Journal of Health Economics [PubMedPublished 19th December 2017

The primary aim of this study was to develop guidelines for costing in economic evaluation studies conducted across more than one European country. The starting point of the societal perspective as the benchmark for costing was not entirely obvious from the abstract, where this broadest approach to costing is not recommended uniformly across all European countries. Recommendations following this starting point looked at the identification, measurement and valuation of resource use, discount rate and discounting of future costs. A three-step Delphi study was used to gain consensus on what should be included in an economic evaluation from a societal perspective, based initially on findings from a review of costing methodologies adopted across European country-specific guidelines. Consensus required at least two thirds (67%) agreement across those participating in the Delphi study at all 3 stages. Where no agreement was reached after the three stages, a panel of four of the co-authors made a final decision on what should be recommended. In total, 26 of the 110 invited to participate completed at least one Delphi round, with all Delphi rounds having at least 16 participants. It remains unclear to me if 16 for a Delphi round is sufficient to reach a European wide consensus on costing methodologies. There were a number of key areas where no consensus was reached (e.g. including costs unrelated to the intervention, measurement of resource use and absenteeism, and valuation of opportunity costs of patient time and informal care), so the four-strong author panel had a leading role on some of the main recommendations. Notwithstanding the limitations associated with the reference perspective taken and sample for the Delphi study and panel, the paper provides a useful illustration of the different approaches to costing across European countries. It also provides a good coverage of costing issues that need to be explained in detail in economic evaluations to allow for clear understanding of methods used and the underpinning rationale for those decisions where a choice is required on the costing methodology applied.

A (five-)level playing field for mental health conditions?: exploratory analysis of EQ-5D-5L derived utility values. Quality of Life Research [PubMedPublished 16th December 2017

The UK health economics community has been reeling from the decision made earlier this year by UK guidelines developer, the National Institute for Health and Care Excellence (NICE), who recommended to not adopt the new population values developed for the EQ-5D-5L version when calculating QALYs and instead rely on a crosswalk of the values developed over 20 years ago for the 3 level EQ-5D version. This paper provides a timely comparison of how these two value sets perform for the EQ-5D-5L descriptive system in patient groups with mental health conditions, groups often thought to be disadvantaged by the physical health functioning focus of the EQ-5D descriptive system. Using baseline data from three trials, the authors find that the new utility values produce a higher mean EQ-5D score of 0.08 compared to the old crosswalk values, with a 0.225 difference for those reporting extreme problems with the anxiety/depression dimension on EQ-5D. Although, the authors of this study highlight using these new values would increase cost per QALY results in this sample using scenario analysis, when improvements are in the depression/anxiety category only, such improvements are relatively better than across the whole EQ-5D-5L descriptive system due to the relative additional value placed on the anxiety/depression dimension in the new values. This paper makes for interesting reading and one that NICE should take into consideration when reviewing their decision on this issue next year. Although I would disagree with the authors when they state that this study would be a primary reason for revising the NICE cost-effectiveness threshold (more compelling arguments for this elsewhere in my view), it does clearly highlight the influence of the choice of descriptive system and the values used in the outcomes produced for economic analysis such as QALYs, even when the two descriptive systems in question (EQ-5D-3L and EQ-5D-5L) are roughly the same.

What characteristics of nursing homes are most valued by customers? A discrete choice experiment with residents and family members. Value in Health Published 1st December 2017

Our final paper for review in 2017 looks at the characteristics that are of most importance to individuals and their family members when it comes to nursing home provision. The authors conducted a valuation exercise using a discrete choice experiment (DCE) to calculate the relative importance of the attributes contained on the Consumer Choice Index-Six Dimension (CCI-6D), a measure developed to assess the quality of nursing home care across 3 levels on six domains: 1. level of time care staff spent with residents; 2. homeliness of shared spaces; 3. homeliness of room setup; 4. access to outside and garden; 5. frequency of meaningful activities; and 6. flexibility with care routines. Those who lived in a nursing home for at least a year with low levels of cognitive impairment completed the DCE themselves, whereas family members were asked to proxy for their close relative with more severe cognitive impairment. 126 residents and 416 family member proxies completed the DCE comparisons of nursing homes with different qualities in these six areas. The results of the DCE show differences in preferences across the two groups. Although similar importance is placed on some dimensions across both groups (i.e. “homeliness of room set up” ranked highly, whereas “frequency of meaningful activities” ranked lower), residents value access to outside and garden four times as much as the family proxies do (second most important dimension for residents, lowest for family proxies), family members value level of time care staff spent with residents twice as much as residents themselves (most important attribute for family proxies, third most important for residents). Although residents in both groups may have important differences in characteristics that might explain some of this difference, it is probably a good time of year to remember family preferences may be inconsistent with individuals within them, so make sure to take account of this variation when preparing those Christmas dinners.

Happy holidays all.

Credits

Meeting round-up: 7th Meeting of the International Academy of Health Preference Research

The 7th meeting of the International Academy of Health Preference Research (IAHPR) took place in Glasgow on Saturday 4th November 2017. The meeting was chaired by Karin Groothuis-Oudshoorn and Terry Flynn. It was preceded by a Friday afternoon symposium on the econometrics of heterogeneity, which I was unable to attend.

IAHPR is a relatively new organisation, describing itself as an ‘international network of multilingual, multidisciplinary researchers who contribute to the field of health preference research’. To minimise participants’ travel costs, IAHPR meetings are usually scheduled alongside major international conferences such as the meetings of iHEA, EuHEA and AHES (the Australian Health Economics Society). The November meeting took place just before the kick-off of the ISPOR European Congress (a behemoth by comparison). Most, but not all, of the attendees I spoke to, said that they would also be attending the ISPOR Congress.

The meeting was attended by 49 researchers from nine different countries. Nine were from the US, 16 from the UK, and 22 from elsewhere in the EU (sadly, I won’t be able to use the phrase ‘elsewhere in the EU’ for much longer). Understandably, the regional representation of the Glasgow meeting was quite different from that of the (July 2017) Boston meeting, where over 60% of the participants were based in the US.

All1

In total there were 12 podium presentations (half by student presenters) and about eight posters. Each podium presenter was allocated 12 minutes for their presentation and a further eight minutes for questions and group discussion. The poster authors were given the opportunity to briefly introduce themselves and their research to the group as part of an ‘elevator talks’ session.

Although all of the presentations focused on issues in stated preference research, the range of topics was quite broad, covering preferences between health outcomes, preferences between health services, conceptual and theoretical issues, experimental design approaches, and novel analytical techniques. Most of the studies presented applications of the DCE and best-worst scaling methods. Several presentations examined issues relating to preference heterogeneity and decision heuristics.

A personal highlight was Tabea Schmidt-Ott’s examination of the use of dominance tests to assess rational choice behaviour amongst survey respondents. She reported that such tests were included in a quarter of the health-related DCE studies published in 2015 (including many studies that had been led by IAHPR meeting attendees). Their inclusion had often been used to justify choices about which respondents to exclude from the final samples. Tabea concluded that dominance tests are a weak technique for assessing the rationality of people’s choice behaviour, as the observation of dominated choices can be explained by and accounted for in DCE models.

Overall, the IAHPR meeting was enjoyable and intellectually stimulating. The standard of the presentations and discussions was high, and it was a good forum for learning about the latest advances in stated preference research. It was quite DCE-dominated, so it would have been interesting to have had some representation from researchers who are sceptical about that methodology.

The next meeting will take place in Tasmania, to be chaired by Brendan Mulhern and Richard Norman.

Credits