36th EuroQol Plenary Meeting

The 36th EuroQol Plenary Meeting will be held on 18-21 September 2019 in Brussels, Belgium.

  • 10 April 2019: Deadline submitting abstracts
  • 11 April – 21 April 2019: Review and selection of abstracts
  • 29 April 2019: Abstract acceptance notification
  • 12 June 2019: Deadline submitting papers and posters
  • 13 June – 26 June 2019: Review of submitted papers and posters
  • 8 July 2019: Papers and posters published on EuroQol members’ website

Brendan Collins’s journal round-up for 14th January 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.

Income distribution and health: can polarization explain health outcomes better than inequality? The European Journal of Health Economics [PubMed] Published 4th December 2018

One of my main interests is health inequalities. I thought polarisation was intuitive; I had seen it in the context of the UK and the US employment market; an increase in poorly-paid ‘McJobs’ and an increase in well-paid ‘MacJobs’, with fewer jobs in the middle. But I hadn’t seen polarisation measured in a statistical way.

Traditional measures of population inequalities like Gini or Atkinson index measure the share of income or the ratio of richest to poorest. But polarisation goes a step further and looks whether there are discrete clusters or groups who have similar incomes. The theory goes that having discrete groups increases social alienation, conflict and socioeconomic comparison and increases health inequalities. Now, I get how you can test statistically for discrete income clusters, and there is an evidence base for the relationship between polarisation and social tension. But groups will cluster based on other factors besides income. I feel like it may be taking a leap to assume a statistical finding (income polarisation) will always represent a sociological construct (alienation) but I confess I don’t know the literature behind this.

China is a country with an increasing degree of polarisation as measured by the Duclos, Esteban and Ray (DER) polarisation indices, and this study suggests that it is related to health status. This study looked at trends in BMI and systolic blood pressure from 1991 to 2011 and found both to increase with increased polarisation. I imagine a lot of other social change went on in this time period in China. I think BMI might not be a good candidate for measuring the effect of polarisation, as being poor is associated with malnourishment and low weight as well as obesity. The authors found that social capital (based on increasing family size, community size, and living in the same community for a long time) had a protective effect against the effects of polarisation on health. Whether this study provides more evidence for the socioeconomic comparison or status anxiety theories of health inequalities, I am not sure; it could equally provide evidence for the neo-materialist (i.e. simply not having enough resources for a healthy life) theories – the relative importance will likely differ by country anyway.

Maybe we don’t need to add more measures of inequality to the mix but I am intrigued. I am just starting my journey with polarisation but I think it has promise.

Two-year evaluation of mandatory bundled payments for joint replacement. The New England Journal of Medicine [PubMed] Published 2nd January 2019

Joint replacements are a big cost to western healthcare systems and often delayed or rationed (partly because replacement joints may only have a 10-20 year lifespan on average). In the UK, for instance, joint replacements have been rationed based on factors like BMI or pain levels (in my opinion, often in an arbitrary way to save money).

This paper found that having a bundled payments and penalties model (Comprehensive Care for Joint Replacement; CJR) for optimal care around hip and knee replacements reduced Medicare spending per episode compared to areas that did not pilot the programme. The overall difference was small in absolute terms at $812 against a total cost of around $24,000 per episode. The programme involves the hospital meeting a set of performance measures, and if they can do so at a lower cost, any savings are shared between the hospital and the payer. Cost savings were mainly driven by a reduction in patients being discharged to post-acute care facilities. Rates of complex patients were similar between pilot and control areas – this is important because a lower rate of complex cases in the CJR trial areas might indicate hospitals ‘cherry picking’ easier to treat, less expensive cases. Also, rates of complications were not significantly different between the CJR pilot areas and controls.
This paper suggests that having this kind of bundled payment programme can save money while maintaining quality.

Association of the Hospital Readmissions Reduction Program with mortality among Medicare beneficiaries hospitalized for heart failure, acute myocardial infarction, and pneumonia. JAMA [PubMed] Published 25th December 2018

Nobody likes being in hospital. But sometimes hospitals are the best places for people. This paper looks at possible unintended consequences of a US programme; the Hospital Readmissions Reduction Program (HRRP) where the Centers for Medicare & Medicaid Services (CMS) impose financial penalties (almost $2billion dollars’ worth since 2012) on hospitals with elevated 30-day readmission rates for patients with heart failure, acute myocardial infarction, and pneumonia. This study compared four time periods (no control group) and found that, after the programme was implemented, death rates for people who had been admitted with pneumonia and heart failure increased, with these increased deaths occurring more in people who had not been readmitted to hospital. The analysis controlled for differences in demographics, comorbidities, and calendar month using propensity scores and inverse probability weighting.

The authors are clear that their results do not establish cause and effect but are concerning nonetheless and worthy of more analysis. Incidentally, there is another paper this week in Health Affairs which suggests that the benefits of the programme in reducing readmissions was overstated.

There has been a similar financial incentive in the English NHS where hospitals are subject to the 30-day readmission rule, meaning they are not paid for people who are readmitted as an emergency within 30 days of being discharged. This is shortly to be abolished for 2019/20. I wonder if there has been similar research on whether this also led to unintended consequences in the NHS. Maybe there is a general lesson here about thinking a bit deeper about the potential outcomes of incentives in healthcare markets?

In these last two papers, we have had two examples of financial incentive programmes from Medicare. The CJR, which seems to have worked, has been dampened down from a mandatory to a voluntary programme, while the HRRP, which may not have worked, has been extended.

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Chris Sampson’s journal round-up for 7th January 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.

Overview, update, and lessons learned from the international EQ-5D-5L valuation work: version 2 of the EQ-5D-5L valuation protocol. Value in Health Published 2nd January 2019

Insofar as there is any drama in health economics, the fallout from the EQ-5D-5L value set for England was pretty dramatic. If you ask me, the criticisms are entirely ill-conceived. Regardless of that, one of the main sticking points was that the version of the EQ-5D-5L valuation protocol that was used was flawed. England was one of the first countries to get a valuation, so it used version 1.0 of the EuroQol Valuation Technique (EQ-VT). We’re now up to version 2.1. This article outlines the issues that arose in using the first version, what EuroQol did to try and solve them, and describes the current challenges in valuation.

EQ-VT 1.0 includes the composite time trade-off (cTTO) task to elicit values for health states better and worse than dead. Early valuation studies showed some unusual patterns. Research into the causes of this showed that in many cases there was very little time spent on the task. Some interviewers had a tendency to skip parts of the explanation for completing the worse-than-dead bit of the cTTO, resulting in no values worse than dead. EQ-VT 1.1 added three practise valuations along with greater monitoring of interviewer performance and a quality control procedure. This dramatically reduced interviewer effects and the likelihood of inconsistent responses. Yet further improvements could be envisioned. And so EQ-VT 2.0 added a feedback module. The feedback module shows respondents the ranking of states implied by their valuations, with which respondents can then agree or disagree. 2.0 was tested against 1.1 and showed further reductions in inconsistencies thanks to the feedback module. Other modifications were not supported by the evaluation. EQ-VT 2.1 added a dynamic question to further improve the warm-up tasks.

There are ongoing challenges with the cTTO, mostly to do with how to model the data. The authors provide a table setting out causes, consequences, and possible solutions for various issues that might arise in the modelling of cTTO data. And then there’s the discrete choice experiment (DCE), which is included in addition to the cTTO, but which different valuation studies used (or did not use) differently in modelling values. Research is ongoing that will probably lead to developments beyond EQ-VT 2.1. This might involve abandoning the cTTO altogether. Or, at least, there might be a reduction in cTTO tasks and a greater reliance on DCE. But more research is needed before duration can be adequately incorporated into DCEs.

Helpfully, the paper includes a table with a list of countries and specification of the EQ-VT versions used. This demonstrates the vast amount of knowledge that has been accrued about EQ-5D-5L valuation and the lack of wisdom in continuing to support the (relatively under-interrogated) EQ-5D-3L MVH valuation.

Do time trade-off values fully capture attitudes that are relevant to health-related choices? The European Journal of Health Economics [PubMed] Published 31st December 2018

Different people have different preferences, so values for health states elicited using TTO should vary from person to person. This study is concerned with how personal circumstances and beliefs influence TTO values and whether TTO entirely captures the impact of these on preferences for health states.

The authors analysed data from an online survey with a UK-representative sample of 1,339. Participants were asked about their attitudes towards quality and quantity of life, before completing some TTO tasks based on the EQ-5D-5L. Based on their response, they were shown two ‘lives’ that – given their TTO response – they should have considered to be of equivalent value. The researchers constructed generalised estimating equations to model the TTO values and logit models for the subsequent choices between states. Age, marital status, education, and attitudes towards trading quality and quantity of life all determined TTO values in addition to the state that was being valued. In the modelling of the decisions about the two lives, attitudes influenced decisions through the difference between the two lives in the number of life years available. That is, an interaction term between the attitudes variable and years variables showed that people who prefer quantity of life over quality of life were more likely to choose the state with a greater number of years.

The authors’ interpretation from this is that TTO reflects people’s attitudes towards quality and quantity of life, but only partially. My interpretation would be that the TTO exercise would have benefitted from the kind of refinement described above. The choice between the two lives is similar to the feedback module of the EQ-VT 2.0. People often do not understand the implications of their TTO valuations. The study could also be interpreted as supportive of ‘head-to-head’ choice methods (such as DCE) rather than making choices involving full health and death. But the design of the TTO task used in this study was quite dissimilar to others, which makes it difficult to say anything generally about TTO as a valuation method.

Exploring the item sets of the Recovering Quality of Life (ReQoL) measures using factor analysis. Quality of Life Research [PubMed] Published 21st December 2018

The ReQoL is a patient-reported outcome measure for use with people experiencing mental health difficulties. The ReQoL-10 and ReQoL-20 both ask questions relating to seven domains: six mental, one physical. There’s been a steady stream of ReQoL research published in recent years and the measures have been shown to have acceptable psychometric properties. This study concerns the factorial structure of the ReQoL item sets, testing internal construct validity and informing scoring procedures. There’s also a more general methodological contribution relating to the use of positive and negative factors in mental health outcome questionnaires.

At the outset of this study, the ReQoL was based on 61 items. These were reduced to 40 on the basis of qualitative and quantitative analysis reported in other papers. This paper reports on two studies – the first group (n=2,262) completed the 61 items and the second group (n=4,266) completed 40 items. Confirmatory factor analysis and exploratory factor analysis were conducted. Six-factor (according to ReQoL domains), two-factor (negative/positive) and bi-factor (global/negative/positive) models were tested. In the second study, participants were either presented with a version that jumbled up the positively and negatively worded questions or a version that showed a block of negatives followed by a block of positives. The idea here is that if a two-factor structure is simply a product of the presentation of questions, it should be more pronounced in the jumbled version.

The results were much the same from the two study samples. The bi-factor model demonstrated acceptable fit, with much higher factor loadings on the general quality of life factor that loaded on all items. The results indicated sufficient unidimensionality to go ahead with reducing the number of items and the two ordering formats didn’t differ, suggesting that the negative and positive loadings weren’t just an artefact of the presentation. The findings show that the six dimensions of the ReQoL don’t stand as separate factors. The justification for maintaining items from each of the six dimensions, therefore, seems to be a qualitative one.

Some outcome measurement developers have argued that items should all be phrased in the same direction – as either positive or negative – to obtain high-quality data. But there’s good reason to think that features of mental health can’t reliably be translated from negative to positive, and this study supports the inclusion (and intermingling) of both within a measure.

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