Alastair Canaway’s journal round-up for 28th August 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.

Valuing health-related quality of life: an EQ-5D-5L value set for England. Health Economics [PubMed] Published 22nd August 2017

With much anticipation, the new EQ-5D-5L value set was officially published. For over 18 months we’ve had access to values via the OHE’s discussion paper but the formal peer-reviewed paper has (I imagine) been in publication purgatory. This paper presents the results of the value-set for the new (ish) EQ-5D-5L measure. The study used the internationally agreed hybrid model combining TTO and DCE data to generate the values for the 3125 health states. It’s worth noting that the official values are marginally different to those in the discussion paper, although in practice this is likely to have little impact on results. Important results of the new value set include fewer health states worse than death (5.1% vs over 33%), and a higher minimum value (-0.285 vs -0.594). I’d always been a bit suspect of the values for worse than death states for the 3L measure, so this if anything is encouraging. This does, however, have important implications, primarily for interventions seeking to improve those in the worst health, where potential gains may be reduced. Many of us are actively using the EQ-5D-5L within trials and have been eagerly awaiting this value set. Perhaps naively, I always anticipated that with more levels and an improved algorithm it would naturally supersede the 3L and the outdated 3L value set upon publication. Unfortunately, to mark the release of the new value set, NICE released a ‘position statement’ [PDF] regarding the choice of measure and value sets for the NICE reference case. NICE specifies that i) the 5L value set is not recommended for use, ii) the EQ-5D-3L with the original UK TTO value set is recommended and if both measures are included then the 3L should be preferred, iii) if the 5L measure is included, then scores should be mapped to the EQ-5D-3L using the van Hout et al algorithm, iv) NICE supports the use of the EQ-5D-5L generally to collect data on quality of life, and v) NICE will review this decision in August 2018 in light of future evidence. So, unfortunately, for the next year at least, we will be either sticking to the original 3L measure or mapping from the 5L. I suspect NICE is buying some time as transitioning to the 5L is going to raise lots of interesting issues e.g. if a measure is cost-effective according to the 3L, but not the 5L, or vice-versa, and comparability of 5L results to old 3L results. Interesting times lie ahead. As a final note, it’s worth reading the OHE blog post outlining the position statement and OHE’s plans to satisfy NICE.

Long-term QALY-weights among spouses of dependent and independent midlife stroke survivors. Quality of Life Research [PubMed] Published 29th June 2017

For many years, spillover impacts were largely being ignored within economic evaluation. There is increased interest in capturing wider impacts, indeed, the NICE reference case recommends including carer impacts where relevant, whilst the US Panel on Cost-Effectiveness in Health and Medicine now advocates the inclusion of other affected parties. This study sought to examine whether the dependency of midlife stroke survivors impacted on their spouses’ HRQL as measured using the SF-6D. An OLS approach was used whilst controlling for covariates (age, sex and education, amongst others). Spouses of dependent stroke survivors had a lower utility (0.69) than those whose spouses were independent (0.77). This has interesting implications for economic evaluation. For example, if a treatment were to prevent dependence, then there could potentially be large QALY gains to spouses. Spillover impacts are clearly important. If we are to broaden the evaluative scope as suggested by NICE and the US Panel to include spillover impacts, then work is vital in terms of identifying relevant contexts, measuring spillover impacts, and understanding the implications of spillover impacts within economic evaluation. This remains an important area for future research.

Conducting a discrete choice experiment study following recommendations for good research practices: an application for eliciting patient preferences for diabetes treatments. Value in Health Published 7th August 2017

To finish this week’s round-up I thought it’d be helpful to signpost this article on conducting DCEs, which I feel may be helpful for researchers embarking on their first DCE. The article hasn’t done anything particularly radical or made ground-breaking discoveries. What it does however do is give you a practical guide to walk you through each step of the DCE process following the ISPOR guidelines/checklist. Furthermore, it expands upon the ISPOR checklist to provide researchers with a further resource to consider when conducting DCEs. The case study used relates to measuring patient preferences for type 2 diabetes mellitus medications. For every item on the ISPOR checklist, it explains how they made the choices that they did, and what influenced them. The paper goes through the entire process from identifying the research question all the way through to presenting results and discussion (for those interested in diabetes – it turns out people have a preference for immediate consequences and have a high discount rate for future benefits). For people who are keen to conduct a DCE and find a worked example easier to follow, this paper alongside the ISPOR guidelines is definitely one to add to your reference manager.

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Paul Mitchell’s journal round-up for 15th May 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.

Informal care: choice or constraint. Scandinavian Journal of Caring Sciences [PubMed] Published 12th April 2017

The provision of social care in the UK has become a major economic issue, with recent increases in government spending and local authority taxation to help ease the burden on both the health and social care system in the short term. This study examines some of the issues surrounding informal carers (i.e. care of a family member), estimated to be approximately 10% of the UK population. In particular, it focuses on the role of choice and constraints involved with the decision to become a carer. Using a cross-sectional survey for a UK city, choice of caring was explored in terms of responses to care provision provided, asking if it was a free choice initially to provide care, and if there were constraints in terms of duty, lack of others or financial resources for paid care. The analysis focused on how perceived choice in the caring role was associated with socio-demographics and the type of caring role performed, as well as the role of perceived choice in caring and their wellbeing. Out of the 798 respondents to all four questions on caring choice, about 1 in 3 reported an entirely free choice in the decision, with half reporting having a free choice but also a constraint in terms of duty, other available carers or financial resources. Less than 1 in 5 reported not having a free choice. Only carers with bad health or receiving state benefits had an association with a constrained caring role. The more intense the care role was also associated with a more constrained choice. Higher levels of choice were associated with higher levels of wellbeing across measures of happiness, life satisfaction and capability. In multivariable regression analysis, it was found that having a free choice in the initial caring decision resulted in a higher impact on life satisfaction than educational qualifications and home ownership, whilst improved capability of comparable levels to that of home ownership, all else being equal. The authors thus recommend enhanced choice as a way for policy to improve carers wellbeing. Although the authors acknowledge limitations with the study design being cross-sectional and geographically limited to one city, the study shows there is plenty of scope for understanding the determinants of informal caring and consequences for those carers in much greater detail in future national surveys to help address policy in this area in the medium to longer term.

Experienced utility or decision utility for QALY calculation? Both. Public Health Ethics [PhilPapersPublished 6th May 2017

How health states should be valued in population health metrics, like QALYs and DALYs, will not be an unfamiliar topic of discussion for regular readers of this blog. Instead of arguing for decision utility (i.e. accounting for general population preferences for avoiding health states) or experienced utility (i.e. accounting for patient experiences of health states), the authors in this paper argue for a combined approach, reviving a suggestion previously put forward by Lowenstein & Ubel. The authors neatly summarise some of the issues of relying on either decision utility or experienced utility approaches alone and instead argue for better informed decision utility exercises by using deliberative democracy methods where experienced utility in health states are also presented. Unfortunately, there is little detail of how this process might actually work in practice. There are likely to be issues of what patient experiences are presented in such an exercise and how other biases that may influence decision utility responses are controlled for in such an approach. Although I am generally in favour of more deliberative approaches to elicit informed values for resource allocation, I find that this paper makes a convincing case for neither of the utility approaches to valuation, rather than both.

The value of different aspects of person-centred care: a series of discrete choice experiments in people with long-term conditions. BMJ Open [PubMed] Published 26th April 2017

The term “person-centred care” is one which is gaining some prominence in how healthcare is provided. What it means, and how important different aspects of person-centred care are, is explored in this study using discrete choice experiments (DCEs). Through focus groups and drawing from the authors’ own experience in this area, four aspects of person-centred care for self-management of chronic conditions make up the attributes in the DCE across two levels: (i) information (same information for all/personalised information); (ii) situation (little account of current situation/suggestions that fit current situation); (iii) living well (everyone wants the same from life/works with patient for what they want from life); (iv) communication (neutral professional way/friendly professional way). A cost attribute was also attached to the DCE that was given to patient groups with chronic pain and chronic lung disease. The overall findings suggest that person-centred care focused on situation and living well were valued most with personal communication style valued the least. Latent class analysis also suggested that 1 in 5 of those sampled valued personalised information the most. Those with lower earnings were likely to look to reduce the cost attribute the most. The authors conclude that the focus on communication in current clinician training on person-centred care may not be what is of most value to patients. However, I am not entirely convinced by this argument, as it could be that communication was not seen as an issue by the respondents, perhaps somewhat influenced due to the skills clinicians already have obtained in this area. Clearly, these process aspects of care are difficult to develop attributes for in DCEs, and the authors acknowledge that the wording of the “neutral” and “high” levels may have biased responses. I also found that dropping the “negative” third level for each of the attributes unconvincing. It may have proved more difficult to complete than two levels, but it would have shown in much greater depth how much value is attached to the four attributes relative to one another.

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Paul Mitchell’s journal round-up for 2nd January 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.

Age effects in mortality risk valuation. European Journal of Health Economics [PubMed] [RePEcPublished 7th December 2016

Placing values on statistical life years has important public policy implications in measuring who benefits and how much they benefit from interventions. The authors of this study provide what they describe as the most comprehensive evidence to date against a constant value for a statistical life year, an assumption they argue is also applicable when calculating QALYs. Using a Spanish household survey collected over a large sample size (approximately 6,000 individuals), the authors study the relationship between willingness to pay (WTP) and age, by estimating individual WTP for reduction in risk of mortality due to acute myocardial infarction. Three different WTP elicitation procedures were performed. Parametric, semi-nonparametric and non-parametric models using marginal and total approaches were applied to understand the relationship using many alternative methods. Binary variables for income (proxied on a measure of self-perceived social status), education (>lower secondary level) and gender were also included as controls for the models. The results of the linear model show that WTP is lower as age increases. Those with higher income (i.e. social status) and education have higher WTP, while gender is not significant in any model. Sensitivity tests were as hypothesised. The non-parametric model produces similar results to the others, albeit with a higher senior discount. The senior discount is not independent of the income variable. From this, the authors estimate the value of a statistical life year for an 85 year old to be 3.5 times higher than that of a 20 year old. The authors are keen to highlight the strengths of their findings with a large sample size allowing for the robustness of results to be tested across a number of different model types. However, they do flag up the lack of comparability with previous studies that have focused on risk reductions with a lower probability of mortality. The assumption that the authors make that their findings for life years have direct applicability for QALYs is somewhat questionable, particularly for non-acute conditions and QALYs calculated for them. The rationale behind the three types of preference elicitation methods and how/why they were chosen is not apparent in the paper itself. The social status measure they use as a proxy for income is also questionable, and appeared to be applied to maximise sample size. If data for real income was used or imputation of income was included for missing data, it would be interesting to see what impact this may have had on their study findings.

Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques. European Journal of Health Economics [PubMedPublished 10th December 2016

Public involvement in health care is something that has become increasingly recognised as important to do and to be informed by public perspectives when making important decisions for their community. How and where that public involvement should feed into decision making is less well understood. In this study, the authors compare two methods, best worst scaling (BWS) case 2, and a new method the authors call ‘trio-wise’ where the choice task is presented in an equilateral triangle. Using ‘trio-wise’, respondents are able to click in any part of the triangle; this the authors argue gives additional insight on the strength of a respondent’s preferences and also accommodates indifferent preferences. Public preferences are sought using these two methods to understand what aspects of public involvement are most important. Eight general characteristics are included in the exercises. Respondents completed either BWS or the ‘trio-wise’ task (not both) using web based surveys. Approximately 1,700 individuals per arm were sampled. Only three of the eight general characteristics could be completed at any one time due to the trio-wise triangle approach. There was some evidence of position bias for both exercises. The authors say that weak preferences were observed using the trio-wise approach but this could be due to difficulty participants faced in choosing which generic characteristic was more important without further information. Impact and focus of public involvement are found to be the most important characteristics across both BWS and trio-wise. The authors find preference intensity has no bearing on choice probabilities, but this could be an artefact of the weak preferences observed in the sample. Although I can see the appeal of using the trio-wise approach when there are only three characteristics, BWS is advantageous in tasks with more characteristics. Indeed it feels that the findings from this experiment were impeded by the use of the trio-wise approach when much more useful information on guiding future public involvement practice could have been gathered using either BWS or a discrete choice experiment (DCE) across all eight characteristics and the options of public involvement within each characteristic.

How do individuals value health states? A qualitative investigation. Social Science & Medicine [PubMedPublished 22nd November 2016

The valuation tasks of health states used to generate QALYs have been previously found to be complex tasks for members of the general public to complete, who have little experience of such health states. This qualitative study seeks to gain a better understanding as to how the general public complete such tasks. Using a purposive sample, 21 individuals were asked to complete eight DCEs and three TTO tasks, based on the EQ-5D-5L valuation protocol. Participants were asked to complete the valuation tasks using think aloud, followed by semi-structured interviews. Three main themes emerged from the framework analysis undertaken on the interview transcripts. Firstly, individuals had to interpret a health state, using their imagination and experience to help visualise a realistic health state with those problems. Knowledge, understanding of descriptive system, additional information for a health state, re-writing of health states and problems with EQ-5D labels all impacted this process. The second theme was called conversion factors, which the authors took to mean in this context the personal and social factors that affected how participants valued health states. Personal interests, values and circumstances were said to have an effect on the interpretation of a health state. The final theme was based on the consequences of health states, that tended to focus on non-health effects caused by health problems, such as activities, enjoyment, independence, relationships, dignity and avoiding being a burden. The authors subsequently developed a three-stage explanatory account as to how people valued health states based on the interview findings. Although I would have some concerns about the generalisability of these findings to general public valuation studies, given the highly educated sample, it does highlight some issues about what health economists might implicitly think individuals are doing when completing such tasks compared to what they actually are doing. There are clearly problems for individuals completing such hypothetical health states, with the authors suggesting a more reflective and deliberative approach to overcome such problems. The authors also raise an interesting comment as to whether participants actually do weigh the consequences of health states and follow compensatory decision-making or instead are using simplifying heuristics based on one attribute, which I agree is an area that requires further investigation.

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