Reporting Quality of Marginal Rates of Substitution in Discrete Choice Experiments That Elicit Patient Preferences.

BACKGROUND: Discrete choice experiments (DCEs) are commonly used to elicit patient preferences as marginal rates of substitution (MRSs) between treatment or health service attributes. Because these studies are increasing in importance, it is vital that uncertainty around MRS estimates is reported. OBJECTIVE: To review recently published DCE studies that elicit patient preferences in relation to MRS reporting and to explore the accuracy of using other reported information to estimate the uncertainty of the MRSs. METHODS: A systematic literature review of DCEs conducted with patients between 2014 and July 2019 was performed. The number of studies reporting coefficients, MRSs, standard errors (SEs), and confidence intervals was recorded. If all information was reported, studies were included in an analysis to determine the impact of estimating the SEs of MRSs using coefficients and assuming zero covariance, to determine the impact of this assumption. RESULTS: Two hundred and thirty-two patient DCEs were identified in the review; 34.1% (n = 79) reported 1 or more MRS and, of these, only 62.0% (n = 49) provided an estimate of the uncertainty. Of these studies, 16 contained enough information for inclusion in the analysis, providing 116 datapoints. Actual SEs were smaller than estimated SEs in 75.0% of cases (n = 87), and estimated SEs were within 25% of the actual SE in 59.5% of cases (n = 69). CONCLUSION: Uncertainty of MRS estimates is unreported in a substantial proportion of recently published DCE studies. Estimating the SE of a MRS by solely using the SEs of the utility coefficients is likely to lead to biased estimates of the precision of patient trade-offs.

Do preferences differ based on respondent experience of a health issue and its treatment? A case study using a public health intervention.

OBJECTIVES: Preference information is increasingly being elicited to support decision-making. Although discrete choice experiments (DCEs) are commonly used, little is known about how respondents' relative experience of a health issue, and its treatment, might impact the results of preference studies. The aim of this study was to explore how preferences differ between groups of individuals with varying levels of experience of a health issue and its treatment, using a weight loss maintenance (WLM) programme as a case study. METHODS: An online DCE survey was provided to four groups, each differing in their level of experience with weight loss and WLM programmes. One group was recruited from a randomised controlled trial of a WLM programme (ISRCTN14657176) and the other three from an online panel. Choice data were analysed using mixed logit models. Relative attribute importance scores and willingness-to-pay (WTP) estimates were estimated to enable comparisons between groups. RESULTS: Preferences differed between the groups across different attributes. The largest differences related to the outcome (weight re-gain) and cost attributes, resulting in WTP estimates that were statistically significantly different. The most experienced group was willing to pay £0.35 (95% CI: £0.28, £0.42) to avoid a percentage point increase in weight re-gain, compared with £0.12 (95% CI: £0.08, £0.16) for the least experienced group. CONCLUSION: This study provides evidence in a public health setting to suggest that preferences differ based on respondent experience of the health issue and its treatment. Health preference researchers should therefore carefully consider the appropriate composition of their study samples.

Modelling Spillover Effects on Informal Carers: The Carer QALY Trap.

The provision of informal (unpaid) care can impose significant 'spillover effects' on carers, and accounting for these effects is consistent with the efficiency and equity objectives of health technology assessment (HTA). Inclusion of these effects in health economic models, particularly carer health-related quality of life (QOL), can have a substantial impact on net quality-adjusted life year (QALY) gains and the relative cost effectiveness of new technologies. Typically, consideration of spillover effects improves the value of a technology, but in some circumstances, consideration of spillover effects can lead to situations whereby life-extending treatments for patients may be considered cost ineffective due to their impact on carer QOL. In this piece we revisit the classic 'QALY trap' and introduce an analogous 'carer QALY trap' which may have practical implications for economic evaluations where the inclusion of carer QOL reduces incremental QALY gains. Such results may align with a strict QALY-maximisation rule, however we consider the extent to which this principle may be at odds with the preferences of carers themselves (and possibly society more broadly), potentially leading decision makers into the carer QALY trap as a result. We subsequently reflect on potential solutions, highlighting the important (albeit limited) role that deliberation has to play in HTA.

Analytical Considerations When Anchoring Discrete Choice Experiment Values Using Composite Time Trade-Off Data: The Case of EQ-5D-Y-3L.

Discrete choice experiments (DCEs) are becoming increasingly used to elicit preferences for children's health states. However, DCE data need to be anchored to produce value sets, and composite time trade-off (cTTO) data are typically used in the context of EQ-5D-Y-3L valuation. The objective of this paper is to compare different anchoring methods, summarise the characteristics of the value sets they produce, and outline key considerations for analysts. Three anchoring methods were compared using data from published studies: (1) rescaling using the mean value for the worst health state; (2) linear mapping; and (3) hybrid modelling. The worst state rescaling value set had the largest range. The worst state rescaling and linear mapping value sets preserved the relative importance of the dimensions from the DCE, whereas the hybrid model value set did not. Overall, the predicted values from the hybrid model value set were more closely aligned with the cTTO values. These findings are relatively generalisable. Deciding upon which anchoring approach to use is challenging, as there are numerous considerations. Where cTTO data are collected for more than one health state, anchoring on the worst health state will arguably be suboptimal. However, the final choice of approach may require value judgements to be made. Researchers should seek input from relevant stakeholders when commencing valuation studies to help guide decisions and should clearly set out their rationale for their preferred anchoring approach in study outputs.

Impact of Including Carer Information in Time Trade-Off Tasks: Results from a Pilot Study.

INTRODUCTION: Carer quality of life (QoL) can be included in economic evaluations and captured using EQ-5D. Traditional valuation tasks require participants to imagine living in a health state for a number of years, without being told what to consider. This pilot study sought to investigate whether participants implicitly consider the impact of the health state on others, and the extent to which this may impact health state valuations. METHODS: Composite time trade-off (TTO) interviews were conducted with a convenience sample. Each interview included a 'traditional' TTO exercise to value three health states, and a 'combined' TTO exercise, where participants valued the same health states again, having been informed that they would require a carer living in a particular health state. Qualitative feedback was collected after each exercise. Paired t-test comparisons of the utilities elicited in each exercise were made. RESULTS: Thirty-three participants enrolled in the pilot. Mean differences between exercises were not statistically significant and differed in direction, although considerable heterogeneity was observed in individual response trajectories. Overall, 36% (n = 12) of participants expressed an unprompted concern about being a burden on others in the traditional exercise, and 67% (n = 22) of participants would have responded differently had the carer been in full health in the combined exercise. CONCLUSION: Providing contextual information about carers may impact valuations. Further research is required to better understand the reasons behind the variation in individual response trajectories observed in this pilot study. The insights from this study may be useful for informing the design of related future studies.

Valuing EQ-5D-Y-3L Health States Using a Discrete Choice Experiment: Do Adult and Adolescent Preferences Differ?

BACKGROUND: An important question in the valuation of children's health is whether the preferences of younger individuals should be captured within value sets for measures that are aimed at them. This depends on whether younger individuals can complete valuation exercises and whether their preferences differ from those of adults. This study compared the preferences of adults and adolescents for EQ-5D-Y-3L health states using latent scale values elicited from a discrete choice experiment (DCE). METHODS: An online DCE survey, comprising 15 pairwise choices, was provided to samples of UK adults and adolescents (aged 11-17 y). Adults considered the health of a 10-year-old child, whereas adolescents considered their own health. Mixed logit models were estimated, and comparisons were made using relative attribute importance (RAI) scores and a pooled model. RESULTS: In total, 1000 adults and 1005 adolescents completed the survey. For both samples, level 3 in pain/discomfort was most important, and level 2 in self-care the least important, based on the relative magnitudes of coefficients. The RAI scores (normalized on self-care) indicated that adolescents gave less weight relative to adults to usual activities (1.18 v. 1.51; P < 0.05), pain/discomfort (1.77 v. 3.12; P < 0.01), and anxiety/depression (1.64 vs. 2.65; P < 0.01). The pooled model indicated evidence of differences between the two samples in both levels in pain/discomfort and anxiety/depression. LIMITATIONS: The perspective of the DCE task differed between the 2 samples, and no data were collected to anchor the DCE data to generate value sets. CONCLUSIONS: Adolescents could complete the DCE, and their preferences differed from those of adults taking a child perspective. It is important to consider whether their preferences should be incorporated into value sets.

A Multinational European Study of Patient Preferences for Novel Diagnostics to Manage Antimicrobial Resistance.

BACKGROUND: Novel diagnostics are needed to manage antimicrobial resistance (AMR). Patient preferences are important in determining whether diagnostic tests are successful in practice, but there are few data describing the test attributes which matter most to patients. We elicited patients' preferences for attributes of diagnostic tests that could be used to reduce unnecessary antibiotic use in primary care across seven European countries. METHODS: We used an online stated preference survey, including a discrete choice experiment (DCE). The DCE explored how patients make trade-offs between three key attributes of diagnostic tests: the speed that results were available, confidence in the test results, and how convenient it is to take the test. Individuals were eligible to complete the survey if they had taken antibiotics within the last 2 years and were resident in Germany, Italy, Spain, France, Greece, the Netherlands or the United Kingdom (UK). RESULTS: In total, 988 respondents completed the survey. The DCE responses illustrated that speed was the least important attribute in most countries. Responses from Germany and the Netherlands indicated that confidence was most important in these countries. Responses from the UK, France, Spain and Italy showed convenience as the most important attribute in these countries. Two attributes, confidence and convenience, were jointly favoured by respondents in Greece. CONCLUSION: Patients in different European countries do not have the same preferences for the attributes of diagnostic tests to manage AMR in primary care. Failure to account for such differences during test development could reduce test uptake, result in continued overuse of antibiotics, and hamper marketisation.