Preferences For Health States Research Articles

Developing an Australian Value Set for the Recovering Quality of Life-Utility Index (ReQoL-UI) instrument using Discrete Choice Experiment with Duration.

The Recovering Quality of Life-Utility Index (ReQoL-UI) instrument was designed to measure the quality of life outcomes for people over 16 years of age with mental health problems. We aim to elicit societal preferences for the ReQoL-UI health states to facilitate better decision-making in Australia. A discrete choice experiment (DCE) with duration was embedded in a self-complete online survey and administered to a representative sample (n=1019) of the Australian adult population aged 18 years and more, stratified for age, sex and geographic location. A partial subset design DCE was used with 3 fixed attributes and 5 varying attributes containing 240 choice tasks that were blocked into 20 blocks, so that each respondent was assigned a block of 12 choice tasks. The value set was modelled using the conditional logit model with utility decrements directly anchored on the 0 to 1 dead-full health scale. Preference heterogeneity was tested using the mixed logit model. The final value set reflects the monotonic nature of the ReQoL-UI descriptive systems where the best health state defined by the descriptive system has a value of 1 and the worst state has a value of -0.585. The most important dimension was physical health problems while the least important attribute was self-perception. Sensitivity analysis and analysis of preference heterogeneity show the stability of the value set. The value set which reflects the preferences of the Australian population facilitates the calculation of an index for quality-adjusted life years in mental health interventions cost-utility analyses.

A Value Set for the EQ-5D-5L for United Arab Emirates.

Objectives To develop a value set for the EQ-5D-5L based on preferences of the general adult population of the United Arab Emirates (UAE). Methods The study followed the EuroQol EQ-5D-5L Valuation protocol and involved conducting interviewer-administered face-to-face or online interviews in Arabic or English, using the EuroQol Valuation Technology (EQ-VT) with a sample of 1005 adults representing the UAE general population. Sample recruitment involved a two-stage quota sampling strategy across the seven Emirates of the UAE, ensuring representation of nationals and expatriates. Various models using composite time-trade-off (cTTO) data only, discrete choice experiment (DCE) data only, and hybrid using both cTTO and DCE data were examined, along with various sensitivity analyses to examine the robustness of the models. Results Average age of respondents was 39 years (SD=10.8), 44.5% were female, and 11% were UAE nationals. The best performing model to generate the value set for the EQ-5D-5Lwas the hybrid Tobit model censored at -1.0, corrected for heteroskedasticity. Values ranged from - 0.654 for the worst health state (55555) to 1 for full health (11111) and 0.962 for 11211, with 15.3% of predicted values worse than dead. Mobility problems had the largest impact on health state preference values relative to other dimensions. Conclusion This value set will facilitate the application and use of the EQ-5D-5L instrument in the UAE population in generating local evidence on the cost-effectiveness of healthcare interventions, as well as to enhance other applications of EQ-5D in population health assessment and health systems.

Cost‐Effectiveness Analysis of Risky Health Interventions: Moving Beyond Risk Neutrality

ABSTRACTCost‐effectiveness analysis for health interventions is traditionally conducted in a risk‐neutral way, insensitive to risk attitudes in the population, which are potentially non‐neutral. While the standard outcome metric of quality‐adjusted life years (QALYs) aims to be deferential to people's valuations of health states, cost‐effectiveness analysis of risky interventions using the QALY metric is not similarly deferential to people's risk attitudes. I argue that there is no good justification for this practice. Non‐neutral attitudes to risk, especially where they concern individually life‐changing interventions need not be irrational, and so imposing neutrality is not justifiable as a way of debiasing preferences. Many common justifications for deference to health state preferences extend to risk attitudes. But even if reasons for deference do not extend, imposition of risk neutrality as opposed to any other rationally permissible risk attitude is under‐motivated as default practice. Thus, either methods for measuring risk attitudes separately and incorporating them into cost‐effectiveness analysis should be used more widely or a richer set of information should be presented to political decision‐makers and the public to enable them to decide how to take into account the individual risks faced by members of the population, on top of aggregate effects on population health.

Deriving disability weights for the Netherlands: findings from the Dutch disability weights measurement study

BackgroundThe aims of this study were to establish national disability weights based on the health state preferences of a Dutch general population sample, examine the relation between results and respondent’s characteristics, and compare disability weights with those estimated in the European disability weights study.MethodsIn this cross-sectional study, a web-based survey was administered to a general population 18–75 years from the Netherlands. The survey included paired comparison questions. Paired comparison data were analysed using probit regression and located results onto the 0-to-1 disability weight scale using non-parametric regression. Bootstrapping was used to estimate 95% uncertainty intervals (95%UI). Spearman’s correlation was used to investigate the relation of probit regression coefficients between respondent’s characteristics.Results3994 respondents completed the questionnaire. The disability weights ranged from 0.007 (95%UI: 0.003–0.012) for mild distance vision impairment to 0.741 (95% UI: 0.498–0.924) for intensive care unit admission. Spearman’s correlation of probit coefficients between sub-groups based on respondent’s characteristics were all above 0.95 (p < 0.001). Comparison of disability weights of 140 health states that were included in the Dutch and European disability weights study showed a high correlation (Spearman’s correlation: 0.942; p < 0.001); however, for 76 (54.3%) health states the point estimate of the Dutch disability weight fell outside of the 95%UI of the European disability weights.ConclusionsRespondent’s characteristics had no influence on health state valuations with the paired comparison. However, comparison of the Dutch disability weights to the European disability weights indicates that health state preferences of the general population of the Netherlands differ from those of other European countries.

A Survey to Determine Health Utility States After a Traumatic Brain Injury (TBI): Influence of a History of TBI on Disability Perceptions.

Background The Glasgow Outcome Scale-Extended (GOSE) has emerged as one of the most widely used outcome instruments for evaluating ongoing disability and recovery after traumatic brain injury (TBI). The influence of a personal history of TBI on disability perception and quality of life is not well understood. This study aimed to assess changes in health utility states using the GOSE among individuals with severe TBI and their caregivers compared to a general population group. We hypothesized that individuals with a history of TBI, either as patients or caregivers, would recognize health utility associated with a more severe disability than the general population group. Methodology This cross-sectional, observational study included 300 individuals with a history of severe TBI, 300 designated primary caregivers or family members, with 1:1 participation for each subject with severe TBI, and 300 participants from the general population. A computer-based survey was developed based on the GOSE. Participants assessed hypothetical scenarios representing one-year post-TBI outcomes using a standard gamble approach. The main measure for this study was participants' perceptions of health-related quality of life and preferences for different GOSE health states following TBI. Results Of the 900 initial participants, 10 were excluded. Among the remaining 890 participants, lower GOSE states were rated to have lower health utilities. The general population group exhibited a notable decrease in health utility ratings from GOSE4 to GOSE3. Individuals with a history of severe TBI and their caregivers or family members experienced the most substantial decline in health utility ratings between GOSE3 and GOSE2. TBI and caregiver/family member status correlated with higher health utility ratings. Conclusions This study validated the use of the GOSE as a health utility metric and emphasized the subjective nature of acceptable outcomes. These findings underscore the need for considering personal experiences and preferences in decision-making regarding TBI care.

The impact of demographic change on value set validity and obsolescence.

To investigate the contribution of demographic trends in countries' age and gender composition to value set validity and obsolescence. Time-trade off (TTO) valuation data from 3 EQ-5D-3L value sets of 20 years or older from the United Kingdom, Japan, and the United States were re-analyzed using Bayesian heteroskedastic Tobit models with sex and age group-specific scale parameters. Original value sets were obtained by weighting the original preference structures with the countries' original demographic composition at the time of the data collection. Updated value sets were created using the original preference structure weighted using the countries' most recent demographic composition. The differences between the original and updated value sets were monitored and compared based on 95% credible intervals. The gender and age composition of the investigated countries changed in all 3 countries over time. The modelled health state preferences also depended on the respondents' gender and age. However, the overall impact of this demographic change on the investigated value sets was negligeable in all 3 countries and this finding was robust to accounting for the impact of ethnicity trends in the United States. Value sets may become redundant and obsolete for various reasons, but demographic change was not identified as a contributing factor.

Comparison of Caregiver and General Population Preferences for Dependency-Related Health States.

We assess whether the preferences regarding dependency-related health states as stated by informal caregivers are aligned with those expressed by the general population. The preferences of a sample of 139 Spanish informal caregivers of dependent patients are compared with those obtained via a sample of 312 persons, also from the Spanish general population. We assess 24 dependency states extracted from the DEP-6D using the time trade-off method. Descriptive statistics and regression methods are used to explore differences between the two samples. Mean difference tests establish that, for all but one of the 24 states, there are no significant differences between the samples. The estimated mean values ranged from - 0.64 to 0.60 for the caregiver sample and from - 0.60 to 0.65 for the general population sample, with a correlation of 0.96. On average, the classification of states as better or worse than dead matched in both samples (except for one state). Regression models also show that sample type does not have a significant average impact. After we introduce interaction effects, only the most severe level of two dimensions, cognitive problems and housework, result in significant differences-with the caregiver sample reporting higher values for the former, and lower values for the latter. Caregivers and the general population exhibit quite similar preferences concerning dependency-related health states. This suggests that the results of cost-utility analyses, and the resource allocation decisions based on them, would likewise not be significantly affected by the preferences used to generate the weighting algorithm.

Patients' values and preferences for health states in allergic rhinitis-An artificial intelligence supported systematic review.

Allergic rhinitis (AR) impacts patients' physical and emotional well-being. Assessing patients' values and preferences (V&P) related to AR is an essential part of patient-centered care and of the guideline development process. We aimed to systematically summarize the information about patients' V&P on AR and its symptoms and impact on daily life. We conducted systematic review in a MEDLINE, Embase, PsychInfo, and CINAHL databases. We included studies which quantitatively assessed patients' V&P for specific outcomes in AR by assessing utilities, applying discrete choice approaches, or rating and ranking outcomes. We grouped outcomes as AR symptoms, functional status, and care-related patient experience. Study selection and data extraction were supported by the Laser AI tool. We rated the certainty of evidence (CoE) using the GRADE approach. Thirty-six studies (41 records) were included: nine utility studies, seven direct-choice studies and 21 studies of rating or ranking outcomes. Utilities were lower with increased AR severity and with the concomitant presence of asthma, but not with whether AR was seasonal or perennial (CoE = low-high). Patients rated AR symptom-related outcomes as more important than those related to care-related patient experience and functional status (CoE = very low-moderate). Nasal symptoms (mainly nasal congestion) followed by breathing disorders, general and ocular symptoms were rated as the symptoms with the highest impact. This systematic review provides a comprehensive overview of V&P of patients with AR. Patients generally considered nasal symptoms as the most important. Future studies with standardized methods are needed to provide more information on V&P in AR.

Would You Rather: Quantifying TBI Survivor Perceptions of Functional Status via Their Surrogates.

To quantify health utilities of the Glasgow Outcome Scale-Extended (GOSE) states after actual Traumatic Brain Injury (TBI). Recovery after TBI is measured using the GOSE, a validated clinical trial endpoint. A recent public survey quantified the health utilities of some GOSE states after hypothetical TBI as worse than death. However, no health utilities exist for disability after actual TBI. This national computer-adaptive survey followed EQUATOR-CHERRIES guidelines and recruited adult TBI survivors (injury>1y prior) via their available surrogates. Using a standard gamble approach in randomized order, participants gave preferences for post-TBI categorical health states ranging from GOSE 2-8. We calculated median [interquartile range, IQR] health utilities for each GOSE state, from -1 (worse than death) to 1 (full health), with 0 as reference (death, GOSE 1). Of 515 eligible, 298 surrogates (58%) consented and completed the scenarios on TBI survivors' behalf. TBI survivors had a current median GOSE 5 [3-7]. GOSE 2, GOSE 3, and GOSE 4 were rated worse than death by 89%, 64%, and 38%, respectively. The relationship was nonlinear, and intervals were unequal between states, with a bimodal distribution for GOSE 4. In this index study of actual post-TBI disability, poor neurologic outcomes represented by GOSE 2-4 were perceived as worse than death by at least one in three survivors. Similar to previously reported public perceptions after a hypothetical TBI, these long-term perceptions may inform earlier post-TBI shared decision making, as well as help shape value-based research and quality of care. II, Economic & Value-based Evaluations.

Exploring health preference heterogeneity in the UK: Using the online elicitation of personal utility functions approach to construct EQ-5D-5L value functions on societal, group and individual level.

A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

Development of a value-based scoring system for the MobQoL-7D: a novel tool for measuring quality-adjusted life years in the context of mobility impairment

Purpose To create a preference-based value set scoring system for the MobQoL-7D outcome measure, and to examine differences in the health state preferences of the general population and individuals with impaired mobility. Methods and materials A preference elicitation study was undertaken to ascribe utility weights to all health states (i.e., all unique combination of answers) described by the MobQoL-7D. The elicitation exercise was developed using the Online Elicitation of Personal Utility Functions (OPUF) tool. Two UK sample groups were recruited; firstly a representative general population sample (N = 504), secondly a balanced sample of individuals with impaired mobility (N = 368). Distinct preference-based value sets were developed for each sample. Differences in dimension ranking, weighting, and overall utility values were assessed. Results The general population sample considered most health states, especially the more severe states, to be worse than the mobility impaired sample comparatively. Statistically significant differences between the samples were observed in four of the seven MobQoL-7D dimensions. Conclusions This study is the first to provide preference-based value sets for the MobQoL-7D, ready for use in economic evaluations, QALY calculation, and other clinical or research applications. The study demonstrates how the general public and individuals with impaired mobility value health states differently.

From simple to even simpler, but not too simple: a head-to-head comparison of the Better-Worse and Drop-Down methods for measuring patient health status

BackgroundWe recently developed a novel, preference-based method (Better-Worse, BW) for measuring health status, expressed as a single metric value. We have since expanded it by developing the Drop-Down (DD) method. This article presents a head-to-head comparison of these two methods. We explored user feasibility, interpretability and statistics of the estimated coefficients, and distribution of the computed health-state values.MethodsWe conducted a cross-sectional online survey among patients with various diseases in the USA. The BW and DD methods were applied in the two arms of the study, albeit in reverse order. In both arms, patients first performed a descriptive task (Task 1) to rate their own health status according to the 12 items (each with 4 levels) in the CS-Base health-outcome instrument. They then performed Task 2, in which they expressed preferences for health states by the two methods. We then estimated coefficients for all levels of each item using logistic regression and used these to compute values for health states.ResultsOur total sample comprised 1,972 patients. Completion time was < 2 min for both methods. Both methods were scored as easy to perform. All DD coefficients were highly significant from the reference level (P < 0.001). For BW, however, only the second-level coefficient of “Cognition” was significantly different (P = 0.026). All DD coefficients were more precise with narrower confidence intervals than those of the BW method.ConclusionsBoth the BW and DD are novel methods that are easy to apply. The DD method outperformed the BW method in terms of the precision of produced coefficients. Due to its task, it is free from a specific distorting factor that was observed for the BW method.

UnitedStates Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.

To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire. A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient. 2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33. This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

PCR49 A Preliminary Comparison between Analytical Hierarchy Process and Discrete Choice Experiment in Health State Preferences in Hong Kong SAR, China

PCR49 A Preliminary Comparison between Analytical Hierarchy Process and Discrete Choice Experiment in Health State Preferences in Hong Kong SAR, China

EE608 The Use of Vignette Studies to Estimate Health-State Preference in Sweden and Norway

EE608 The Use of Vignette Studies to Estimate Health-State Preference in Sweden and Norway

Influence of Self-Reported Health Impairments on German EQ-5D-5L Values

ObjectivesThe German EQ-5D-5L value set is based on the average preferences of the general population. Nevertheless, in Germany, there is an ongoing debate about the appropriateness of using general population preferences and whether patient preferences should be used instead. Thus, this research aimed to determine the robustness of the German EQ-5D-5L valuation data for the general population compared with those with health impairments. MethodsSubgroups were built on the self-reported quality of life, measured with the EQ-5D-5L. To identify which groups significantly influenced the value set, different regression models, including dummy variables for the subgroups, were tested while controlling for preference heterogeneity. Backward selection based on the Akaike information criterion led to significant subgroup dummies, which were analyzed in more detail. For each significant subgroup, the value set model was estimated separately. The models were then compared. Sociodemographics of the subgroups were considered. ResultsThree significant dummies were identified: state 11111, severity levels 5 to 7, and self-reported problems with pain/discomfort. The value sets for the 6 subgroups were compared with the national German value set, showing only marginal deviations. The mean absolute deviation ranged from 0.004 to 0.013. No different densities were identified for the decrements of the different value sets. ConclusionsPeople with self-reported health impairments do not have different EQ-5D-5L health state preferences compared with the German general population. Further research is needed to determine whether the presence of a chronic health condition has a larger influence on health state valuation than the general population.

How sure are you? — the properties of self-reported conviction in the elicitation of health preferences with discrete choice experiments

Discrete choice experiments (DCE) are often used to elicit preferences, for instance, in health preference research. However, DCEs only provide binary responses, whilst real-life choices are made with varying degrees of conviction. We aimed to verify whether eliciting self-reported convictions on a 0–100 scale adds meaningful information to the binary choice. Eighty three respondents stated their preferences for health states using DCE and the time trade-off method (TTO). In TTO, utility ranges were also elicited to account for preference imprecision. We verified the properties of the conviction across three areas: (1) response to various choice task modifications (e.g. dominance, increase in complexity, distance from the status quo) and association with rationality violations (e.g. intransitivity); (2) association with test–retest results; (3) relation to the utility difference and imprecision estimated in TTO. Regarding (1), conviction increased in choice tasks with lower complexity, larger relative attractiveness, and lower distance to the status quo. Regarding (2), choices made with above-median conviction were sustained in 90% of the cases, compared to 68% for below-median conviction. Regarding (3), the conviction increases with utility difference and it decreases with utility imprecision; overconfidence seems to prevail: non-zero conviction is reported even for identical utilities. Self-reported conviction in DCE is associated in an intuitive way with the observed choices. It may, therefore, be useful in explaining or predicting behaviour or bridging the gap between the results of various elicitation tasks.

Urban/rural differences in preferences for EQ-5D-5L health states: a study of a multi-ethnic region in China.

This study aimed to compare health preferences for EQ-5D-5L health states between urban and rural populations in China. This study used pooled secondary data from two EQ-5D-5L valuation studies. Participants were recruited from Guizhou province and Chongqing municipality, China using quota sampling. Each participant was interviewed face-to-face to value a set of 15 or 16 out of 30 EQ-5D-5L health states using time trade-off (TTO) methods including composite TTO and other two variants. Regression analysis was used to compare health state preferences between urban and rural participants. A total of 597 participants (urban: 55.44%; rural: 44.56%) completed the valuation interviews. Both univariate and multivariable linear regression analyses showed that rural participants tended to value health states lower than urban participants regardless of severity of health states. The unadjusted and adjusted overall mean differences between the two groups were -0.041 (95% confidence interval [CI] -0.077, -0.004, p-value = 0.031) and -0.040 (95% CI -0.078, -0.002, p-value = 0.038), respectively. Predictions for the 3125 health states based on rural participants' health preferences were lower than those based on urban participants' health preferences. There were small, yet statistically significant, differences in EQ-5D-5L health states preferences between urban and rural populations in China. Future study aiming at establishing a national value set should pay more attention to the sample representativeness.

A national survey of Iranian general population to estimate a value set for the EQ-5D-5L.

The main aim of this study is to estimate a national value set of the EQ-5D-5L questionnaire for Iran. The composite time trade-off (cTTO) and discrete choice experiment (DCE) methods; and the protocol for EuroQol Portable Valuation Technology (EQ-PVT) were used to estimate the Iran national value set. 1179 face-to-face computer-assisted interviews were conducted with adults that were recruited from five Iran major cities in 2021. Generalized least squares, Tobit, heteroskedastic, logit, and hybrid models were used to analyze the data and to identify the best fitting model. According to the logical consistency of the parameters, significance levels and prediction accuracy indices of the MAE; a heteroscedastic censored Tobit hybrid model combining cTTO and DCE responses was considered as the best fitting model to estimate the final value set. The predicted values ranged from -1.19 for the worst health state (55555) to 1 for full health (11111), with 53.6% of the predicted values being negative. Mobility was the most influential dimension on health state preference values. The present study estimated a national EQ-5D-5L value set for Iranian policy makers and researchers. The value set enables the EQ-5D-5L questionnaire to use to calculate QALYs to assist the priority setting and efficient allocation of limited healthcare resources.

In search of a ‘pan-European value set’; application for EQ-5D-3L

ObjectivesCountry-specific value sets for the EQ-5D are available which reflect preferences for health states elicited from the general population. This allows the transformation of responses on EQ-5D to health state utility values. Only twelve European countries possess country-specific value sets and no value set reflecting the preferences of Europe exists. We aim to estimate a ‘pan-European’ value set for the EQ-5D-3L, reflecting the preferences for health states of the European population that could help to evaluate health care from the perspective of the European decision-maker.MethodsWe systematically assessed and compared the methodologies of available EQ-5D-3L time trade-off (TTO) value sets from twelve European countries: Denmark, France, Germany, Hungary, Italy, Netherlands, Poland, Portugal, Romania, Slovenia, Spain and UK. Using their published coefficients, a dataset with utility values for all 243 health states was simulated. Different modelling techniques and model specifications including interaction terms were tested. Model selection was based on goodness-of-fit criteria. We also explored results with application of population size weights.ResultsMethodological, procedural and analytical characteristics of the included EQ-5D-3L valuation studies were quite comparable. An OLS based model was the preferred model to represent European preferences. Weighting with population size made little difference.ConclusionsEQ-5D-3L valuation studies were considered of sufficient comparability to form the basis for a new ‘pan-European’ value set. The method used allows for an easy update when new national value sets become available.