Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments.

A randomized controlled discrete choice experiment (DCE) with 3,320 participating respondents was used to investigate the individual and combined impact of level overlap and color coding on task complexity, choice consistency, survey satisfaction scores, and dropout rates. The systematic differences between the study arms allowed for a direct comparison of dropout rates and cognitive debriefing scores and accommodated the quantitative comparison of respondents' choice consistency using a heteroskedastic mixed logit model. Our results indicate that the introduction of level overlap made it significantly easier for respondents to identify the differences and choose between the choice options. As a stand-alone design strategy, attribute level overlap reduced the dropout rate by 30%, increased the level of choice consistency by 30%, and avoided learning effects in the initial choice tasks of the DCE. The combination of level overlap and color coding was even more effective: It reduced the dropout rate by 40% to 50% and increased the level of choice consistency by more than 60%. Hence, we can recommend attribute level overlap, with color coding to amplify its impact, as a standard design strategy in DCEs.

Effect of Level Overlap and Color Coding on Attribute Non-Attendance in Discrete Choice Experiments.

OBJECTIVE: The aim of this study was to test the hypothesis that level overlap and color coding can mitigate or even preclude the occurrence of attribute nonattendance in discrete choice experiments. METHODS: A randomized controlled experiment with five experimental study arms was designed to investigate the independent and combined impact of level overlap and color coding on respondents' attribute nonattendance. The systematic differences between the study arms allowed for a direct comparison of observed dropout rates and estimates of the average number of attributes attended to by respondents, which were obtained by using augmented mixed logit models that explicitly incorporated attribute non-attendance. RESULTS: In the base-case study arm without level overlap or color coding, the observed dropout rate was 14%, and respondents attended, on average, only two out of five attributes. The independent introduction of both level overlap and color coding reduced the dropout rate to 10% and increased attribute attendance to three attributes. The combination of level overlap and color coding, however, was most effective: it reduced the dropout rate to 8% and improved attribute attendance to four out of five attributes. The latter essentially removes the need to explicitly accommodate for attribute non-attendance when analyzing the choice data. CONCLUSIONS: On the basis of the presented results, the use of level overlap and color coding are recommendable strategies to reduce the dropout rate and improve attribute attendance in discrete choice experiments.

Advocating a Paradigm Shift in Health-State Valuations: The Estimation of Time-Preference Corrected QALY Tariffs.

BACKGROUND: Despite evidence of nonproportional trade-offs in time trade-off exercises and the explicit incorporation of exponential discounting in health technology assessment calculations, quality-adjusted life-year (QALY) tariffs are currently still established under the assumption of linear time preferences. OBJECTIVES: The aim of this study was to introduce a general method of accommodating for nonlinear time preferences in discrete choice experiment (DCE) duration studies and to evaluate its impact on estimated QALY tariffs. METHODS: A parsimonious utility function is proposed that accommodates any discounting function and preserves linear time preferences as a special case. Based on an efficient DCE design and 1775 respondents from a nationally representative scientific household panel, preferences and QALY tariffs for the Dutch SF-6D were estimated while accommodating for nonlinear time preferences via exponential and hyperbolic discounting functions. RESULTS: When the discount rate was estimated directly, we found strong evidence of nonlinear time preferences (with an exponential and hyperbolic discount rate of 5.7% and 16.5%, respectively). When the discount rate was estimated as a function of health state severity, we found that years lived in better health states are discounted minus years lived in impaired health states. Finally, the best statistical fit was obtained when using a hyperbolic discount function, which resulted in smaller QALY decrements and fewer health states classified as worse than immediate death. CONCLUSIONS: Our results highlight the relevance and even necessity of a paradigm shift in health valuation studies in favor of time-preference corrected QALY tariffs, with potentially important implications for health technology assessment calculations and regulatory decisions.

Choice Defines Value: A Predictive Modeling Competition in Health Preference Research.

OBJECTIVE: To identify which specifications and approaches to model selection better predict health preferences, the International Academy of Health Preference Research (IAHPR) hosted a predictive modeling competition including 18 teams from around the world. METHODS: In April 2016, an exploratory survey was fielded: 4074 US respondents completed 20 out of 1560 paired comparisons by choosing between two health descriptions (e.g., longer life span vs. better health). The exploratory data were distributed to all teams. By July, eight teams had submitted their predictions for 1600 additional pairs and described their analytical approach. After these predictions had been posted online, a confirmatory survey was fielded (4148 additional respondents). RESULTS: The victorious team, "Discreetly Charming Econometricians," led by Michal Jakubczyk, achieved the smallest χ2, 4391.54 (a predefined criterion). Its primary scientific findings were that different models performed better with different pairs, that the value of life span is not constant proportional, and that logit models have poor predictive validity in health valuation. CONCLUSIONS: The results demonstrated the diversity and potential of new analytical approaches in health preference research and highlighted the importance of predictive validity in health valuation.

Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self-assessed Health and an Efficient Discrete Choice Experiment.

Health state valuations of patients and non-patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often-overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd.

EQ-5D in Central and Eastern Europe: 2000-2015.

OBJECTIVE: Cost per quality-adjusted life year data are required for reimbursement decisions in many Central and Eastern European (CEE) countries. EQ-5D is by far the most commonly used instrument to generate utility values in CEE. This study aims to systematically review the literature on EQ-5D from eight CEE countries. METHODS: An electronic database search was performed up to 1 July 2015 to identify original EQ-5D studies from the countries of interest. We analysed the use of EQ-5D with respect to clinical areas, methodological rigor, population norms and value sets. RESULTS: We identified 143 studies providing 152 country-specific results with a total sample size of 81,619: Austria (n = 11), Bulgaria (n = 6), Czech Republic (n = 18), Hungary (n = 47), Poland (n = 51), Romania (n = 2), Slovakia (n = 3) and Slovenia (n = 14). Cardiovascular (21 %), neurologic (17 %), musculoskeletal (15 %) and endocrine, nutritional and metabolic diseases (13 %) were the most frequently studied clinical areas. Overall, 112 (78 %) of the studies reported EQ VAS results and 86 (60 %) EQ-5D index scores, of which 27 (31 %) did not specify the applied tariff. Hungary, Poland and Slovenia have population norms. Poland and Slovenia also have a national value set. CONCLUSIONS: Increasing use of EQ-5D is observed throughout CEE. The spread of health technology assessment activities in countries seems to be reflected in the number of EQ-5D studies. However, improvement in informed use and methodological quality of reporting is needed. In jurisdictions where no national value set is available, in order to ensure comparability we recommend to apply the most frequently used UK tariff. Regional collaboration between CEE countries should be strengthened.

Cost-effectiveness of the 'Walcheren Integrated Care Model' intervention for community-dwelling frail elderly.

BACKGROUND: An important aim of integrated care for frail elderly is to generate more cost-effective health care. However, empirical research on the cost-effectiveness of integrated care for community-dwelling frail elderly is limited. OBJECTIVE: This study reports on the cost-effectiveness of the Walcheren Integrated Care Model (WICM) after 12 months from a societal perspective. METHODS: The design of this study was quasi-experimental. In total, 184 frail elderly patients from 3 GP practices that implemented the WICM were compared with 193 frail elderly patients of 5 GP practices that provided care as usual. Effects were determined by health-related quality of life (EQ-5D questionnaire). Costs were assessed based on questionnaires, GP files, time registrations and reports from multidisciplinary meetings. Average costs and effects were compared using t-tests. The incremental cost-effectiveness ratio (ICER) was calculated, and bootstrap methods were used to determine its reliability. RESULTS: Neither the WICM nor care as usual resulted in a change in health-related quality of life. The average total costs of the WICM were higher than care as usual (17089 euros versus 15189 euros). The incremental effects were 0.00, whereas the incremental costs were 1970 euros, indicating an ICER of 412450 euros. CONCLUSIONS: The WICM is not cost-effective, and the costs per quality-adjusted life year are high. The costs of the integrated care intervention do not outweigh the limited effects on health-related quality of life after 12 months. More analyses of the cost-effectiveness of integrated care for community-dwelling frail elderly are recommended as well as consideration of the specific costs and effects.

Multinational evidence of the applicability and robustness of discrete choice modeling for deriving EQ-5D-5L health-state values.

AIMS: To investigate the feasibility of discrete choice experiments for valuing EQ-5D-5L states using computer-based data collection, the consistency of the estimated regression coefficients produced after modeling the preference data, and to examine the similarity of the values derived across countries. METHODS: Data were collected in Canada, England, The Netherlands, and the United States (US). Interactive software was developed to standardize the format of the choice tasks across countries, except for face-to-face interviewing in England. The choice task required respondents to choose between 2 suboptimal health states. A Bayesian design was used to generate 200 pairs of states that were randomly grouped into 20 blocks. Each respondent completed 1 block of 10 pairs. A main-effects probit model was used to estimate regression coefficients and to derive values. RESULTS: Approximately 400 respondents participated from each country. The mean time to perform 1 choice task was between 29.2 (US) and 45.2 (England) seconds. All regression coefficients were statistically significant, except level 2 for Usual Activities in The Netherlands (P=0.51). Predictions for the complete set of 3125 EQ-5D-5L health states were similar for the 4 countries. Intraclass correlation coefficients between the countries were high: from 0.80 (England vs. US) through 0.98 (Canada vs. US) CONCLUSIONS: Derivation of value sets from the general population using computer-based choice tasks for the EQ-5D-5L is feasible. Parameter estimates were generally consistent and logical, and health-state values were similar across the 4 countries.

Putting the Choice in Choice Tasks: Incorporating Preference Elicitation Tasks in Health Preference Research.

Choice-based preference elicitation methods such as the discrete choice experiment (DCE) present hypothetical choices to respondents, with an expectation that these hypothetical choices accurately reflect a 'real world' health-related decision context and that consequently the choice data can be held to be a true representation of the respondent's health or treatment preferences. For this to be the case, careful consideration needs to be given to the format of the choice task in a choice experiment. The overarching aim of this paper is to highlight important aspects to consider when designing and 'setting up' the choice tasks to be presented to respondents in a DCE. This includes the importance of considering the potential impact of format (e.g. choice context, choice set presentation and size) as well as choice set content (e.g. labelled and unlabelled choice sets and inclusion of reference alternatives) and choice questions (stated choice versus additional questions designed to explore complete preference orders) on the preference estimates that are elicited from studies. We endeavoure to instil a holistic approach to choice task design that considers format alongside content, experimental design and analysis.

Lead time TTO: leading to better health state valuations?

Preference elicitation tasks for better than dead (BTD) and worse than dead (WTD) health states vary in the conventional time trade-off (TTO) procedure, casting doubt on uniformity of scale. 'Lead time TTO' (LT-TTO) was recently introduced to overcome the problem. We tested different specifications of LT-TTO in comparison with TTO in a within-subject design. We elicited preferences for six health states and employed an intertemporal ranking task as a benchmark to test the validity of the two methods. We also tested constant proportional trade-offs (CPTO), while correcting for discounting, and the effect of extending the lead time if a health state is considered substantially WTD. LT-TTO produced lower values for BTD states and higher values for WTD states. The validity of CPTO varied across tasks, but it was higher for LT-TTO than for TTO. Results indicate that the ratio of lead time to disease time has a greater impact on results than the total duration of the time frame. The intertemporal ranking task could not discriminate between TTO and LT-TTO.

Condition-specific preference-based measures: benefit or burden?

OBJECTIVES: Some argue that generic preference-based measures (PBMs) are not sensitive to certain disease-specific improvements. To overcome this problem, new condition-specific PBMs (CS-PBMs) are being developed, but it is not yet clear how such measures compare with existing generic PBMs. METHOD: We generated CS-PBMs from three condition-specific questionnaires (Health Assessment Questionnaire for arthritis, Quality of Life Questionnaire for Cancer 30 for cancer, and Multiple Sclerosis Impact Scale 29 for multiple sclerosis). First, the questionnaires were reduced in content, and then, a time trade-off study was conducted in the general public (N = 402) to obtain weights associated with the dimensions and levels of the new questionnaire. Finally, we compared utilities obtained by using the CS-PBMs with utilities obtained by using the EuroQol five-dimensional (EQ-5D) questionnaire in four data sets. RESULTS: Utility values generated by the CS-PBMs were higher than those of the EQ-5D questionnaire. The Health Assessment Questionnaire-based measure for arthritis proved to be insensitive to comorbidities. Measures based on the Multiple Sclerosis Impact Scale 29 and the Quality of Life Questionnaire for Cancer 30 discriminated comorbidities and side effect equally well as the EQ-5D questionnaire and were more sensitive than the EQ-5D questionnaire for mild impairments. CONCLUSIONS: The introduction of PBMs that are specific to a certain disease may have the merit of sensitivity to disease-specific effects of interventions. That gain, however, is traded off to the loss of comparability of utility values and, in some cases, insensitivity to side effects and comorbidity. The use of a CS-PBM for cost-utility analysis is warranted only under strict conditions.

Physicians underestimate the importance of patient-centredness to patients: a discrete choice experiment in fertility care.

BACKGROUND: High-quality healthcare should be effective, safe and patient-centred. How important patient-centredness is in relation to effectiveness of fertility care has never been investigated. This study aimed to determine and compare the importance of patient-centredness, relative to pregnancy rates, to patients and physicians. METHODS: A discrete choice experiment (DCE) was designed. Participants had to choose between hypothetical fertility clinics differing in following attributes: travel time; pregnancy rate (effectiveness); physicians' attitude; information on treatment; and continuity of physicians (the latter three represent patient-centredness). A total of 1378 patients and 268 physicians from eight Dutch and Belgian fertility clinics received the DCE-questionnaire. The attributes' relative importance was analysed using multinomial logistic regression. Additionally, patients' actual choice behaviour was investigated. RESULTS: In total, 925 patients and 227 physicians participated. Pregnancy rates were relatively more important to physicians. Patients assigned more value to patient-centredness (P < 0.001) and were willing to trade-off a higher pregnancy rate for patient-centredness than physicians recommended them to do (P < 0.05). For example, patients considered pregnancy rates 1.5 times as important as an interested physician's attitude, whereas physicians considered this 2.4 times as important (P < 0.001). The willingness to trade-off pregnancy rate for this attitude was 9.8% for patients and 6.3% for physicians (P < 0.001). A lack of patient-centredness was the most cited non-medical reason for changing fertility clinics. CONCLUSIONS: Patients and physicians put considerable value on pregnancy rates. However, physicians significantly undervalue the importance of patient-centredness to patients. Clinics aiming to optimize the quality of their services should be aware of the substantial importance their patients assign to patient-centredness.

The cost-effectiveness of an intensive treatment protocol for severe dyslexia in children.

Studies of interventions for dyslexia have focused entirely on outcomes related to literacy. In this study, we considered a broader picture assessing improved quality of life compared with costs. A model served as a tool to compare costs and effects of treatment according to a new protocol and care as usual. Quality of life was measured and valued by proxies using a general quality-of-life instrument (EQ-5D). We considered medical cost and non-medical cost (e.g. remedial teaching). The model computed cost per successful treatment and cost per quality adjusted life year (QALY) in time. About 75% of the total costs was related to diagnostic tests to distinguish between children with severe dyslexia and children who have reading difficulties for other reasons. The costs per successful treatment of severe dyslexia were €36 366. Successful treatment showed a quality-of-life gain of about 11%. At primary school, the average cost per QALY for severe dyslexia amounted to €58 647. In the long term, the cost per QALY decreased to €26 386 at secondary school and €17 663 thereafter. The results of this study provide evidence that treatment of severe dyslexia is cost-effective when the investigated protocol is followed.

Discrete choice modeling for the quantification of health states: the case of the EQ-5D.

OBJECTIVES: Probabilistic models have been developed to establish the relative merit of subjective phenomena by means of specific judgmental tasks involving discrete choices (DCs). The attractiveness of these DC models is that they are embedded in a strong theoretical measurement framework and are based on relatively simple judgmental tasks. The aim of our study was to determine whether the values derived from a DC experiment are comparable to those obtained using other valuation techniques, in particular the time trade-off (TTO). METHODS: Two hundred nine students completed several tasks in which we collected DC, rank, visual analog scale, and TTO responses. DC data were also collected in a general population sample (N=444). The DC experiment was designed using a Bayesian approach, and involved 60 choices between two health states and a comparison of all health states to being dead. The DC data were analyzed using a conditional logit and a rank-ordered logit model, relying, respectively, on TTO values and the value for being dead to anchor the DC-derived values to the 0 to 1 quality-adjusted life-year (QALY) scale. RESULTS: Although modeled DC data broadly replicated the pattern found in TTO responses, the DC consistently produced higher values. The two methods for anchoring DC-derived values on the QALY scale produced similar results. CONCLUSIONS: On the basis of the high level of comparability between DC-derived values and TTO values, future valuation studies based on a combination of these two techniques may be considered. The results further suggest that DC can potentially be used as a substitute for TTO.

Mapping onto Eq-5 D for patients in poor health.

BACKGROUND: An increasing amount of studies report mapping algorithms which predict EQ-5 D utility values using disease specific non-preference-based measures. Yet many mapping algorithms have been found to systematically overpredict EQ-5 D utility values for patients in poor health. Currently there are no guidelines on how to deal with this problem. This paper is concerned with the question of why overestimation of EQ-5 D utility values occurs for patients in poor health, and explores possible solutions. METHOD: Three existing datasets are used to estimate mapping algorithms and assess existing mapping algorithms from the literature mapping the cancer-specific EORTC-QLQ C-30 and the arthritis-specific Health Assessment Questionnaire (HAQ) onto the EQ-5 D. Separate mapping algorithms are estimated for poor health states. Poor health states are defined using a cut-off point for QLQ-C30 and HAQ, which is determined using association with EQ-5 D values. RESULTS: All mapping algorithms suffer from overprediction of utility values for patients in poor health. The large decrement of reporting 'extreme problems' in the EQ-5 D tariff, few observations with the most severe level in any EQ-5 D dimension and many observations at the least severe level in any EQ-5 D dimension led to a bimodal distribution of EQ-5 D index values, which is related to the overprediction of utility values for patients in poor health. Separate algorithms are here proposed to predict utility values for patients in poor health, where these are selected using cut-off points for HAQ-DI (> 2.0) and QLQ C-30 (< 45 average of QLQ C-30 functioning scales). The QLQ-C30 separate algorithm performed better than existing mapping algorithms for predicting utility values for patients in poor health, but still did not accurately predict mean utility values. A HAQ separate algorithm could not be estimated due to data restrictions. CONCLUSION: Mapping algorithms overpredict utility values for patients in poor health but are used in cost-effectiveness analyses nonetheless. Guidelines can be developed on when the use of a mapping algorithms is inappropriate, for instance through the identification of cut-off points. Cut-off points on a disease specific questionnaire can be identified through association with the causes of overprediction. The cut-off points found in this study represent severely impaired health. Specifying a separate mapping algorithm to predict utility values for individuals in poor health greatly reduces overprediction, but does not fully solve the problem.

Dear policy maker: have you made up your mind? A discrete choice experiment among policy makers and other health professionals.

OBJECTIVES: The aim of this study was to get insight in what criteria as presented in Health technology assessment (HTA) studies are important for decision makers in healthcare priority setting. METHODS: We performed a discrete choice experiment among Dutch healthcare professionals (policy makers, HTA experts, advanced HTA students). In twenty-seven choice sets, we asked respondents to elect reimbursement of one of two different healthcare interventions, which represented unlabeled, curative treatments. Both treatments were incrementally compared with usual care. The results of the interventions were normal outputs of HTA studies with a societal perspective. Results were analyzed using a multinomial logistic regression model. Upon completion of the questionnaire, we discussed the exercise with policy makers. RESULTS: Severity of disease, costs per quality-adjusted life-year gained, individual health gain, and the budget impact were the most decisive decision criteria. A program targeting more severe diseases increased the probability of reimbursement dramatically. Uncertainty related to cost-effectiveness was also important. Respondents preferred health gains that include quality of life improvements over extension of life without improved quality of life. Savings in productivity costs were not crucial in decision making, although these are to be included in Dutch reimbursement dossiers for new drugs. Regarding subgroups, we found that policy makers attached relatively more weight to disease severity than others but less to uncertainty. CONCLUSIONS: Dutch policy makers and other healthcare professionals seem to have reasonably well articulated preferences: six of seven attributes were significant. Disease severity, budget impact, and cost-effectiveness were very important. The results are comparable to international studies, but reveal a larger set of important decision criteria.

Willingness to pay for lives saved by Helicopter Emergency Medical Services.

INTRODUCTION: Currently, policy makers in the Netherlands are discussing the possibility to expand the availability of Helicopter Emergency Medical Services (HEMS) from 12 hours to 24 hours per day. For this, the preferences of the general public towards both the positive effects and negative consequences of HEMS should be taken into account. Therefore, the willingness to pay (WTP) for lives saved by HEMS was calculated. METHODS: A discrete choice experiment (DCE) was performed in order to explore the preferences of respondents towards (expansion of) HEMS availability. The attributes: costs (for HEMS) per household number of additional lives saved (by HEMS), number of noise disturbances (caused by HEMS) during day time or night time were used. A written questionnaire was presented to 150 individuals by convenience sampling. RESULT: One hundred and thirty-six (91%) of the 150 individuals completed the DCE questionnaire. The marginal WTP for one additional life saved (in a month) was euro 3.43 (95% CI; 2.96-3.90) per month per household. Overall, the WTP for expansion to a 24-hour availability of HEMS can therefore be estimated at euro 12.29 ( approximately US$ 17.50) per household per month. CONCLUSION: The WTP derived from this study is by far exceeding the 1-1.5 Million-euro necessary per HEMS per year for the expansion from a daytime HEMS to a 24-h availability in the Netherlands. Respondents are willing to pay for lives saved by HEMS in spite of increases in flights and concurrent noise disturbances. These results may be helpful for the decision-making process, and may provide a positive argument for the expansion of HEMS availability.

Patient preferences for a guided self-help programme to prevent relapse in anxiety or depression: A discrete choice experiment.

BACKGROUND: Anxiety and depressive disorders are increasingly being viewed as chronic conditions with fluctuating symptom levels. Relapse prevention programmes are needed to increase self-management and prevent relapse. Fine-tuning relapse prevention programmes to the needs of patients may increase uptake and effectiveness. MATERIALS AND METHODS: A discrete choice experiment (DCE) was conducted amongst patients with a partially or fully remitted anxiety or depressive disorder. Patients were presented 20 choice tasks with two hypothetical treatment scenarios for relapse prevention, plus a "no treatment" option. Each treatment scenario was based on seven attributes of a hypothetical but realistic relapse prevention programme. Attributes considered professional contact frequency, treatment type, delivery mode, programme flexibility, a personal relapse prevention plan, time investment and effectiveness. Choice models were estimated to analyse the data. RESULTS: A total of 109 patients with a partially or fully remitted anxiety or depressive disorder completed the DCE. Attributes with the strongest impact on choice were high effectiveness, regular contact with a professional, low time investment and the inclusion of a personal prevention plan. A high heterogeneity in preferences was observed, related to both clinical and demographic characteristics: for example, a higher number of previous treatment episodes was related to a preference for a higher frequency of contact with a professional, while younger age was related to a stronger preference for high effectiveness. CONCLUSIONS: This study using a DCE provides insights into preferences for a relapse prevention programme for anxiety and depressive disorders that can be used to guide the development of such a programme.

Exploring the Impact of Adding a Respiratory Dimension to the EQ-5D-5L.

Objectives. To evaluate the impact of adding a respiratory dimension (a bolt-on dimension) to the EQ-5D-5L health state valuations. Methods. Based on extensive regression and principal component analyses, 2 respiratory bolt-on candidates were formulated: R1, limitations in physical activities due to shortness of breath, and R2, breathing problems. Valuation interviews for the selected bolt-ons were performed with a representative sample from the Dutch general public using the standardized interview protocol and software of the EuroQol group. Hybrid models based on the combined time-tradeoff (TTO) and discrete choice experiment (DCE) data were estimated to assess whether the 5 levels of the respiratory bolt-on led to significant changes in utility values. Results. For each bolt-on candidate, slightly more than 200 valuation interviews were conducted. Mean TTO values and DCE choice probabilities for health states with a level 4 or 5 for the respiratory dimension were significantly lower compared with the same health states in the Dutch EQ-5D-5L valuation study without the respiratory dimension. Results of hybrid models showed that for the bolt-on "limitations in physical activities," the utility decrements were significant for level 3 (-0.055), level 4 (-0.087), and level 5 (-0.135). For "breathing problems," the utility decrements for the same levels were greater (-0.086, -0.219, and -0.327, respectively). Conclusions. The addition of each of the 2 respiratory bolt-ons to the EQ-5D-5L had a significant effect on the valuation of health states with severe levels for the bolt-on. The bolt-on dimension "breathing problems" showed the greatest utility decrements and therefore seems the most appropriate respiratory bolt-on dimension.

The Fold-in, Fold-out Design for DCE Choice Tasks: Application to Burden of Disease.

Background In discrete-choice experiments (DCEs), choice alternatives are described by attributes. The importance of each attribute can be quantified by analyzing respondents' choices. Estimates are valid only if alternatives are defined comprehensively, but choice tasks can become too difficult for respondents if too many attributes are included. Several solutions for this dilemma have been proposed, but these have practical or theoretical drawbacks and cannot be applied in all settings. The objective of the current article is to demonstrate an alternative solution, the fold-in, fold-out approach (FiFo). We use a motivating example, the ABC Index for burden of disease in chronic obstructive pulmonary disease (COPD). Methods Under FiFo, all attributes are part of all choice sets, but they are grouped into domains. These are either folded in (all attributes have the same level) or folded out (levels may differ). FiFo was applied to the valuation of the ABC Index, which included 15 attributes. The data were analyzed in Bayesian mixed logit regression, with additional parameters to account for increased complexity in folded-out questionnaires and potential differences in weight due to the folding status of domains. As a comparison, a model without the additional parameters was estimated. Results Folding out domains led to increased choice complexity for respondents. It also gave domains more weight than when it was folded in. The more complex regression model had a better fit to the data than the simpler model. Not accounting for choice complexity in the models resulted in a substantially different ABC Index. Conclusion Using a combination of folded-in and folded-out attributes is a feasible approach for conducting DCEs with many attributes.