Preferences For Health States Research Articles

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.

Effect of a Patient Decision Aid on Preferences for Colorectal Cancer Screening Among Older Adults

Guidelines recommend individualized decision-making for colorectal cancer (CRC) screening among adults aged 76 to 84 years, a process that includes a consideration of health state and patient preference. To determine whether a targeted patient decision aid would align older adults' screening preference with their potential to benefit from CRC screening. This is a prespecified secondary analysis from a randomized clinical trial. Participants aged 70 to 84 years who were not up to date with screening and had an appointment within 6 weeks were purposively sampled by health state (poor, intermediate, or good) at 14 community-based primary care practices and block randomized to receive the intervention or control. Patients were recruited from March 1, 2012, to February 28, 2015, and these secondary analyses were performed from January 15 to March 1, 2022. Patient decision aid targeted to age and sex. The primary outcome of this analysis was patient preference for CRC screening. The a priori hypothesis was that the decision aid (intervention) group would reduce the proportion preferring screening among those in poor and intermediate health compared with the control group. Among the 424 participants, the mean (SD) age was 76.8 (4.2) years; 248 (58.5%) of participants were women; and 333 (78.5%) were White. The proportion preferring screening in the intervention group was less than in the control group for those in the intermediate health state (34 of 76 [44.7%] vs 40 of 73 [54.8%]; absolute difference, -10.1% [95% CI, -26.0% to 5.9%]) and in the poor health state (24 of 62 [38.7%] vs 33 of 61 [54.1%]; absolute difference, -15.4% [95% CI, -32.8% to 2.0%]). These differences were not statistically significant. The proportion of those in good health who preferred screening was similar between the intervention and control groups (44 of 74 [59.5%] for intervention vs 46 of 75 [61.3%] for control; absolute difference, -1.9% [95% CI, -17.6% to 13.8%]). The findings of this secondary analysis of a clinical trial did not demonstrate statistically significant differences in patient preferences between the health groups. Additional studies that are appropriately powered are needed to determine the effect of the decision aid on the preferences of older patients for CRC screening by health state. ClinicalTrials.gov Identifier: NCT01575990.

PD56 Conceptual Issues In The Valuation Of Health States In Children

IntroductionAssessing the cost utility of health technologies for pediatric patients requires robust utility values for child health states, but the methods for valuing these pediatric health states are much less established than those for valuing adult health states. This is partly because the elicitation of preferences for child health states poses many normative, ethical, and practical challenges.MethodsThis presentation examines the conceptual issues in the valuation of health states in children by addressing the following questions.(i)Normative theories of health state values: What are we attempting to elicit?(ii)Sources of preferences: Whose preferences should we elicit, and from which perspective?(iii)Valuation methodologies: How should we elicit preferences?(iv)Attaching different values to child and adult health: Is a lack of consistency problematic?To answer these questions, we used desk research (non-systematic literature reviews) and findings from a two-part workshop held in April 2021. The workshop included 25 participants with expertise in health economics, health state valuation, child health, health technology assessment (HTA) decision-making, and ethics.ResultsWe identified a lack of consensus on what is being elicited for both adults and children. Many HTA agencies recommend that the public be involved in utility generation exercises, but some criteria for defining who constitutes a member of the public exclude children. Of the many candidate sample types, perspectives, and methodologies, only a few were deemed relevant, acceptable, and feasible for use in the child health context. In addition, there were diverging views on whether it is possible to compare and integrate adult and child value sets with different properties.ConclusionsSeveral questions remain to be answered before the public and other stakeholders can have confidence in child health state valuation protocols. We propose a research agenda, including both empirical and conceptual work, to inform future methodological development and to help HTA agencies make recommendations about how child utility values should be generated.

OP94 Online Elicitation Of Personal Utility Functions (OPUF): A New Tool For Eliciting EQ-5D-5L Value Sets On The Societal-, Group-, Subgroup-, And Individual-Level

IntroductionThe ‘Online elicitation of Personal Utility Functions’ (OPUF) is a new method for valuing health states. It is based on compositional preference elicitation techniques. In contrast to established, decompositional techniques, such as time trade-off or discrete choice experiment (DCE), the OPUF approach does not require hundreds or thousands of respondents, but allows estimating utility functions for small (patient) groups and even on the individual level. The objective of this study was to generate and compare EQ-5D-5L value sets on the societal-, group-, subgroup-, and individual-level.MethodsA demonstration version of the EQ-5D-5L OPUF Tool is available at: https://eq5d5l.me. It broadly consists of three valuation steps: dimension weighting, level rating, and anchoring. Responses were combined on the individual level to construct personal utility functions. Every respondent also completed three conventional DCEs. Preferences were aggregated across individuals to estimate a societal and various group-level preference functions. We then assessed the heterogeneity of preferences between groups using descriptive statistics and k-means cluster analysis.ResultsA representative sample (n = 1,000) of the United Kingdom (UK) population was recruited through the prolific online platform. On average, it took participants about 7 minutes to complete the survey. Data of 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. The derived utility functions predicted respondents’ choices in DCE with an accuracy of 78 percent. On the societal level, the predicted values for the EQ-5D-5L health states ranged from -0.376 to 1. Health state preference varied greatly between groups. This was largely due to differences in the anchoring, while there was near consensus on the relative importance of the five EQ-5D dimensions between groups. Demographic characteristics explained only a small proportion of the variability.ConclusionsUsing the OPUF approach, we were not only able to estimate a new EQ-5D-5L value set for the UK, but also to examine the underlying individual preferences in an unprecedented level of detail.

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.

Disability weights for castration-resistant prostate cancer: an empirical investigation.

Health state valuation and diagnostic-therapeutic pathways at the junction between non-metastatic and metastatic castration-resistant prostate cancer (CRPC) are not well documented. We aimed at: (i) estimating the disability weights (DWs) for health states across a continuum of disease from asymptomatic non-metastatic (nmCRPC) to symptomatic metastatic state (mCRPC); (ii) mapping the diagnostic-therapeutic pathway of nmCRPC in Italy. Structured qualitative interviews were performed with clinical experts to gather information on nmCRPC clinical pathway. An online survey was administered to clinical experts to estimate DWs for four CRPC health states defined from interviews and literature review (i.e., nmCRPC, asymptomatic mCRPC, symptomatic mCRPC, mCRPC in progression during or after chemotherapy). Clinicians' preferences for health states were elicited using the Person-Trade-Off (PTO) and Visual Analogue Scale (VAS) methods. DWs associated with each health state, from 0 (best imaginable health state) and 1 (worst imaginable health state), were estimated. We found that the management of nmCRPC is heterogeneous across Italian regions and hospitals, especially with respect to diagnostic imaging techniques. DWs for PTO ranged from 0.415 (95% confidence interval [CI] 0.208-0.623) in nmCRPC to 0.740 (95% CI 0.560-0.920) in mCRPC, in progression during or after chemotherapy. DWs for VAS ranged between 0.246 (95% CI 0.131-0.361) in nmCRPC to 0.689 (95% CI 0.583-0.795) in mCRPC, in progression during or after chemotherapy. Estimated DWs suggest that delaying transition to a metastatic state might ease the disease burden at both patient and societal levels.

An EQ-5D-Y-3L Value Set for Belgium.

In Belgium, a value set for children and adolescents for a generic health-related quality-of-life measure is not available. To inform drug pricing and make resource allocation decisions for children and adolescents, national tax-payers' preferences for youth health states should be known. We aimed to obtain a value set for EQ-5D-Y-3L in Belgium, following the international youth valuation protocol for data collection. Composite Time Trade-Off interviews were conducted in a sample of 200 adults, either face to face or via video conferencing. Another sample of 1000 adults completed an online discrete choice experiment survey. All adults were asked to take the perspective of a 10-year-old child for both methods. Both samples were representative for Belgium in terms of age, sex and region. A latent class analysis was selected to obtain the relative importance of the five dimensions and their levels based on the discrete choice experiment data, which were anchored with the composite Time Trade-Off censored value for the worst health state (33333). Preferences from Belgian adults revealed a mean censored value for 33333 for children and adolescents of -0.475. All the estimated coefficients of the modelwith 4 latent classes were statistically significant and showed higher disutility as severity levels increase. The most important health dimension was pain/discomfort, followed by feeling sad/worried/unhappy. This study presents the Belgian EQ-5D-Y-3L value set, which will be included in the Belgian pharmacoeconomic guidelines. The value set enables the calculation of quality-adjusted life-years in children and adolescents, allowing a cost-effectiveness evaluation of health technologies and their youth-specific price setting.

Do they just know more, or do they also have different preferences? An exploratory analysis of the effects of self-reporting serious health problems on health state valuation

BackgroundHealth state valuation is often conducted by people valuing either only their own health state (experience-based valuation) or several stylised states (hypothetical valuation). The approach used can affect the elicited values, but it is not clear whether this is caused by different understandings of the states (an “information mechanism”) and/or by different opinions of the states (a “preference mechanism”). Justifying privileging the valuations of those with the relevant health state experience solely because they are better informed is insufficient when their opinions differ. This study proposes a new framework to examine the effect of having health problems on health state valuation by distinguishing “within-dimensional” effects (which can be due to better information or due to differences in opinion) and “cross-dimensional” effects (which must be due to differences in opinion). MethodsSecondary data from the UK that valued EQ-5D-5L using Discrete Choice Experiments with duration (DCETTO) are remodelled controlling for whether a respondent self-reports serious (viz., severe or extreme) problems in “pain or discomfort” (PD) or “anxiety or depression” (AD). The main analysis uses respondents who have serious PD or serious AD alongside matched respondents who do not, and assumes constant proportional time trade-off. ResultsSelf-reporting serious PD or serious AD problems has no within-dimensional effect on health state preferences. However, self-reporting serious AD problems has negative cross-dimensional effects on the utility of having any problem in PD, which suggests that the preference mechanism is present. A similar pattern holds when all available (unmatched) data are used and when constant proportional time trade-off is relaxed. ConclusionsFindings consistent with the preference mechanism indicate that those with serious health problems may have different opinions on the value of health states compared to the rest of the population, which has normative implications for the debate on which values to use.