Health State Values Research Articles

Cost-benefit analysis: just a step in the HIA process

Abstract The economic analysis within Health Impact Assessments (HIA) is a critical component in informing public policy decisions by assessing the financial implications of health outcomes associated with the different intervention options. Health metrics play a role defining the cost-effectiveness and societal value associated with the interventions. These metrics, quantifying the health impacts, include quality-adjusted life years (QALYs), years of life lost (YLLs) or disability-adjusted life years (DALYs). On another level, such metrics need to be translated into cost-effectiveness and societal value in which other methods play a role, such as the value of statistical life (VSL) or the value of a life year (VOLY). While VSL quantifies the value individuals place on reducing mortality risk, VOLY evaluates the value attributed to extending life expectancy. On another hand, uncertainties related to economic valuation pose challenges to the accuracy and reliability of cost estimates within HIA. These come from several factors, including data quality, methodological differences across studies, and subjective judgments involved in valuing health states. In fact, estimating the economic value of a prevented death involves multifaceted considerations and important assumptions. Additionally, assigning monetary values to non-fatal health outcomes, such as disability or reduced quality of life, involves subjective assessments and value judgments. By selecting appropriate metrics, considering diverse data sources, and addressing methodological steps and uncertainties, HIA practitioners can improve the utility of economic assessments, facilitating evidence-based decision-making in public health policy and resource allocation. This work was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia,I.P., within CINTESIS, R&D Unit (reference UIDP/4255/2020).

Deriving the PedsUtil health state classification system to measure health utilities for pediatric populations based on the PedsQL: a confirmatory factor analysis.

An important methodological challenge in conducting pediatric economic evaluations is estimating the preference-based health-related quality of life (HRQoL) of children. Current methods are highly variable and there is no single instrument available to value HRQoL consistently across multiple pediatric age groups. The Pediatric Quality of Life Inventory (PedsQL) is a non-preference-based generic HRQoL instrument validated for children 2-18 years, but it cannot be directly used in economic evaluations. The aim of this study was to establish the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis, which is the first step of deriving a preference-based measure of HRQoL based on the PedsQL. Four competing dimension structures of the PedsUtil health state classification system were developed based on published literature and expert opinion. Using data from the Longitudinal Study of Australian Children (LSAC) (n = 45,207), the 4 dimension structures were evaluated using the robust weighted least squares estimation method. The analyses were stratified by 2-year age intervals (from 2 to 17 years) to reflect the study design of the LSAC, as well as special healthcare needs status of the child. Model fit was evaluated by examining standardized factor loadings and various fit indices including the comparative fit index (CFI), Tucker-Lewis Index (TLI), and the root mean square error of approximation (RMSEA). Modification indices and residual correlations were examined to re-specify the models to improve model fit when necessary. The findings supported a 7-dimension structure (i.e., Physical Functioning, Pain, Fatigue, Emotional Functioning, Social Functioning, School Functioning, and School Absence) of the PedsUtil health state classification system. The 7-dimension model exhibited adequate fit across subgroups with CFI values that ranged from 0.929 to 0.954, TLI values from 0.916 to 0.946, and RMSEA values from 0.058 to 0.102. This study established the core dimension structure of the PedsUtil health state classification system using confirmatory factor analysis. The 7-dimension structure was found to be applicable across diverse pediatric populations. Research is currently ongoing to select the most representative item within each dimension of the PedsUtil health state classification system and valuation surveys will be fielded to estimate the PedsUtil scoring system.

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.

Comparison of four approaches in eliciting health state utilities with SF-6Dv2.

To empirically compare four preference elicitation approaches, the discrete choice experiment with time (DCETTO), the Best-Worst Scaling with time (BWSTTO), DCETTO with BWSTTO (DCEBWS), and the Standard Gamble (SG) method, in valuing health states using the SF-6Dv2. A representative sample of the general population in Quebec, Canada, completed 6 SG tasks or 13 DCEBWS (i.e., 10 DCETTO followed by 3 BWSTTO). Choice tasks were designed with the SF-6Dv2. Several models were used to estimate SG data, and the conditional logit model was used for the DCE or BWS data. The performance of SG models was assessed using prediction accuracy (mean absolute error [MAE]), goodness of fit using Bayesian information criterion (BIC),t-test, Jarque-Bera (JB) test, Ljung-Box (LB) test, the logical consistency of the parameters, and significance levels. Comparison between approaches was conducted using acceptability (self-reported difficulty and quality levels in answering, and completion time), consistency (monotonicity of model coefficients), accuracy (standard errors), dimensions coefficient magnitude, correlation between the value sets estimated, and the range of estimated values. The variance scale factor was computed to assess individuals' consistency in their choices for DCE and BWS approaches. Out of 828 people who completed SG and 1208 for DCEBWS tasks, a total of 724 participants for SG and 1153 for DCE tasks were included for analysis. Although no significant difference was observed in self-reported difficulties and qualities in answers among approaches, the SG had the longest completion time and excluded participants in SG were more prone to report difficulties in answering. The range of standard errors of the SG was the narrowest (0.012 to 0.015), followed by BWSTTO (0.023 to 0.035), DCEBWS (0.028 to 0.050), and DCETTO (0.028 to 0.052). The highest number of insignificant and illogical parameters was for BWSTTO. Pain dimension was the most important across dimensions in all approaches. The correlation between SG and DCEBWS utility values was the strongest (0.928), followed by the SG and BWSTTO values (0.889), and the SG and DCETTO (0.849). The range of utility values generated by SG tended to be shorter (-0.143 to 1) than those generated by the other three methods, whereas BWSTTO (-0.505 to 1) range values were shorter than DCETTO (-1.063 to 1) and DCEBWS (-0.637 to 1). The variance scale factor suggests that respondents had almost similar level of certainty or confidence in both DCE and BWS responses. The SG had the narrowest value set, the lowest completion rates, the longest completion time, the best prediction accuracy, and produced an unexpected sign for one level. The BWSTTO had a narrower value set, lower completion time, higher parameter inconsistency, and higher insignificant levels compared to DCETTO and DCEBWS. The results of DCEBWS were more similar to SG in number of insignificant and illogical parameters, and correlation.

How Does the New Australian EQ-5D-5L Value Set Impact Utility Scores? Analysis of Data from the Australian Orthopaedic Association National Joint Replacement Registry.

With advances in health state valuation methods, new value sets may be developed for some countries. Quantifying the impact of moving between existing and new value sets is critical for guiding decisions around utility score interpretation, reporting and comparison with published scores. The aim of this study is to examine, using large-scale national registry data, how the new Australian EQ-5D-5L value set impacts utility scores for patients undergoing joint replacement. Data from the Australian Orthopaedic Association National Joint Replacement Registry were used for this analysis. All primary total hip (THR), knee (TKR), and shoulder replacement (TSR) procedures between 2018 and 2022 with pre-operative and 6-month post-operative EQ-5D-5L data were included. Utility scores were generated using the 2013 and 2023 Australian value sets ('previous' and 'new' value sets, respectively) and analysed descriptively for each joint replacement cohort. Agreement between the two utility score sets was evaluated using concordance correlation coefficients and Bland-Altman plots. EQ-5D-5L data were available for 17,576 THR, 23,010 TKR, and 1667 TSR procedures. The new value set produced a lowest possible EQ-5D-5L utility score of -0.30 (compared with -0.68 previously) and fewer patients had 'worse-than-dead' quality of life (score < 0.00) before surgery. Mean pre-operative scores were 0.21 (THR), 0.19 (TKR), and 0.17 (TSR) units higher with the new value set, and mean post-operative scores were 0.11-0.14 units higher. The new value set resulted in smaller effect sizes for the THR (1.08 versus 1.23) and TKR cohorts (0.86 versus 0.92). There was moderate-to-good overall agreement (coefficients: 0.70-0.80), but concordance varied by time point. Although acceptable agreement was evident, the new Australian value set produces less extreme negative utility scores and markedly higher group-level scores. Transition to reporting new EQ-5D-5L utility scores will require accompanying explanation to signal measurement modifications rather than better quality of life.

Analyzing quality of life among people with opioid use disorder from the National Institute on Drug Abuse Data Share initiative: implications for decision making

PurposeWe aimed to estimate health state utility values (HSUVs) for the key health states found in opioid use disorder (OUD) cost-effectiveness models in the published literature.MethodsData obtained from six trials representing 1,777 individuals with OUD. We implemented mapping algorithms to harmonize data from different measures of quality of life (the SF-12 Versions 1 and 2 and the EQ-5D-3 L). We performed a regression analysis to quantify the relationship between HSUVs and the following variables: days of extra-medical opioid use in the past 30 days, injecting behaviors, treatment with medications for OUD, HIV status, and age. A secondary analysis explored the impact of opioid withdrawal symptoms.ResultsThere were statistically significant reductions in HSUVs associated with extra-medical opioid use (-0.002 (95% CI [-0.003,-0.0001]) to -0.003 (95% CI [-0.005,-0.002]) per additional day of heroin or other opiate use, respectively), drug injecting compared to not injecting (-0.043 (95% CI [-0.079,-0.006])), HIV-positive diagnosis compared to no diagnosis (-0.074 (95% CI [-0.143,-0.005])), and age (-0.001 per year (95% CI [-0.003,-0.0002])). Parameters associated with medications for OUD treatment were not statistically significant after controlling for extra-medical opioid use (0.0131 (95% CI [-0.0479,0.0769])), in line with prior studies. The secondary analysis revealed that withdrawal symptoms are a fundamental driver of HSUVs, with predictions of 0.817 (95% CI [0.768, 0.858]), 0.705 (95% CI [0.607, 0.786]), and 0.367 (95% CI [0.180, 0.575]) for moderate, severe, and worst level of symptoms, respectively.ConclusionWe observed HSUVs for OUD that were higher than those from previous studies that had been conducted without input from people living with the condition.

Estimating Australian Population Utilities for Inherited Retinal Disease Using Time Trade-Off.

Inherited retinal disease (IRD) causes progressive loss of visual function, degenerating towards complete blindness. Economic evaluation of gene therapies for rare forms of genetic IRDs have had to rely on health-related quality of life (HR-QoL) estimates from other diseases because there is limited data available for such a rare condition. This study aimed to estimate Australian societal-based utility values for IRD health states that can be used in cost-utility analyses (CUA) using a time trade-off (TTO) protocol adapted from a UK study. The EuroQol Valuation Technology (EQVT) protocol composite TTO (cTTO) framework was followed, which includes worse-than-death (WTD) states and quality control (QC) measures. Preferences were collected from a general population sample of 110 Australian adult participants. Five health state vignettes from the UK study which had been validated with patients and clinicians were presented randomly to participants during videoconferencing (VC) interviews with one of four interviewers. Technical and protocol feasibility were assessed in a pilot of 10 interviews. QC measures were used to monitor interviewers' performance during the study. One participant withdrew consent. The final analysis was conducted on 109 respondents (including 4 non-traders). The average time to complete the interview was 44.2 minutes (SD 8.7). Participants reported mean visual analogue scale (VAS) scores between 63.15 for 'moderate impairment' and 17.98 for 'hand motion' to 'no light perception'. Mean health state utilities (HSU) varied between 0.76 (SD 0.26) in 'moderate impairment', and 0.20 (SD 0.58) in 'hand motion' to 'no light perception'. Of all HSU evaluations, 14% were considered WTD which most commonly occurred in the most severe visually impaired health state. This study provides valuable information on HSUs across a range of IRD health states from the Australian general population perspective. The utilities obtained in this study can be used as inputs into CUA of IRD therapies.

A novel approach for health state valuation: Multiple bounded dichotomous choice compared to the traditional standard gamble

Objectiveto assess the feasibility of a new stated preference approach, the multiple bounded dichotomous choice (MBDC), designed to generate value sets for preference-based measurement of health-related quality of life. MethodsMBDC and standard gamble (SG) tasks were completed to derive SF-6Dv2 value sets from a sample of the general population in Quebec, Canada. Participants were randomized between the two approaches: 6 health states were evaluated in SG and 11 health states in MBDC. Several models were used to estimate data in each approach, and the preferred models were chosen by using mean absolute error (MAE), logical consistency of parameters, and significance levels. Results of MBDC were compared with SG in terms of acceptability (self-reported difficulty and quality levels in answering, and completion time), consistency (monotonicity of model coefficients), accuracy (standard errors), dimensions coefficient magnitude, correlation between the value sets estimated, and the range of estimated values. The intra-class correlation coefficient (ICC) was computed to assess value sets' consistency. ResultsOut of 655 individuals who completed MBDC tasks and 828 who completed SG tasks, a total of 585 participants for MBDC and 714 for SG tasks were included for analysis. The preferred models for both approaches were GLS Tobit. No significant difference was observed in self-reported difficulties and qualities in answers among approaches, but MBDC had less excluded participants and was less prone to report difficulties in answering. Additionally, completion time in the MBDC group was significantly lower (99.80 vs 68.12 s). Most standard errors in the MBDC were lower than those in SG, and the number of non-significant parameters was also lower. The range of utility values generated by MBDC tended to be wider (−0.372 to 1) than those generated by the SG (−0.137 to 1) and the number of worse-than-dead states in MBDC (0.91%) was higher than for SG (0.08%). The Pain dimension was identified as the most significant, while the Vitality dimension showed the lowest significant decrement. Both approaches exhibited a tendency to overestimate severe health state values and underestimate better health state values. The correlation and ICC between the two value sets were 0.937 and 0.983, respectively. ConclusionBased on empirical evidence, it can be inferred that the MBDC method is not only feasible but also holds the potential to generate meaningful and well-informed preference data from respondents. This approach can be used to derive a value set for preference-based instrument.

Proxy Preferences and the Values of Children's Health States.

To assign values to the health states of children, some health economists have suggested relying on the 'proxy' preferences among the health states of children expressed by a random sample of the adult population. These preferences have been elicited in several ways, with respondents sometimes asked to express their (adult) preferences among the health states of children, and sometimes asked to imagine themselves as children and to express what they think their preferences would be. This essay discusses three grounds for eliciting the preferences of a random sample of adults that have been suggested as ways to assign values to the health states in the EQ-5D-Y, and criticizes the first two: (1) the evidential ground: the preferences of the population sample are good evidence of how good or bad the health states of children are; (2) the 'taxpayer' ground: the adult population has the authority to assign values to health states, therefore their preferences are determinative; and (3) the pragmatic grounds: surveying is straightforward and shifts the responsibility from health economists to the population. I argue that instead of surveying a random sample of the population, health economists should rely on deliberative groups that include older children, experts on children's health and development, as well as members of the population at large. These groups should engage with the reasons that lie behind preferences among health states.

Valuation of Multi-Dimensional Health States With a Bolt-On: Is There a Shortcut?

ObjectivesTo use the EQ-5D questionnaire with bolt-on dimensions in economic evaluation studies, new value sets are needed. In this study, we explored the feasibility of a new approach called the scaling factor model, which estimates bolt-on value sets using estimated EQ-5D dimensional weights. MethodsWe designed a 2-arm study, inviting university students to value health states with and without bolt-on items using the composite time trade-off method. We selected 25 health states from an orthogonal array and added the 5 mildest EQ-5D states in the design. In arm 1, EQ-5D without self-care and standard EQ-5D states were valued, and in arm 2, standard EQ-5D states and EQ-5D with vision were valued. By arm, we compared the mean observed values of health states with and without bolt-on item. Next, by arm, we estimated value sets for the EQ-5D with bolt-on states using both standard model and scaling factor model. Model performances were compared in terms of prediction accuracy and correlation with likelihood-based mean values. ResultsAdding a five-level bolt-on to EQ-5D resulted in statistically lower values. This effect was consistent across 2 arms and bolt-on items. The scaling factor models outperformed the standard models in all statistics. ConclusionsThe scaling factor model offers a methodologically viable and low-cost option for producing value sets for EQ-5D supplemented with bolt-on items. Future studies should further test this method using other bolt-on items and more relevant study populations.

Creating an SF-6Dv2 social value set for New Zealand

The SF-6D health descriptive system and its second version published in 2020, the SF-6Dv2, is used worldwide for valuing health-related quality of life (HRQoL) for economic evaluation and measuring patient-reported health outcomes. In this study, a valuation tool was developed and applied to create a social value set, comprising 18,750 health state values, for the SF-6Dv2 for New Zealand (NZ). This tool was adapted and extended from the one used to create a social value set for the EQ-5D-5L, a simpler health descriptive system with fewer dimensions and health states. The tool implements the PAPRIKA method, a type of adaptive discrete choice experiment, and a binary search algorithm to identify health states worse than dead and has extensive data quality controls to ensure the validity and reliability of the social value set derived from participants' personal value sets. The tool, accompanied by a short introductory video designed specifically for the SF-6Dv2, was distributed via an online survey to a large representative sample of adult New Zealanders in June–July 2022. The tool's data quality controls enabled participants who failed to understand or sincerely engage with the valuation tasks to be identified and excluded, resulting in the participants being pared down to a sub-sample of 2985 ‘high-quality’ participants whose personal value sets were averaged for the social value set. These results, including participants' positive feedback, demonstrate the feasibility and acceptability of using the tool to value larger health descriptive systems such as the SF-6Dv2. Having successfully created an SF-6Dv2 social value set for NZ, the valuation tool can be readily applied to other countries, used to generate personal value sets for personalised medicine and adapted to create value sets for other health descriptive systems.

Is anchoring at 'dead' a theoretical requirement for health state valuation?

Values that accompany generic health measures are typically anchored at 1=full health and 0=dead. Some health states may then be considered 'worse than dead' (WTD) and assigned negative values, which causes fundamental measurement problems. In this paper, we challenge the assumption that anchoring values at 'dead=0' is necessary for quality-adjusted life year (QALY) estimation. We summarise the role of 'dead' in health state valuation and consider three critical questions: (i) whether the measurement properties of health state values require 'dead'; (ii) whether 'dead' needs to be valued relative to health states; and (iii) whether values for states WTD are meaningful or useful. We conclude that anchoring 0 at dead is not a requirement of health status measurement or cost-effectiveness analysis. This results from reframing QALYs as the relevant unit of measurement and reframing values as being derived from QALYs rather than the reverse.

Utilities for Complications Associated with Type 2 Diabetes: A Review of the Literature.

Utility values are used in health economic modeling analyses of type 2 diabetes (T2D) to quantify the effect of acute and long-term complications on quality of life (QoL). For accurate modeling projections, it is important that the utility values used are up to date, accurate and representative of the simulated model cohort. A literature review was performed to identify utility values for health states representing acute and chronic T2D-related complications including cardiovascular complications, stroke, renal disease, ophthalmic complications, neuropathy, diabetic foot, amputation and hypoglycemia. Searches were performed using the PubMed, Embase and Cochrane Library databases and limited to articles published since 2010. Supplementary searches were performed to identify data published at congresses in 2019-2023. A total of 54 articles were identified that reported utility values for T2D-related complications. The most frequently used elicitation method/instrument was the EQ-5D (n = 42 studies) followed by the Short Form-6 dimensions (n = 6), time tradeoff (n = 5), the Health Utilities Index Mark 2 or Mark 3 (n = 2), 15D (n = 1), visual analog scale (n = 1) and standard gamble (n = 1). Stroke and amputation were consistently associated with the largest decrements in QoL. There is a lack of published data that distinguishes between severity of several complications including renal disease, retinopathy and neuropathy. Diabetes-related complications can have a profound impact on QoL; therefore, it is important that these are captured accurately and appropriately in health economic models. Recently published utility values for diabetes-related complications that can be used to inform health economic models are summarized here.

Testing “Pits” Time Trade-Off: Can Data Quality be Improved by Removing Death From Valuation of Health States?

ObjectivesComposite time trade-off (cTTO) often exhibits issues such as a value clustering at −1, potentially due to suboptimal valuation task design. We developed a novel time trade-off which uses the “pits” state as an anchor state and enables a unified time trade-off procedure for all health states (referred to as “pTTO”). This study aimed to test the pTTO for valuation of EQ-5D-5L health states. MethodsA total of 120 members of the general public were invited to value 3 pairs of dominant/dominated EQ-5D-5L states using both cTTO and pTTO and the “pits” state using cTTO. We compared the pTTO with cTTO in terms of feasibility (interviewer-rated task-completing difficulty), acceptability (participant-reported task experience), value distribution, logical consistency, and discriminatory ability (using the standardized response mean, an effect size measure, derived from 3 pairwise comparisons of states with dominant/dominated relationship). ResultsThe pTTO demonstrated similar feasibility to cTTO but slightly lower acceptability. The pTTO values exhibited a smoother and more continuous distribution compared with cTTO values. Relative to the cTTO, the pTTO showed higher individual-level logical consistency rate for the pairs comprising severe states (stringent criterion: 53.04% vs 17.39%; less stringent criterion: 82.61% vs 78.26%). The standardized response mean value based on pTTO values were higher than those based on cTTO values for the pair comprising severe states (0.388 vs −0.140). ConclusionsThe pTTO appeared to be feasible and acceptable to value EQ-5D-5L states. The pTTO values were less clustered, more logically consistent, and discriminative compared with the cTTO values for severe health states.

Health-related quality of life in patients with conditions affecting the hand: meta-analysis.

Health state utility values provide the quality component of quality-adjusted life years and are essential for health economic analyses, such as the National Institute for Health and Care Excellence Technology Appraisal. The aims of this systematic review were to: catalogue utility values for health states experienced by patients with hand conditions; provide pooled utility estimates for common hand conditions; and determine how utilities have been estimated. A PRISMA-compliant systematic review and meta-analysis was conducted (registered in PROSPERO, the international prospective register of systematic reviews (CRD42021226098)). Five databases were searched from inception until April 2023 (Embase, MEDLINE, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the Cochrane Central Register of Controlled Trials (CENTRAL)). All studies that reported primary utility values for hand health states in adult patients were eligible for inclusion. Pooled utility estimates were determined across conditions and intervention status using random-effects meta-analysis. A total of 10 254 articles were identified; 57 studies met the full inclusion criteria and reported 363 distinct health state utility values. Health state utility values were estimated using a range of methods; the most common measure was the EQ-5D. Pooled utility estimates for carpal tunnel syndrome and hand osteoarthritis before surgical intervention were 0.69 (95% c.i. 0.66 to 0.73) and 0.63 (95% c.i. 0.60 to 0.67) respectively. Pooled utility estimates for patients with untreated carpal tunnel syndrome and hand osteoarthritis are 11% and 18% lower than age-matched population norms respectively. Hand conditions have a significant detrimental impact on health-related quality of life and this study provides catalogued utility values for use in future economic analyses to support the delivery of value-based hand surgery.

A happiness approach to valuing health states for children

Preference weights are widely used to score generic health states into utility indexes for estimation of quality adjusted life years (QALYs) and to aid health care funding decisions. To date, health state utilities are predominantly derived using stated preference methods based on decision utility. This paper tests an alternative and generates preference weights using experienced utility for children based on the Child Health Utility 9D (CHU9D) descriptive system. We estimate the relative values of the CHU9D health states with regard to experienced utility, where experienced utility is approximated by self-reported happiness. A nationally-representative longitudinal survey was used including 6090 Australian children aged 12–17 years surveyed over 2014–2018. The derived weights were then applied to calculate the utility decrements for a few common child health conditions. We found that the estimated utility decrements are largely similar to those estimated using the published CHU9D Australian adolescent weights based on decision utility, except for pain and depression. A smaller utility decrement for pain and a larger utility decrement for depression were indicated by experienced utility. We contribute to the literature by showing that using experienced utility methods to generate preference weights for health states is possible, and we discuss some important methodological challenges for future studies such as the impracticability of anchoring to ‘dead’ when utilizing experienced utility.

Assessment of health state utilities associated with adult and pediatric acid sphingomyelinase deficiency (ASMD)

IntroductionAcid sphingomyelinase deficiency (ASMD) type B is a rare genetic disorder leading to enlargement of the spleen and liver, pulmonary dysfunction, and other symptoms. Cost-utility analyses are often conducted to quantify the value of new treatments, and these analyses require health state utilities. Therefore, the purpose of this study was to estimate utilities associated with varying levels of severity of adult and pediatric ASMD type B.MethodsSeven adult and seven child health state vignettes describing ASMD were developed based on published literature, clinical trial results, and interviews with clinicians, patients with ASMD, and parents of children with ASMD. The health states were valued in time trade-off interviews with adult general population respondents in the UK.ResultsInterviews were completed with 202 participants (50.0% female; mean age = 41.3 years). The health state representing ASMD without impairment had the highest mean utility for both the adult and child health states (0.92/0.94), and severe ASMD had the lowest mean utility (0.33/0.45). Every child health state had a significantly greater utility than the corresponding adult health state. Differences between adult/child paired states ranged from 0.02 to 0.13. Subgroup analyses explored the impact of parenting status on valuation of child health states.DiscussionGreater severity of ASMD was associated with lower mean utility. Results have implications for valuation of pediatric health states. The resulting utilities may be useful in cost-utility modeling estimating the value of treatment for ASMD.

Systematic methodological review of health state values in glaucoma cost-utility analyses.

Describing the characteristics and sources of health state utility values and reporting practice in the literature of cost-utility analyses facilitates an understanding of the level of the transparency, validity, and generalizability of cost-utility analyses. Improving the quality of reporting will support investigators in describing the incremental value of emerging glaucoma interventions. To describe the state of practice among published glaucoma cost-utility analysis studies, focusing on valuation of health and the quality of reporting. We searched several databases including Medline, CINHAL, Embase, Web of Science, Scopus, Biosis previews, the Health Economic Evaluations Database, and the NHS Economic Evaluation Database (NHS EED). We included full-text, English, published cost-utility analyses of glaucoma interventions with quality-adjusted life years (QALYs) as the primary outcome measure to calculate incremental cost-utility ratios. Excluded studies were non-English language, reviews, editorials, protocols, or other types of economic studies (cost-benefit, cost-minimization, cost-effectiveness). Study characteristics, operational definitions of glaucoma health states and health state utilities were extracted. The original source of the health utility was reviewed to determine the scale of measurement and the source of preference weighting. Items from the Systematic Review of Utilities for Cost-Effectiveness (SpRUCE checklist) were used to assess the reporting and quality of health utilities in glaucoma CUA. 43 CUAs were included, with 11 unique sources of health utilities. A wide range of health utilities for the same Hodapp-Parrish-Anderson glaucoma health states were reported; ocular hypertension (0.84-0.95), mild (0.68-0.94), moderate (0.57-0.92), advanced (0.58-0.88), severe/blind (0.46-0.76), and bilateral blindness (0.26-0.5). Most studies reported the basis for using health utilities (34, 79%) and any assumptions or adjustments applied to the health utilities (22, 51%). Few studies reported a framework for assessing the relevance of health utilities to a decision context (8, 19%). Even fewer (3, 7%) applied a systematic search strategy to identify health utilities and used a structured assessment of quality for inclusion. Overall, reporting has not improved over time. This review describes that few CUAs describe important rationale for using health state utility values. Including additional details on the search, appraisal, selection, and inclusion process of health utility values improves transparency, generalizability and supports the assessment of the validity of study conclusions. Future investigations should aim to use health utilities on the same scale of measurement across health states and consider the source and relevance to the decision context/purpose of conducting that cost-utility study.

Development and Valuation of a Preference-Weighted Measure in Age-Related Macular Degeneration From the Vision Impairment in Low Luminance Questionnaire: A MACUSTAR Report

ObjectivesThis study generates VILL-UI (Vision Impairment in Low Luminance - Utility Index), a preference-weighted measure (PWM) derived from the VILL-33 measure for use in patients with age-related macular degeneration (AMD) and valued to generate United Kingdom and German preference weights. MethodsA PWM consists of a classification system to describe health and utility values for every state described by the classification. The classification was derived using existing data collected as part of the MACUSTAR study, a low-interventional study on AMD, conducted at 20 clinical sites across Europe. Items were selected using psychometric and Rasch analyses, published criteria around PWM suitability, alongside instrument developer views and concept elicitation work that informed VILL-33 development. An online discrete choice experiment (DCE) with duration of the health state was conducted with the United Kingdom and German public. Responses were modeled to generate utility values for all possible health states. ResultsThe classification system has 5 items across the 3 domains of VILL-33: reading and accessing information, mobility and safety, and emotional well-being. The DCE samples (United Kingdom: n = 1004, Germany: n = 1008) are broadly representative and demonstrate good understanding of the tasks. The final DCE analyses produce logically consistent and significant coefficients. ConclusionsThis study enables responses to VILL-33 to be directly used to inform economic evaluation in AMD. The elicitation of preferences from both United Kingdom and Germany enables greater application of VILL-UI for economic evaluation throughout Europe. VILL-UI fills a gap in AMD in which generic preference-weighted measures typically lack sensitivity.

Comparing heuristic valuation processes between health state valuation from child and adult perspectives

ObjectivesHealth state valuation assumes that respondents trade off between all aspects of choice tasks and maximize their utility. Yet, respondents may use heuristic valuation processes, i.e., strategies to simplify or avoid the trade-offs that are core to health state valuation. The objective of this study is to explore if heuristic valuation processes are more prevalent for valuation from a 10-year-old child’s perspective compared to the use of an adult perspective.MethodsWe reused existing data in which EQ-5D health states were valued from adult and child perspectives with composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks. Our analyses focused on comparing completion time and responding patterns across both perspectives. We also explored how reflective of a set of heuristic strategies respondents’ choices were in both perspectives.ResultsWe found no evidence for systematic differences in completion time across perspectives. Generally, we find different responding patterns in child perspectives, e.g., more speeding, dominance violations, and clustering of utilities at 1.0, 0.8, and 0. Very few heuristic strategies provide a coherent explanation for the observed DCE responses.ConclusionOur results provide some, albeit indirect, evidence for differences in heuristic valuation processes between perspectives, although not across all data sources. Potential effects of heuristic valuation processes, such as transfer of responsibility, may be identified through studying responding patterns in cTTO and DCE responses.