Valuing health-related quality of life: systematic variation in health perception.

BACKGROUND: Population-based value sets are widely used to transform health states into utilities, but may deviate from actual patient experience. Whether this occurs in a systematic way can be analyzed, in a first step, for respondents who do not report problems on the five domains of the EQ-5D-5L instrument in population studies. METHODS: EQ-5D-5L results from three annual cross-sectional surveys (2012, 2013, and 2014) were filtered for participants who reported being problem-free. Continuous visual analog scale (VAS) scores, ranging from 0 (worst imaginable health) to 100 (best imaginable health) were then used to measure their actual health perception and to compare results with the proposed EQ-5D-5L value. A multiple linear regression model was used to identify possible risk factors for low VAS scores. RESULTS: Some 3739 (61.5%) participants reported being problem-free. Their mean age was 41.1 years and mean VAS score was 91.9. Age and BMI were significantly associated with lower VAS scores. Age groups from 50 years onwards reported VAS means of 90.0 and below. Female gender and low education also had small but significant negative effects on patient experience. The presence of BMI class III as well as diabetes had the greatest negative effect on VAS results (- 9.0 and - 8.4) and reached the range of minimally important differences. Heart disease (- 6.2) and musculoskeletal disease (- 3.4) also had strong negative effects. The 25th percentile of VAS scores in our sample was 90.0, and the 50th percentile was 95.0. CONCLUSIONS: For some groups in population studies, especially older people with high BMI and those affected by specific diseases, no problems on all five domains of the EQ-5D-5L fails to reflect the respondents' health perception as measured by the VAS.

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.

Assessment of the Swedish EQ-5D experience-based value sets in a total hip replacement population.

BACKGROUND: All patients undergoing elective total hip replacement (THR) in Sweden are asked to complete a survey, including the EQ-5D. Thus far, EQ-5D values have been presented using the UK TTO value set based on hypothetical values. Shift to the use of the recently introduced Swedish experience-based value set, derived from a representative Swedish population, is an appealing alternative. PURPOSE: To investigate how accurate the Swedish experience-based VAS value set predicts observed EQ VAS values and to compare correlations between Swedish and UK value sets including two provisional value sets derived from the THR population. METHODS: Pre- and one-year postoperative data from 56,062 THR patients from the Swedish Hip Arthroplasty Register were used. Agreement between the observed and the predicted EQ VAS values was assessed with correlation. Based on pre- and postoperative data, we constructed two provisional VAS value sets. RESULTS: Correlations between observed and calculated values using the Swedish VAS value set were moderate (r = 0.46) in preoperative data and high (r = 0.72) in postoperative data. Correlations between UK and register-based value sets were constantly lower compared to Swedish value sets. Register-based values and Swedish values were highly correlated. CONCLUSIONS: The Swedish value sets are more accurate in terms of representation of the Swedish THR patients than the currently used UK TTO value set. We find it feasible to use the experience-based Swedish value sets for further presentation of EQ-5D values in the Swedish THR population.

Toward Real-World Reproducibility: Verifying Value Sets for Clinical Research.

Standardized operational definitions are an important tool to improve reproducibility of research using secondary real-world healthcare data. This approach was leveraged for studies evaluating the effectiveness of AZD7442 as COVID-19 pre-exposure prophylaxis across multiple healthcare systems. Value sets were defined, grouped, and mapped. Results of this exercise were reviewed and recorded. Value sets were updated to reflect findings.

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.

Determining prescriptions in electronic healthcare record data: methods for development of standardized, reproducible drug codelists.

Objective: To develop a standardizable, reproducible method for creating drug codelists that incorporates clinical expertise and is adaptable to other studies and databases. Materials and Methods: We developed methods to generate drug codelists and tested this using the Clinical Practice Research Datalink (CPRD) Aurum database, accounting for missing data in the database. We generated codelists for: (1) cardiovascular disease and (2) inhaled Chronic Obstructive Pulmonary Disease (COPD) therapies, applying them to a sample cohort of 335 931 COPD patients. We compared searching all drug dictionary variables (A) against searching only (B) chemical or (C) ontological variables. Results: In Search A, we identified 165 150 patients prescribed cardiovascular drugs (49.2% of cohort), and 317 963 prescribed COPD inhalers (94.7% of cohort). Evaluating output per search strategy, Search C missed numerous prescriptions, including vasodilator anti-hypertensives (A and B:19 696 prescriptions; C:1145) and SAMA inhalers (A and B:35 310; C:564). Discussion: We recommend the full search (A) for comprehensiveness. There are special considerations when generating adaptable and generalizable drug codelists, including fluctuating status, cohort-specific drug indications, underlying hierarchical ontology, and statistical analyses. Conclusions: Methods must have end-to-end clinical input, and be standardizable, reproducible, and understandable to all researchers across data contexts.

Clinical decision support malfunctions related to medication routes: a case series.

OBJECTIVE: To identify common medication route-related causes of clinical decision support (CDS) malfunctions and best practices for avoiding them. MATERIALS AND METHODS: Case series of medication route-related CDS malfunctions from diverse healthcare provider organizations. RESULTS: Nine cases were identified and described, including both false-positive and false-negative alert scenarios. A common cause was the inclusion of nonsystemically available medication routes in value sets (eg, eye drops, ear drops, or topical preparations) when only systemically available routes were appropriate. DISCUSSION: These value set errors are common, occur across healthcare provider organizations and electronic health record (EHR) systems, affect many different types of medications, and can impact the accuracy of CDS interventions. New knowledge management tools and processes for auditing existing value sets and supporting the creation of new value sets can mitigate many of these issues. Furthermore, value set issues can adversely affect other aspects of the EHR, such as quality reporting and population health management. CONCLUSION: Value set issues related to medication routes are widespread and can lead to CDS malfunctions. Organizations should make appropriate investments in knowledge management tools and strategies, such as those outlined in our recommendations.

Concordance among Swedish, German, Danish, and UK EQ-5D-3L Value Sets: Analyses of Patient-Reported Outcomes in the Swedish Hip Arthroplasty Register.

Background: Application of different value sets to health-related quality of life (HRQoL) measured with the EQ-5D-3L may lead to different results due to differences in methods, perspectives, and countries used. Focusing on concordance, this study aimed at understanding the implications of applying EQ-5D-3L value sets from Sweden, Germany, Denmark, and the UK to evaluate HRQoL of patients undergoing total hip replacement (THR) in Sweden before and after surgery. Methods: We performed a longitudinal study of patients in the Swedish Hip Arthroplasty Register from preoperative stage to 1-year follow-up (n = 73,523) using data collected from 2008 to 2016. Eight EQ-5D-3L value sets from the four countries were compared based on a valuation method (visual analogue scale (VAS) or time trade-off (TTO)), perspective (experience-based or hypothetical), and country. Concordance among the value sets with patient-reported EQ VAS score was also assessed. Longitudinal changes in EQ-5D-3L index over the 1-year follow-up were compared across value sets by method, perspective, and country. Results: Value sets based on the same method and perspective showed higher concordance in EQ-5D-3L index at both measurement time points than other comparisons. In the comparisons by perspective, VAS value sets showed higher concordance than TTO value sets. The Swedish VAS and the Danish TTO value sets showed the highest levels of concordance with patient-reported EQ VAS scores. Generally, value sets based on the same method and perspective had the smallest mean differences between changes in EQ-5D-3L indices from preoperative to 1-year postoperative follow-up. Conclusion: Among THR patients value sets based on the same method and perspective, a direct transfer of results across countries could be meaningful. In cases of differences in methods and perspectives among value sets, transfer of value sets across settings would have to consider conversion through crosswalk.

A new tool for creating personal and social EQ-5D-5L value sets, including valuing 'dead'.

The EuroQol Group's health descriptive systems, the EQ-5D-3L and its successor introduced in 2009, the EQ-5D-5L, are widely used worldwide for valuing health-related quality of life for cost-utility analysis and patient-reported health outcome measures. A new online tool for creating personal and social EQ-5D-5L value sets was recently developed and trialled in New Zealand (NZ). The tool, which includes extensive checks of the quality of participants' data, implements the PAPRIKA method - a novel type of adaptive discrete choice experiment in the present context - and a binary search algorithm to identify any health states worse than dead. After development and testing, the tool was distributed in an online survey in February and March 2018 to a representative sample of NZ adults (N = 5112), whose personal value sets were created. The tool's extensive data quality checks resulted in a 'high-quality' sub-sample of 2468 participants whose personal value sets were, in effect, averaged to create a social value set for NZ. These results overall as well as feedback from participants indicates that the new valuation tool is feasible and acceptable to participants, enabling valuation data to be relatively easily and cheaply collected. The tool could also be used in other countries, tested against other methods for creating EQ-5D-5L value sets, applied in personalised medicine and adapted to create value sets for other health descriptive systems.

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets.

BACKGROUND: Defining clinical phenotypes from electronic health record (EHR)-derived data proves crucial for clinical decision support, population health endeavors, and translational research. EHR diagnoses now commonly draw from a finely grained clinical terminology-either native SNOMED CT or a vendor-supplied terminology mapped to SNOMED CT concepts as the standard for EHR interoperability. Accordingly, electronic clinical quality measures (eCQMs) increasingly define clinical phenotypes with SNOMED CT value sets. The work of creating and maintaining list-based value sets proves daunting, as does insuring that their contents accurately represent the clinically intended condition. OBJECTIVE: The goal of the research was to compare an intensional (concept hierarchy-based) versus extensional (list-based) value set approach to defining clinical phenotypes using SNOMED CT-encoded data from EHRs by evaluating value set conciseness, time to create, and completeness. METHODS: Starting from published Centers for Medicare and Medicaid Services (CMS) high-priority eCQMs, we selected 10 clinical conditions referenced by those eCQMs. For each, the published SNOMED CT list-based (extensional) value set was downloaded from the Value Set Authority Center (VSAC). Ten corresponding SNOMED CT hierarchy-based intensional value sets for the same conditions were identified within our EHR. From each hierarchy-based intensional value set, an exactly equivalent full extensional value set was derived enumerating all included descendant SNOMED CT concepts. Comparisons were then made between (1) VSAC-downloaded list-based (extensional) value sets, (2) corresponding hierarchy-based intensional value sets for the same conditions, and (3) derived list-based (extensional) value sets exactly equivalent to the hierarchy-based intensional value sets. Value set conciseness was assessed by the number of SNOMED CT concepts needed for definition. Time to construct the value sets for local use was measured. Value set completeness was assessed by comparing contents of the downloaded extensional versus intensional value sets. Two measures of content completeness were made: for individual SNOMED CT concepts and for the mapped diagnosis clinical terms available for selection within the EHR by clinicians. RESULTS: The 10 hierarchy-based intensional value sets proved far simpler and faster to construct than exactly equivalent derived extensional value set lists, requiring a median 3 versus 78 concepts to define and 5 versus 37 minutes to build. The hierarchy-based intensional value sets also proved more complete: in comparison, the 10 downloaded 2018 extensional value sets contained a median of just 35% of the intensional value sets' SNOMED CT concepts and 65% of mapped EHR clinical terms. CONCLUSIONS: In the EHR era, defining conditions preferentially should employ SNOMED CT concept hierarchy-based (intensional) value sets rather than extensional lists. By doing so, clinical guideline and eCQM authors can more readily engage specialists in vetting condition subtypes to include and exclude, and streamline broad EHR implementation of condition-specific decision support promoting guideline adherence for patient benefit.

A Comparison of EQ-5D-3L Index Scores Using Malaysian, Singaporean, Thai, and UK Value Sets in Indonesian Cervical Cancer Patients.

OBJECTIVES: To gain insight into the most suitable foreign value set among Malaysian, Singaporean, Thai, and UK value sets for calculating the EuroQol five-dimensional questionnaire index score (utility) among patients with cervical cancer in Indonesia. METHODS: Data from 87 patients with cervical cancer recruited from a referral hospital in Yogyakarta province, Indonesia, from an earlier study of health-related quality of life were used in this study. The differences among the utility scores derived from the four value sets were determined using the Friedman test. Performance of the psychometric properties of the four value sets versus visual analogue scale (VAS) was assessed. Intraclass correlation coefficients and Bland-Altman plots were used to test the agreement among the utility scores. Spearman ρ correlation coefficients were used to assess convergent validity between utility scores and patients' sociodemographic and clinical characteristics. With respect to known-group validity, the Kruskal-Wallis test was used to examine the differences in utility according to the stages of cancer. RESULTS: There was significant difference among utility scores derived from the four value sets, among which the Malaysian value set yielded higher utility than the other three value sets. Utility obtained from the Malaysian value set had more agreements with VAS than the other value sets versus VAS (intraclass correlation coefficients and Bland-Altman plot tests results). As for the validity, the four value sets showed equivalent psychometric properties as those that resulted from convergent and known-group validity tests. CONCLUSIONS: In the absence of an Indonesian value set, the Malaysian value set was more preferable to be used compared with the other value sets. Further studies on the development of an Indonesian value set need to be conducted.

Parallel Valuation: A Direct Comparison of EQ-5D-3L and EQ-5D-5L Societal Value Sets.

OBJECTIVE: To compare and contrast EQ-5D-5L (5L) and EQ-5D-3L (3L) health state values derived from a common sample. METHODS: Data from the 2017 US EQ-5D valuation study were analyzed. Value sets were estimated with random-effects linear regression based on composite time trade-off (cTTO) valuations for 3L and 5L health states with 2 approaches to model specification: main effects only and additional N3/N45 terms. Properties of the descriptive system and value set characteristics were compared by examining distributions of predicted index scores, ceiling effects, and single-level transition values from adjacent corner health states. Mean transition values were calculated for all predicted 3L and 5L health states and plotted against baseline index scores. RESULTS: A total of 1062 respondents were included in the analysis. The observed mean cTTO values for the worst possible 3L and 5L health states were -0.423 and -0.343, respectively. The range of scale was larger with the 3L, compared to the 5L, for both main effects and N term models. Values for the mildest 5L health states (range, 0.857-0.924) were similar to 11111 for the 3L. Parameter estimates for matched dimension levels differed by <|0.07| except for the most severe level of Mobility. For the main effects model, 3L mean transition values were greater for more severe baseline 3L index scores, whereas 5L mean transition values remained constant irrespective of the baseline index score. CONCLUSIONS: Compared to the 3L, the 5L exhibited a lower ceiling effect and improved measurement properties. There was a larger range of scale for the 3L compared to 5L; however, this difference was driven by differences in preference for the most severe level of problems in Mobility.

Comparison of EQ-5D-5L health state utilities using four country-specific tariffs on a breast cancer patient sample in mainland China.

OBJECTIVE: The objective of this study was to compare the differences in the five-level EuroQol-5 dimensions (EQ-5D-5L) health state utility scores derived from Chinese, Japanese, Korean, and UK tariffs. METHODS: Six hundred and twenty-one breast cancer patients were invited for a face-to-face interview in Qingdao Municipal Hospital, China. EQ-5D-5L was scored using tariffs from China, Japan, Korea, and the UK. The null hypothesis of normal distribution of the EQ-5D-5L utility score was tested by the Shapiro-Wilk test. Nonparametric Friedman test and Wilcoxon signed-rank test were used to determine the difference among the four tariffs. The intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to study the agreement among the four EQ-5D-5L scores. Known-groups validity was studied using a regression framework. RESULTS: There were 608 participants in the final analysis, with a mean ± standard deviation (SD) age of 48.0±9.6 years. EQ-5D-5L utility scores were non-normally distributed. The means (median) ± SD of EQ-5D-5L utilities derived from Chinese, Japanese, Korean, and UK tariffs were 0.828 (0.879) ±0.184, 0.802 (0.823) ±0.164, 0.831 (0.829) ±0.137, and 0.838 (0.866) ±0.154, respectively. Among pairwise comparisons, the difference of median EQ-5D-5L utility scores was only insignificant between Chinese and UK tariffs. Excellent agreements (with ICCs >0.9) were found among the four tariffs albeit the limits of agreement between each pair of tariffs were wide. Known-groups validity was supported. CONCLUSION: Although four country-specific EQ-5D-5L tariffs have shown an overall high level of correlation and agreement, none of them could be regarded as interchangeable. The higher correlation and agreement between Chinese and UK tariffs may be due to the similar functions that were used in the tariff development. In the absence of Chinese-specific tariff, the UK tariff is the second-best option to be applied in the Chinese population. Results of this study further contribute to the explanation of variations among country-specific tariffs.