Unpaid caring and heath-related quality of life: longitudinal analysis of Understanding Society (the UK Household Longitudinal Survey).

OBJECTIVES: Decision models for economic evaluation are increasingly including health-related quality of life (HRQoL) for informal/unpaid carers, but these estimates often come from poor quality data and typically rely on cross-sectional analysis. We aimed to identify within-person effects using longitudinal analysis of 13 waves of Understanding Society (the UK Household Longitudinal Survey). METHODS: We analysed data for co-resident carer and care-recipient dyads, where the carer reported "looking after or giving special help to" the care-recipient in any of the 13 waves. We used fixed effects models to study the effects of caring for the care-recipient (the "caregiving" effect) using volume of care (hours per week) and continuous duration of caregiving (years); and caring about the care-recipient (the "family" effect) using the care-recipient's HRQoL on the carer's HRQoL. HRQoL was measured using the short-form 6 dimension (SF-6D), calculated from SF-12. RESULTS: We found consistent evidence for the family effect: improving care-recipient's HRQoL by 0.1 would improve carer's HRQoL by approximately 0.012. We also consistently found evidence of a small but statistically significant decrement to carer's HRQoL for each additional year of caring. These findings were robust to scenario analyses. Evidence for the relationship between volume of care and carer's HRQoL was less clear. CONCLUSIONS: We propose that our estimates can be used to populate economic models to predict changes in carers' HRQoL over time and allow disutilities to be estimated separately for the family and caregiving effect.

An International Comparison of EQ-5D-5L and EQ-5D-3L for Use in Cost-Effectiveness Analysis.

OBJECTIVES: To estimate the impact of using EQ5D-5L (5L) compared with EQ5D-3L (3L) in cost-effectiveness analyses in 6 countries with 3L and 5L values: Germany, Japan, Korea, The Netherlands, China, and Spain. METHODS: Eight cost-effectiveness analyses based on clinical studies with 3L provided 11 pairwise comparisons. We estimated cost-effectiveness by applying the appropriate country values for 3L to observed responses. We re-estimated cost-effectiveness for each country by predicting the 5L tariff score for each respondent, for each country, using a previously published mapping method. We compared results in terms of impact on estimated incremental quality-adjusted life-year (QALY) gain and cost-effectiveness ratios. RESULTS: For most countries the impact of moving from 3L to 5L is to lower the incremental QALY gain in the majority of comparisons. The only exception to this was Japan, where 4 out of 11 cases (37%) saw lower QALYs gained when using 5L. The mean and median reductions in health gain, in those case studies where 5L does lead to lower health gain, are largest in The Netherlands (84% mean reduction, 41% median reduction), Germany (68% and 27%), and Spain (30% and 31%). For most countries, those studies where 5L leads to lower health gain see larger reductions than the gains in studies showing the opposite tendency. CONCLUSIONS: Overall, 3L and 5L are not interchangeable in these countries. Differences between results are large, but the direction of change can be unpredictable. These findings should prompt further investigation into the reasons for differences.

Mapping EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS).

PURPOSE: To develop a mapping model to estimate EQ-5D-3L from the Knee Injury and Osteoarthritis Outcome Score (KOOS). METHODS: The responses to EQ-5D-3L and KOOS questionnaires (n = 40,459 observations) were obtained from the Swedish National anterior cruciate ligament (ACL) Register for patients ≥ 18 years with the knee ACL injury. We used linear regression (LR) and beta-mixture (BM) for direct mapping and the generalized ordered probit model for response mapping (RM). We compared the distribution of the original data to the distributions of the data generated using the estimated models. RESULTS: Models with individual KOOS subscales performed better than those with the average of KOOS subscale scores (KOOS5, KOOS4). LR had the poorest performance overall and across the range of disease severity particularly at the extremes of the distribution of severity. Compared with the RM, the BM performed better across the entire range of disease severity except the most severe range (KOOS5 < 25). Moving from the most to the least disease severity was associated with 0.785 gain in the observed EQ-5D-3L. The corresponding value was 0.743, 0.772 and 0.782 for LR, BM and RM, respectively. LR generated simulated EQ-5D-3L values outside the feasible range. The distribution of simulated data generated from the BM model was almost identical to the original data. CONCLUSIONS: We developed mapping models to estimate EQ-5D-3L from KOOS facilitating application of KOOS in cost-utility analyses. The BM showed superior performance for estimating EQ-5D-3L from KOOS. Further validation of the estimated models in different independent samples is warranted.

Catalog of EQ-5D-3L Health-Related Quality-of-Life Scores for 199 Chronic Conditions and Health Risks in Denmark.

Background. Assessments of health-related quality of life (HRQoL) are essential in estimating quality-adjusted life-years. It is sometimes not feasible to collect primary HRQoL data, and reliable secondary sources are necessary. Current "off-the-shelf" HRQoL catalogs are based on older diagnosis classifications and include a limited number of diseases. This article aims to provide 1) a Danish EQ-5D-3L-based HRQoL catalog for 199 nationally representative chronic conditions based on ICD-10 codes and 2) a complementary model-based catalog controlling for age, sex, comorbidities, lifestyle, and health risks. Design. A total of 55,616 respondents from 3 national health survey samples were pooled and combined with 7 national registers containing patient-level information on diagnoses, health care activity, and sociodemographics. EQ-5D-3L data were converted to utility scores using the Danish EQ-5D-3L value set to estimate the mean utility for each chronic disease population. Adjusted limited dependent variable mixture models were estimated and used to provide a regression-based catalog of utilities/disutilities. Results. Diseases with the lowest mean EQ-5D score in the Danish population were systemic sclerosis (M34; score = 0.432), fibromyalgia (M797; score = 0.490), rheumatism (M790; score = 0.515), dementia (F00, G30; score = 0.546), posttraumatic stress syndrome (F431; score = 0.557), and systemic atrophies (G10-G14; score = 0.583. Based on the estimated models, the largest estimated disutilities were cystic fibrosis, cerebral palsy, depression, dorsalgia, sclerosis, and fibromyalgia. Lifestyle factors, including perceived stress, loneliness, and body mass index, were also significantly associated with low HRQoL. Conclusions. This study provides a comprehensive nationally representative catalog and a model-based catalog of EQ-5D-3L-based HRQoL scores for Denmark that can be used to describe aspects of disease burden and allocate resources within health care. Additional Stata programs are also provided to facilitate predictions in other populations. Highlights: A Danish national representative catalog of health-related quality-of-life scores for 199 chronic conditions is presented, which provides population estimates for chronic conditions subgroups that can be used for health economic evaluation.Two separate regression models of EQ-5D-3L utility scores with different sets of control variables are estimated to allow researchers to adjust for differences in the composition of the subgroups and provide a tool that can be used in other settings.Results indicate that health-related quality of life varies across disease groups but is lowest for renal disease, mental and behavioral disorders, benign neoplasms and diseases of the blood, digestive systems, and nervous systems.Health risks and lifestyle factors such as perceived stress, loneliness, and a large body mass index are highly correlated with health-related quality of life, and, in many cases, the correlation is higher than with individual diseases.

Valuing states from multiple measures on the same visual analogue sale: a feasibility study.

Previous methods of empirical mapping involve using regressions on patient or general population self-reported data from datasets involving two or more measures. This approach relies on overlap in the descriptive systems of the measures and assumes it is appropriate to use different measures on the same population, which may not always be the case. This paper presents a feasibility study for a new approach to mapping between preference-based measures (PBM) using general population visual analogue scale (VAS) values as a common yardstick. We use data from a valuation study of 502 members of the UK general population, where, using ranking and VAS tasks, interviewees simultaneously valued health states defined by three of six PBM: EQ-5D (generic), SF-6D (generic), HUI2 (generic for children and adults), AQL-5D (asthma specific), OPUS (social care specific) and ICECAP (capabilities). Regression techniques are used to estimate the relationship between these VAS values and the original value set (i.e. 'tariff'). These results are subsequently used to estimate the relationship between all six PBM to enable 'value-based mapping' between measures. This new method of mapping potentially has a useful role in evidence synthesis and cross programme comparisons in studies using different measures.

Common scale valuations across different preference-based measures: estimation using rank data.

BACKGROUND: Different preference-based measures (PBMs) used to estimate quality-adjusted life years (QALYs) provide different utility values for the same patient. Differences are expected since values have been obtained using different samples, valuation techniques, and descriptive systems. Previous studies have estimated the relationship between pairs of PBMs using patient self-reported data. However, there is a need for an approach capable of generating values directly on a common scale for a range of PBMs using the same sample of general population respondents and valuation technique but keeping the advantages of the different descriptive systems. METHODS: . General public survey data (n = 501) in which respondents ranked health states described using subsets of 6 PBMs were analyzed. We develop a new model based on the mixed logit to overcome 2 key limitations of the standard rank-ordered logit model-namely, the unrealistic choice pattern (independence of irrelevant alternatives) and the independence of repeated observations. RESULTS: . There are substantial differences in the estimated parameters between the 2 models (mean difference 0.07), leading to different orderings across the measures. Estimated values for the best states described by different PBMs are substantially and significantly different using the standard model, unlike our approach, which yields more consistent results. Limitations. Data come from an exploratory study that is relatively small both in sample size and coverage of health states. CONCLUSIONS: . This study develops a new, flexible econometric model specifically designed to reflect appropriately the features of rank data. Results support the view that the standard model is not appropriate in this setting and will yield very different and apparently inconsistent results. PBMs can be compared using a common scale by implementation of this new approach.

Good practice guidelines for the use of statistical regression models in economic evaluations.

Decision-analytic models (DAMs) used to evaluate the cost effectiveness of interventions are pivotal sources of evidence used in economic evaluations. Parameter estimates used in the DAMs are often based on the results of a regression analysis, but there is little guidance relating to these. This study had two objectives. The first was to identify the frequency of use of regression models in economic evaluations, the parameters they inform, and the amount of information reported to describe and support the analyses. The second objective was to provide guidance to improve practice in this area, based on the review. The review concentrated on a random sample of economic evaluations submitted to the UK National Institute for Health and Clinical Excellence (NICE) as part of its technology appraisal process. Based on these findings, recommendations for good practice were drafted, together with a checklist for critiquing reporting standards in this area. Based on the results of this review, statistical regression models are in widespread use in DAMs used to support economic evaluations, yet reporting of basic information, such as the sample size used and measures of uncertainty, is limited. Recommendations were formed about how reporting standards could be improved to better meet the needs of decision makers. These recommendations are summarised in a checklist, which may be used by both those conducting regression analyses and those critiquing them, to identify what should be reported when using the results of a regression analysis within a DAM.

Primary angioplasty versus thrombolysis for acute ST-elevation myocardial infarction: an economic analysis of the National Infarct Angioplasty project.

OBJECTIVE: To estimate the cost-effectiveness of primary angioplasty compared with thrombolysis for acute ST elevation myocardial infarction. Design Cost analysis of UK observational database, incorporated into decision analytical model. METHODS: Patients receiving treatment within a comprehensive angioplasty service were compared with control patients receiving thrombolysis-based care. The treatment costs and delays to treatment of thrombolysis and angioplasty were estimated. These estimates were then incorporated into an existing model of cost-effectiveness that synthesises evidence from 22 randomised trials to estimate health outcomes measured by quality-adjusted life years (QALYs). Main outcome measures Costs from a health service perspective and outcomes measured as quality adjusted. RESULTS: The mean cost of the initial treatment was 3509 pounds for thrombolysis at control sites, 5176 pounds for angioplasty in usual working hours at National Infarct Angioplasty Project sites and an additional 245 pounds if undertaken out of hours. Angioplasty-based care had an incremental cost of 4520 pounds per QALY gained and 0.9 probability of being cost-effective at a threshold of 20,000 pounds per QALY gained. This probability was >0.95 if patients were directly admitted to the cardiac catheter laboratory, 0.75 if admitted via the emergency department or coronary care unit and 0.38 if transferred to the angioplasty centre from another hospital. CONCLUSIONS: Overall, primary angioplasty-based care is highly likely to be cost-effective at an assumed threshold of 20,000 pounds per QALY gained. It is more likely to be cost-effective if patients are admitted directly to the cardiac catheter laboratory rather than via other hospital departments, or if transferred from another hospital.