Exploring the relationship between two health state classification systems and happiness using a large patient data set

The economic evaluation of health care technologies employs a standard economic approach based on preferences to provide utility information. This paper investigates an alternative approach that uses happiness to weight the health states of two preference-based measures (EQ-5D and SF-6D) in a follow-up of a large hospital patient sample (N=15,184). Logit models relating the health state classifications of these two measures to happiness suggests a different weighting across dimensions to that from preference elicitation techniques such as time trade-off. While mental health (depression and anxiety), vitality and social functioning were found to have a large significant association to a patient’s own happiness assessment, pain was less so and physical health had none. The implications of these results for health policy are discussed

Mapping Functions in Health-Related Quality of Life: Mapping From Two Cancer-Specific Health-Related Quality-of-Life Instruments to EQ-5D-3L.

BACKGROUND: Clinical trials in cancer frequently include cancer-specific measures of health but not preference-based measures such as the EQ-5D that are suitable for economic evaluation. Mapping functions have been developed to predict EQ-5D values from these measures, but there is considerable uncertainty about the most appropriate model to use, and many existing models are poor at predicting EQ-5D values. This study aims to investigate a range of potential models to develop mapping functions from 2 widely used cancer-specific measures (FACT-G and EORTC-QLQ-C30) and to identify the best model. METHODS: Mapping models are fitted to predict EQ-5D-3L values using ordinary least squares (OLS), tobit, 2-part models, splining, and to EQ-5D item-level responses using response mapping from the FACT-G and QLQ-C30. A variety of model specifications are estimated. Model performance and predictive ability are compared. Analysis is based on 530 patients with various cancers for the FACT-G and 771 patients with multiple myeloma, breast cancer, and lung cancer for the QLQ-C30. RESULTS: For FACT-G, OLS models most accurately predict mean EQ-5D values with the best predicting model using FACT-G items with similar results using tobit. Response mapping has low predictive ability. In contrast, for the QLQ-C30, response mapping has the most accurate predictions using QLQ-C30 dimensions. The QLQ-C30 has better predicted EQ-5D values across the range of possible values; however, few respondents in the FACT-G data set have low EQ-5D values, which reduces the accuracy at the severe end. CONCLUSIONS: OLS and tobit mapping functions perform well for both instruments. Response mapping gives the best model predictions for QLQ-C30. The generalizability of the FACT-G mapping function is limited to populations in moderate to good health

What is the evidence for the performance of generic preference-based measures? A systematic overview of reviews

OBJECTIVE: To assess the evidence on the validity and responsiveness of five commonly used preference-based instruments, the EQ-5D, SF-6D, HUI3, 15D and AQoL, by undertaking a review of reviews. METHODS: Four databases were investigated using a strategy refined through a highly sensitive filter for systematic reviews. References were screened and a search for grey literature was performed. Identified citations were scrutinized against pre-defined eligibility criteria and data were extracted using a customized extraction template. Evidence on known group validity, convergent validity and responsiveness was extracted and reviewed by narrative synthesis. Quality of the included reviews was assessed using a modified version of the AMSTAR checklist. RESULTS: Thirty reviews were included, sixteen of which were of excellent or good quality. The body of evidence, covering more than 180 studies, was heavily skewed towards EQ-5D, with significantly fewer studies investigating HUI3 and SF-6D, and very few the 15D and AQoL. There was also lack of head-to-head comparisons between GPBMs and the tests reported by the reviews were often weak. Where there was evidence, EQ-5D, SF-6D, HUI3, 15D and AQoL seemed generally valid and responsive instruments, although not for all conditions. Evidence was not consistently reported across reviews. CONCLUSIONS: Although generally valid, EQ-5D, SF-6D and HUI3 suffer from some problems and perform inconsistently in some populations. The lack of head-to-head comparisons and the poor reporting impedes the comparative assessment of the performance of GPBMs. This highlights the need for large comparative studies designed to test instruments' performance

An empirical comparison of well-being measures used in the UK

A number of different, yet related, measures of subjective well-being (SWB) and health are used across government departments. Under its Measuring National Well-being Programme, the Office of National Statistics (ONS) has adopted the use of the short Warwick Edinburgh Mental Well-being Scale (SWEMWBS) and the General Health Quest ionnaire (GHQ-12) which is a mental health screening measure, as well as four summary subjective (personal) well-being questions which ask about life satisfaction, happiness and anxiety yesterday, and worthwhileness (the ONS-4). I n addition to the measures used within the ONS framework, the National Institute for Health and Care Excellence (NICE) currently preferthe EQ-5D, a measure of health-related quality of life (HRQoL), in the assessment of medical technologies and public health interventions, while social care guidance includes measures of capability and need, the Investigating Choice Experiments Capability Measures for Older people/Adults(ICECAP-A and ICECAP-O) and the Adult Social Care Outcomes Toolkit (ASCOT). There is limited evidence on how these measures relate to each other, which causes difficulty in the comparison of results across datasets and evaluations containing different measures as well as for informing decisions across sectors. Given that these measures are used to inform policy making throughout Government, it is important to better understand how these measures compare. The Department of Health has asked the Policy Research Unit in Economic Evaluation of Health and Care Interventions (EEPRU) to undertake a conceptual and empirical comparison of these six commonly used measures of health and well-being: SWEMWBS, GHQ-12, ONS-4, ICECAP-A, ASCOT and EQ-5D. This report summarises psychometric analysis including factor analysis which sought to compare the ONS- 4, the SWEMWBS/WEMWBS, the GHQ-12, the ICECAP-A or ICECAP- O, ASCOT, the EQ-5D and the SF-6D. The report also takes into consideration additional measures of SWB found within the datasets to shed further light on these comparisons and the concepts behind the measures

A conceptual comparison of well-being measures used in the UK

There is significantpolitical interest in the UK in measuring subjective well- being (SWB) and the possibility of incorporating such measures into policy, including health policy. A number of different, yet related, measures of well-being and health are used across government departments. This includes four summary subjective (personal) well -being questions which ask about life satisfaction, happiness yesterday, anxiety yesterday and worthwhileness adopted by the Office of National Statistics (ONS) under its Measuring National Well-being Programme(referred to here as the ONS-4). They have also adopted the use of the short Warwick Edinburgh Mental Well-being Scale (S- WEMWBS) and the General Health Questionnaire (GHQ-12) which is a mental health screening measure that has been used in well-being measurement. In addition to the measures used within the ONS framework, the National Institute for Health and Care Excellence (NICE) currently rely upon the EQ-5D, a measure of health- related quality of life (HRQoL), in the assessment of medical technologies and public health interventions while social care guidance includes measures of capability and need, ICECAP-A and Adult Social Care Outcomes Toolki

Sensitivity and responsiveness of the EQ-5D-3L in patients with uncontrolled focal seizures: an analysis of Phase III trials of adjunctive brivaracetam.

PURPOSE: Preference-based measures are required to measure the impact of interventions for cost-effectiveness analysis. This study assessed the psychometric performance of the EQ-5D-3L in adults with uncontrolled focal (partial-onset) seizures. METHODS: Data from three Phase III studies of an antiepileptic drug (adjunctive brivaracetam; n = 1095) were used. Analysis included correlations between EQ-5D-3L and Quality of Life in Epilepsy Inventory (QOLIE-31P) and seizure frequency. Known group validity was based on ability of the EQ-5D-3L to discriminate between baseline QOLIE-31P total scores, seizure type and number of antiepileptic drugs using effect sizes (ES). Responsiveness assessed proportions reporting highest or lowest scores, overall change using standardized response means (SRM) and change by responder and clinician/patient evaluation groups using ES. RESULTS: Correlations were weak to moderate (ρ = 0.2-0.4) between EQ-5D-3L dimensions and QOLIE-31P subscales, apart from medication effects (ρ < 0.1); seizure frequency was not associated with either measure. Known group analysis had small ES. A quarter (24.9%) of patients had a baseline EQ-5D-3L utility score of 1 (full health) but lower average QOLIE-31P scores. SRMs were small (<0.1) in EQ-5D-3L compared with 0.1-0.4 for QOLIE-31P subscales. Results across the studies were mixed for responder status and clinician/patient evaluation of improvement for EQ-5D-3L. CONCLUSIONS: EQ-5D-3L had weak-to-moderate correlations with QOLIE-31P and varied with QOLIE-31P severity groups, but showed less responsiveness than QOLIE-31P. Given this lack of sensitivity, EQ-5D-3L may not be appropriate for measuring the impact of interventions in cost-effectiveness analysis in this population and disease-specific preference-based measures may be more appropriate

Estimating informal care inputs associated with EQ-5D for use in economic evaluation.

OBJECTIVES: This paper estimates informal care need using the health of the patient. The results can be used to predict changes in informal care associated with changes in the health of the patient measured using EQ-5D. METHODS: Data was used from a prospective survey of inpatients containing 59,512 complete responses across 44,494 individuals. The number of days a friend or relative has needed to provide care or help with normal activities in the last 6 weeks was estimated using the health of the patient measured by EQ-5D, ICD chapter and other health and sociodemographic data. A variety of different regression models were estimated that are appropriate for the distribution of the informal care dependent variable, which has large spikes at 0 (zero informal care) and 42 days (informal care every day). RESULTS: The preferred model that most accurately predicts the distribution of the data is the zero-inflated negative binomial with variable inflation. The results indicate that improving the health of the patient reduces informal care need. The relationship between ICD chapter and informal care need is not as clear. CONCLUSIONS: The preferred zero-inflated negative binomial with variable inflation model can be used to predict changes in informal care associated with changes in the health of the patient measured using EQ-5D and these results can be applied to existing datasets to inform economic evaluation. Limitations include recall bias and response bias of the informal care data, and restrictions of the dataset to exclude some patient groups

Examining productivity losses associated with health related quality of life using patient and general population data

The work described in this report was commissioned by the Department of Health to inform its work on Value-Based-Pricing (VBP), which is due to replace the current Pharmaceutical Pricing Regulation Scheme (PPS) in January 2014 for pricing medicines in the UK. VBP will include additional payments to interventions that are deemed to provide benefit that is of greater social value instead of the current narrow focus on outcomes relevant to the NHS and Personal Social Services (PSS). This requires taking into account wider societal benefits of medicines beyond the health of the patient including productivity. The objective of the analyses was to provide a model to predict productivity losses associated with paid work that were representative of all patients that are likely to be seen in the NHS

Systematic review of the effect of a one-day versus seven-day recall duration on Patient Reported Outcome Measures (PROMs)

Background There is ongoing uncertainty around the most suitable recall period for patient-reported outcome measures (PROMs). Method This systematic review integrates quantitative and qualitative literature across health, economics, and psychology to explore the effect of a one-day (or ‘24-h’) versus seven-day (or ‘one week’) recall period. The following databases were searched from database inception to 30 November 2021: MEDLINE, EMBASE, PsycINFO, Web of Science, EconLit, CINAHL Complete, Cochrane Library, and Sociological Abstracts. Studies were included that compared a one-day (or ‘24-h’) versus seven-day (or weekly) recall period condition on patient-reported scores for PROM and Health-Related Quality-of-Life (HRQoL) instrument scores in adult populations (aged 18 and above) or combined paediatric and adult populations with a majority of respondents aged over 18 years. Studies were excluded if they assessed health behaviours only, used ecological momentary assessment to derive an index of daily recall, or incorporated clinician reports of patient symptoms. We extracted results relevant to six domains with generic health relevance: physical functioning, pain, cognition, psychosocial wellbeing, sleep-related symptoms and aggregated disease-specific signs and symptoms. Quantitative studies compared weekly recall scores with the mean or maximum score over the last seven days or with the same-day recall score. Results Overall, across the 24 quantitative studies identified, 158 unique results were identified. Symptoms tended to be reported as more severe and HRQoL lower when assessed with a weekly recall than a one-day recall. A narrative synthesis of 33 qualitative studies integrated patient perspectives on the suitability of a one-day versus seven-day recall period for assessing health state or quality of life. Participants had mixed preferences, some noted the accuracy of recall for the one-day period but others preferred the seven-day recall for conditions characterised by high symptom variability, or where PROMs concepts required integration of infrequent experiences or functioning over time. Conclusion This review identified a clear trend toward higher symptom scores and worse quality of life being reported for a seven-day compared to a one-day recall. The review also identified anomalies in this pattern for some wellbeing items and a need for further research on positively framed items. A better understanding of the impact of using different recall periods within PROMs and HRQoL instruments will help contextualise future comparisons between instruments