Challenges in Using Recommended Quality of Life Measures to Assess Fluctuating Health:A Think-Aloud Study to Understand How Recall and Timing of Assessment Influence Patient Responses

BACKGROUND: It can be challenging to measure quality of life to calculate quality-adjusted life-years in recurrent fluctuating health states, as quality of life can constantly change. It is not clear how patients who experience fluctuations complete measures and how assessment timing and recall influence responses. OBJECTIVE: We aimed to understand how patients with fluctuating health complete widely recommended and commonly used measures (EQ-5D-5L, EORTC QLQ-C30 and SF-12) and the extent to which the recall period (‘health today’, ‘past week’ and ‘past 4 weeks’) and timing of assessment influence the way that patients complete these questionnaires. METHODS: Twenty-four adult patients undergoing chemotherapy for urological, gynaecological or bowel cancers in the UK participated in think-aloud interviews, while completing the measures, completed a pictorial task illustrating how quality of life changed during the chemotherapy cycle and took part in semi-structured interviews. Transcripts were analysed using constant comparison. RESULTS: Patients were consistent in describing their quality of life as changing considerably throughout a chemotherapy cycle. The shorter recall period of ‘health today’ does not adequately represent patients’ quality of life because of fluctuations, patients remarked they could give a different answer depending on the timing of assessment, and many struggled to combine the “ups and downs” to answer measures with longer recall (‘past week’ and ‘past 4 weeks’). Across all measures, patients attempted to provide averages, adopt the peak-end rule or focus on the best part of their experience. Patients commonly used more than one approach when completing a given questionnaire as well as across questionnaires. CONCLUSIONS: Patients who experience recurrent fluctuations in health are unable to provide meaningful responses about their quality of life when completing quality-of-life measures due to the recall period and timing of assessment. The use of such responses to calculate health state values in economic evaluations to inform resource allocation decisions in fluctuating conditions must be questioned. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40271-021-00555-7

Development of a supportive care measure for economic evaluation of end-of-life care using qualitative methods

Background: An imperative to assess the economic impact of care at the end of life is emerging in response to national policy developments in a number of settings. Current focus on health benefits in economic evaluation may not appropriately capture benefits of interventions at the end of life. No instruments are available for measuring such benefits for economic evaluation of end-of-life care. Aim: To develop a descriptive system for a measure for use in economic evaluation of end-of-life care. Design: An initial phase of in-depth interviews was conducted to develop conceptual attributes for inclusion in a measure; a second phase of semi-structured repeat interviews with a subsample of informants was carried out to clarify and confirm the final set of attributes and to develop meaningful wording for a measure. Setting/participants: In total, 23 older people from three groups across the dying trajectory: older people (1) within the general population, (2) living in residential care and (3) receiving palliative care. Results: Interviews suggested that the important domains to include within this framework from the perspective of those approaching the end-of-life are choice/having a say in decision-making, love and affection/being with people who care, freedom from physical suffering, freedom from emotional suffering, dignity and self-respect, support, and preparation. A full descriptive system comprising seven questions, each representing one attribute, was developed. Conclusion: Economic evaluation should reflect the broader benefits of end-of-life care. Although the supportive care measure developed here requires validation and valuation, it provides a substantial step forward in appropriate economic evaluation of end-of-life care. </jats:sec

Development of a self-report measure of capability wellbeing for adults: the ICECAP-A

Purpose The benefits of health and social care are not confined to patient health alone and therefore broader measures of wellbeing may be useful for economic evaluation.\ud This paper reports the development of a simple measure of capability wellbeing for adults (ICECAP-A).\ud Methods In-depth, informant-led, interviews to identify the attributes of capability wellbeing were conducted with 36 adults in the UK. Eighteen semi-structured, repeat interviews were carried out to develop a capability-based descriptive system for the measure. Informants were purposively selected to ensure variation in socio-economic status, age, sex, ethnicity and health. Data analysis was carried out inductively and iteratively alongside interviews, and findings were used to shape the questions in later interviews.\ud Results Five over-arching attributes of capability wellbeing were identified for the measure: ‘‘stability’’,‘‘attachment’’, ‘‘achievement’’, ‘‘autonomy’’ and ‘‘enjoyment’’. One item, with four response categories, was developed for each attribute for the ICECAP-A descriptive system.\ud Conclusions The ICECAP-A capability measure represents a departure from traditional health economics outcome measures, by treating health status as an influence over broader attributes of capability wellbeing. Further work is required to value and validate the attributes and test the sensitivity of the ICECAP-A to healthcare interventions

Estimating preferences for a dermatology consultation using Best-Worst Scaling: Comparison of various methods of analysis

Background: Additional insights into patient preferences can be gained by supplementing discrete choice experiments with best-worst choice tasks. However, there are no empirical studies illustrating the relative advantages of the various methods of analysis within a random utility framework. Methods: Multinomial and weighted least squares regression models were estimated for a discrete choice experiment. The discrete choice experiment incorporated a best-worst study and was conducted in a UK NHS dermatology context. Waiting time, expertise of doctor, convenience of attending and perceived thoroughness of care were varied across 16 hypothetical appointments. Sample level preferences were estimated for all models and differences between patient subgroups were investigated using ovariateadjusted multinomial logistic regression. Results: A high level of agreement was observed between results from the paired model (which is theoretically consistent with the 'maxdiff' choice model) and the marginal model (which is only an approximation to it). Adjusting for covariates showed that patients who felt particularly affected by their skin condition during the previous week displayed extreme preference for short/no waiting time and were less concerned about other aspects of the appointment. Higher levels of educational attainment were associated with larger differences in utility between the levels of all attributes, although the attributes per use had the same impact upon choices as those with lower levels of attainment. The study also demonstrated the high levels of agreement between summary analyses using weighted least squares and estimates from multinomial models. Conclusion: Robust policy-relevant information on preferences can be obtained from discrete choice experiments incorporating best-worst questions with relatively small sample sizes. The separation of the effects due to attribute impact from the position of levels on the latent utility scale is not possible using traditional discrete choice experiments. This separation is important because health policies to change the levels of attributes in health care may be very different from those aiming to change the attribute impact per se. The good approximation of summary analyses to the multinomial model is a useful finding, because weighted least squares choice totals give better insights into the choice model and promote greater familiarity with the preference data

Scoring the ICECAP-A capability instrument. Estimation of a UK general population tariff

This paper reports the results of a best–worst scaling (BWS) study to value the Investigating Choice Experiments Capability Measure for Adults (ICECAP-A), a new capability measure among adults, in a UK setting. A main effects plan plus its foldover was used to estimate weights for each of the four levels of all five attributes. The BWS study was administered to 413 randomly sampled individuals, together with sociodemographic and other questions. Scale-adjusted latent class analyses identified two preference and two (variance) scale classes. Ability to characterize preference and scale heterogene-ity was limited, but data quality was good, and the final model exhibited a high pseudo-r-squared. After adjusting for heterogeneity, a population tariff was estimated. This showed that ‘attachment ’ and ‘stability ’ each account for around 22 % of the space, and ‘autonomy’, ‘achievement ’ and ‘enjoyment ’ account for around 18 % each. Across all attributes, greater value was placed on the difference between the lowest levels of capability than between the highest. This tariff will enable ICECAP-A to be used in economic evaluation both within the field of health and across public policy generally. © 2013 The Authors. Health Economics published by John Wiley &amp; Sons Ltd

An investigation of the construct validity of the ICECAP-A capability measure

Abstract Purpose To investigate the construct validity of the ICECAP-A capability wellbeing measure. Methods A face-to-face interview-administered survey was conducted with 418 members of the UK general population, randomly sampled from the Postcode Address File. Pre-specified hypotheses were developed about the expected associations between individuals’ ICECAP-A responses and their socio-economic circumstances, health and freedom. The hypotheses were investigated using statistical tests of association. Results The ICECAP-A responses and scores reflected differences across different health and socioeconomic groups as anticipated, but did not distinguish individuals by the level of local deprivation. Mean ICECAP-A scores reflected individuals’ perceived freedom slightly more closely than did measures of health and happiness. Conclusion This study suggests that the ICECAP-A measure can identify expected differences in capability wellbeing in a general population sample. Further work could establish whether self-reported capabilities exhibit desirable validity and acceptability in sub-groups of the population such as patients, social care recipients and informal carers

Measuring Health Spillovers for Economic Evaluation: A Case Study in Meningitis

The health of carers and others close to the patient will often be relevant to economic evaluation, but it is very rarely considered in practice. This may reflect a lack of understanding of how the spillover effect of illness can be appropriately quantified. In this study we used three different approaches to quantify health spillovers resulting from meningitis. We conducted a survey of 1218 family networks affected by meningitis and used regression modelling to estimate spillover effects. The findings show that meningitis had long-term effects on family members' health, particularly affecting the likelihood of family members reporting anxiety and depression. These effects extended beyond a single close family member. These findings suggest that vaccinating against meningitis will bring significant health benefits not just to those that might have contracted the illness but also to their family networks. In methodological terms, different approaches for quantifying health spillovers provided broadly consistent results. The choice of method will be influenced by the ease of collecting primary data from family members in intervention contexts