Good Days and Bad Days:Measuring Health-Related Quality of Life in People With Epilepsy

Objectives: Cost-effectiveness analyses typically require measurement of health-related quality of life (HRQoL) to estimate quality-adjusted life-years. Challenges with measuring HRQoL arise in the context of episodic conditions if patients are less likely—or even unable—to complete surveys when having disease symptoms. This article explored whether HRQoL measured at regular time intervals adequately reflects the HRQoL of people with epilepsy (PWE). Methods: Follow-up data from the Epilepsy Support Dog Evaluation study on the (cost-)effectiveness of seizure dogs were used in which HRQoL is measured in 25 PWE with the EQ-5D at baseline and every 3 months thereafter. Seizure count is recorded daily using a seizure diary. Regression models were employed to explore whether PWE were more likely to complete the HRQoL survey on a good day (ie, when seizures are absent or low in frequency compared with other days) and to provide an estimate of the impact of reporting HRQoL on a good day on EQ-5D utility scores. Results: A total of 111 HRQoL measurements were included in the analyses. Regression analyses indicated that the day of reporting HRQoL was associated with a lower seizure count (P&lt;.05) and that a lower seizure count was associated with a higher EQ-5D utility score (P&lt;.05). Conclusions: When HRQoL is measured at regular time intervals, PWE seem more likely to complete these surveys on good days. Consequently, HRQoL might be overestimated in this population. This could lead to underestimation of the effectiveness of treatment and to biased estimates of cost-effectiveness.</p

Is “end of life” a special case? Connecting Q with survey methods to measure societal support for views on the value of life-extending treatments

Preference elicitation studies reporting societal views on the relative value of end-of-life treatments have produced equivocal results. This paper presents an alternative method, combining Q methodology and survey techniques (Q2S) to determine the distribution of 3 viewpoints on the relative value of end-of-life treatments identified in a previous, published, phase of this work. These were Viewpoint 1, “A population perspective: value for money, no special cases”; Viewpoint 2, “Life is precious: valuing life-extension and patient choice”; and Viewpoint 3, “Valuing wider benefits and opportunity cost: the quality of life and death.”. A Q2S survey of 4,902 respondents across the United Kingdom measured agreement with these viewpoints; 37% most agreed with Viewpoint 1, 49% with Viewpoint 2, and 9% with Viewpoint 3. Regression analysis showed associations of viewpoints with gender, level of education, religion, voting preferences, and satisfaction with the NHS. The Q2S approach provides a promising means to investigate how in-depth views and opinions are represented in the wider populati

Are life-extending treatments for terminal illnesses a special case? Exploring choices and societal viewpoints

Criteria used by the National Institute for Health and Care Excellence (NICE) to assess life-extending, end-of-life (EoL) treatments imply that health gains from such treatments are valued more than other health gains. Despite claims that the policy is supported by societal values, evidence from preference elicitation studies is mixed and in-depth research has shown there are different societal viewpoints. Few studies elicit preferences for policies directly or combine different approaches to understand preferences.Survey questions were designed to investigate support for NICE EoL guidance at national and regional levels. These ‘Decision Rule’ and ‘Treatment Choice’ questions were administered to an online sample of 1496 UK respondents in May 2014. The same respondents answered questions designed to elicit their agreement with three viewpoints (previously identified and described) in relation to provision of EoL treatments for terminally ill patients. We report the findings of these choice questions and examine how they relate to each other and respondents' viewpoints.The Decision Rule questions described three policies: DA – a standard ‘value for money’ test, applied to all health technologies; DB – giving special consideration to all treatments for terminal illnesses; and DC – giving special consideration to specific categories of treatments for terminal illnesses e.g. life extension (as in NICE EoL guidance) or those that improve quality-of-life (QoL). Three Treatment Choices were presented: TA – improving QoL for patients with a non-terminal illness; TB – extending life for EoL patients; and TC – improving QoL at the EoL.DC received most support (45%) with most respondents giving special consideration to EoL only when treatments improved QoL. The most commonly preferred treatment choices were TA (51%) and TC (43%). Overall, this study challenges claims about public support for NICE's EoL guidance and the focus on life extension at EoL and substantiates existing evidence of plurality in societal values

The impact of losses in income due to ill health: does the EQ-5D reflect lost earnings?

Two key questions in the context of UK health policy are: do the published preference indices for EQ-5D reflect the impact of lost earnings? Are we currently implicitly including indirect costs in our analyses? It is crucial to investigate whether or not individuals take into account any possible impact of lost income in health state valuation exercises. If respondents do consider income effects, and these considerations change valuations, then these effects would need to be excluded both under the current NICE reference case, or where productivity costs are included in the numerator to avoid double counting. This study adapts the study design used to generate population value sets for EQ-5D, as first used in the Measurement and Valuation of Health (MVH) Study, and carries out valuations of hypothetical EQ-5D states using Time Trade Off (TTO) exercises through an online survey administered in the Netherlands. Furthermore, this study uses a number of different TTO questions to explore the impact of losses in income on the valuation of hypothetical health states, and to determine the relationship between income and health.EQ-5D; time trade-off; health-related loss of income

The monetary value of informal care: obtaining pure time valuations using a Discrete Choice Experiment

Background Interventions in health care often not only have an efect on patients, but also on their informal caregivers. Caregiving can have a profound impact on the health and wellbeing of carers. Ignoring these spillovers in economic evaluations risks labelling interventions mistakenly as cost-efective, at the expense of informal caregivers. Objective This paper investigates willingness-to-accept (WTA) values for an hour of informal care, corrected for positive and negative impacts of informal care, to facilitate the inclusion of informal care hours on the cost side of economic evaluations without double-counting spillover efects. Methods A discrete choice experiment (DCE) was conducted among a representative sample of the adult population in the Netherlands (n=552) in September 2011. An experimental design minimizing the D-error was used to construct choice sets with two unlabelled alternatives with the attributes ‘hours caregiving’, ‘monetary compensation for caregiving’ and seven impacts of caregiving. To operationalize the random utility model, we used a panel mixed multinomial logit (MMNL) parameter model. For calculation of WTA, we used both population-level parameters and individual-level parameters. Results The mean WTA for an additional hour of informal care, corrected for positive and negative impacts of informal care, was €14.57. The signs of the coefcients were all in the expected directions. Conclusions This study reports a preference-based monetary value for informal care, corrected for other impacts. This valuation facilitates the inclusion of informal care hours on the cost side in economic evaluations without double-counting any spillover efects included on the efects side

What Constitutes Well-being? Five Views Among Adult People from the Netherlands on what is Important for a Good Life

Well-being has gained interest as object of study in the social sciences and as an outcome measure for policy evaluation. However, little agreement exists with respect to the substantive meaning of well-being, the dimensions of well-being that should be considered in a multi-dimensional approach, and the variety of well-being conceptions people have for their own lives. This study explored conceptions of “a good life for you” among 1,477 adult people from the Netherlands by means of Q-methodology, based on a theoretical framework synthesizing the main theories of well-being. We find five distinct views on what people consider to be a good life for themselves: “Health and feeling well”, “Hearth and home”, “Freedom and autonomy”, “Social relations and purpose” and “Individualism and independence”. While there is strong agreement with respect to the importance of feeling both physically and mentally well, the views diverge considerably regarding aspects such as social relations, autonomy, spirituality, and material welfare. Associations between viewpoints and respondent characteristics had face validity. The findings of this study have significant implications for the development of measures of well-being and policies aimed to improve population well-being. Further research is required into the prevalence of these views on well-being in the population, their relation to respondent characteristics and into differences in views over time and between countries with different socio-economic, political and cultural environments.</p

Welfarism vs. extra-welfarism

'Extra-welfarism' has received some attention in health economics, yet there is little consensus on what distinguishes it from more conventional 'welfarist economics'. In this paper, we seek to identify the characteristics of each in order to make a systematic comparison of the ways in which they evaluate alternative social states. The focus, though this is not intended to be exclusive, is on health. Specifically, we highlight four areas in which the two schools differ: (i) the outcomes considered relevant in an evaluation; (ii) the sources of valuation of the relevant outcomes; (iii) the basis of weighting of relevant outcomes and (iv) interpersonal comparisons. We conclude that these differences are substantive. (C) 2007 Elsevier B.V. All rights reserved