Exploring health preference heterogeneity in the UK: Using the online elicitation of personal utility functions approach to construct EQ-5D-5L value functions on societal, group and individual level

A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

The value of health-Empirical issues when estimating the monetary value of a quality-adjusted life year based on well-being data

Decisions on interventions or policy alternatives affecting health can be informed by economic evaluations, like cost-benefit or cost-utility analyses. In this context, there is a need for valid estimates of the monetary equivalent value of health (gains), which are often expressed in € per quality-adjusted life years (QALYs). Obtaining such estimates remains methodologically challenging, with a recent addition to the health economists' toolbox, which is based on well-being data: The well-being valuation approach. Using general population panel data from Germany, we put this approach to the test by investigating several empirical and conceptual challenges, such as the appropriate functional specification of income utility, the choice of health utility tariffs, or the health state dependence of consumption utility. Depending on specification, the bulk of estimated € per QALY values ranged from €20,000-60,000, with certain specifications leading to more considerable deviations, underlining persistent practical challenges when applying the well-being valuation methodology to health and QALYs. Based on our findings, we formulate recommendations for future research and applications.

Acute Complications and Sequelae from Foodborne Infections: Informing Priorities for Cost of Foodborne Illness Estimates

Cost of foodborne illness (CoFI) estimates provide estimates of the overall impact of foodborne illnesses, including hospitalizations, long-term complications, and deaths. CoFI estimates are needed in countries that require cost-benefit analysis as part of the process of adopting new regulations, as is the case in the United States. Monetary estimates of the impact of disease also provide a meaningful way of communicating with the public about the impact of foodborne disease. In 2014, researchers at the U.S. Department of Agriculture, Economic Research Service (ERS), published CoFI estimates for 15 pathogens that account for roughly 95% of illnesses and deaths from the 31 major foodborne pathogens included in the Centers for Disease Control and Prevention (CDC) foodborne disease incidence estimates. ERS is currently updating their estimates to include all 31 known pathogens and unspecific agents included in CDC incidence estimates. CoFI estimates are based on quantitative models of the health outcomes people experience as a result of these illnesses and an assessment of the costs associated with these health outcomes. Research on the incidence of foodborne disease provides a starting point for this disease modeling, but it usually must be supplemented by other additional synthesis of research on acute complications and long-term health outcomes of different foodborne diseases. As part of its current work revising CoFI estimates, ERS convened a workshop attended by leading foodborne disease public health scientists to discuss how changes in scientific research on the incidence and outcomes of foodborne illnesses should inform the next revision of ERS's CoFI estimates. This article presents a summary, based on discussion at this workshop, of the state of scientific research available to inform updated economic modeling of the CoFI in the United States.

Overview, Update, and Lessons Learned From the International EQ-5D-5L Valuation Work: Version 2 of the EQ-5D-5L Valuation Protocol

A standardized 5-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) valuation protocol was first used in national studies in the period 2012 to 2013. A set of problems encountered in this initial wave of valuation studies led to the subsequent refinement of the valuation protocol. To clarify lessons learned and how the protocol was updated when moving from version 1.0 to the current version 2.1 and 2.0, this article will (1) present the challenges faced in EQ-5D-5L valuation since 2012 and how these were resolved and (2) describe in depth a set of new challenges that have become central in currently ongoing research on how EQ-5D-5L health states should be valued and modeled.

Environmental and Socioeconomic Health Inequalities: a Review and an Example of the Industrial Ostrava Region

BACKGROUND AND AIM

According to the World Health Organization (WHO) more than 2 million premature deaths and 7 million of total deaths each year can be attributed to the effects of air pollution. The contribution of air pollution to the health status of population is estimated to be about 20%. Health is largely determined by factors outside the reach of healthcare sector, including low income, unemployment, poor environment, poor education, and substandard housing. The aim of the paper was to review a current knowledge of relationships among air pollution, socioeconomic health inequalities, socio-spatial differentiation, and environmental inequity. The relationships were demonstrated on an example of the Ostrava region. Also basic approaches to health valuation were reviewed.

RESULTS

Social differences are reasons both for health inequalities and spatial patterns of unprivileged area housing. In urban environments with poor air quality there is also a large concentration of low income residents. Less affluent population groups are more often affected by inadequate housing conditions including second-hand smoking and higher environmental burden in their residential neighbourhoods. Environmental injustice is highly correlated with other factors that link poverty with poor health, including inadequate access to medical and preventive care, lack of availability of healthful food, lack of safe play spaces for children, absence of good jobs, crime, and violence.

CONCLUSIONS

The theoretical background and also results of the studies brought evidence that population health is affected by both socioeconomic and environmental inequalities. Air pollution is unevenly distributed in Ostrava and is related to distribution of socially disadvantaged environment and social exclusion as well.

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. © 2015 The Authors. Health Economics published by John Wiley & Sons Ltd.

Learning and satisficing: an analysis of sequence effects in health valuation

OBJECTIVE

To estimate the effect of sequence on response precision and response behavior in health valuation studies.

METHODS

Time trade-off (TTO) and paired comparison responses from six health valuation studies-four US, one Spanish, and one Dutch-were examined (22,225 respondents) to test whether task sequence influences response precision (e.g., rounding), response changes, and median response times. Each study used a computer-based instrument that randomized task sequence among a national sample of adults, age 18 years or older, from the general population.

RESULTS

For both TTO and paired comparisons, median response times decreased with sequence (i.e., learning), but tended to flatten after the first three tasks. Although the paired comparison evidence demonstrated that sequence had no effect on response precision, the frequency of rounded TTO responses (to either 1-year or 5-year units) increased with sequence.

CONCLUSIONS

Based on these results, randomizing or reducing the number of paired comparison tasks does not appear to influence response precision; however, generalizability, practicality, and precautionary considerations remain. Overall, participants learned to respond efficiently within the first three tasks and did not resort to satisficing, but may have rounded their TTO responses.

Sick but satisfied: the impact of life and health satisfaction on choice between health scenarios

Preference elicitation methods require respondents to predict the impact a change in health might have on their future selves. The focus on the change in health is at the possible expense of other experiences of life once in that health state. We analyse personal preferences to a pairwise choice task involving trade-offs between quality and length of life, where satisfaction levels with life or health are introduced in the description of the health states. We find that a health scenario including low levels of satisfaction increases the likelihood of preferring to die sooner in full health, whereas scenarios including high levels of satisfaction increase the likelihood of preferring to live for longer in poor health. The differences highlight the sensitivity of preferences to what is described in health states and therefore show the importance of on-going discussions about precisely what respondents should be asked to consider in preference elicitation studies.

Comorbidity and disease burden in the National Comorbidity Survey Replication (NCS-R)

BACKGROUND

Disease burden estimates rarely consider comorbidity. Using a recently developed methodology for integrating information about comorbidity into disease burden estimates, we examined the comparative burdens of nine mental and 10 chronic physical disorders in the National Comorbidity Survey Replication (NCS-R).

METHODS

Face-to-face interviews in a national household sample (n = 5,692) assessed associations of disorders with scores on a visual analog scale (VAS) of perceived health. Multiple regression analysis with interactions for comorbidity was used to estimate these associations. Simulation was used to estimate incremental disorder-specific effects adjusting for comorbidity.

RESULTS

The majority of respondents (74.9%) reported one or more disorders. Of respondents with disorders, 73.8-98.2% reported having at least one other disorder. The best-fitting model to predict VAS scores included disorder main effects and interactions for number of disorders. Adjustment for comorbidity reduced individual-level disorder-specific burden estimates substantially, but with considerable between-disorder variation (0.07-0.69 ratios of disorder-specific estimates with and without adjustment for comorbidity). Four of the five most burdensome disorders at the individual level were mental disorders based on bivariate analyses (panic/agoraphobia, bipolar disorder, posttraumatic stress disorder, major depression) but only two based on multivariate analyses, adjusting for comorbidity (panic/agoraphobia, major depression). Neurological disorders, chronic pain conditions, and diabetes were the other most burdensome individual-level disorders. Chronic pain conditions, cardiovascular disorders, arthritis, insomnia, and major depression were the most burdensome societal-level disorders.

CONCLUSIONS

Adjustments for comorbidity substantially influence estimates of disease burden, especially those of mental disorders, underlining the importance of including information about comorbidity in studies of mental disorders.