Recommendations for Emerging Good Practice and Future Research in Relation to Family and Caregiver Health Spillovers in Health Economic Evaluations: A Report of the SHEER Task Force.

BACKGROUND: Omission of family and caregiver health spillovers from the economic evaluation of healthcare interventions remains common practice. When reported, a high degree of methodological inconsistency in incorporating spillovers has been observed. AIM: To promote emerging good practice, this paper from the Spillovers in Health Economic Evaluation and Research (SHEER) task force aims to provide guidance on the incorporation of family and caregiver health spillovers in cost-effectiveness and cost-utility analysis. SHEER also seeks to inform the basis for a spillover research agenda and future practice. METHODS: A modified nominal group technique was used to reach consensus on a set of recommendations, representative of the views of participating subject-matter experts. Through the structured discussions of the group, as well as on the basis of evidence identified during a review process, recommendations were proposed and voted upon, with voting being held over two rounds. RESULTS: This report describes 11 consensus recommendations for emerging good practice. SHEER advocates for the incorporation of health spillovers into analyses conducted from a healthcare/health payer perspective, and more generally inclusive perspectives such as a societal perspective. Where possible, spillovers related to displaced/foregone activities should be considered, as should the distributional consequences of inclusion. Time horizons ought to be sufficient to capture all relevant impacts. Currently, the collection of primary spillover data is preferred and clear justification should be provided when using secondary data. Transparency and consistency when reporting on the incorporation of health spillovers are crucial. In addition, given that the evidence base relating to health spillovers remains limited and requires much development, 12 avenues for future research are proposed. CONCLUSIONS: Consideration of health spillovers in economic evaluations has been called for by researchers and policymakers alike. Accordingly, it is hoped that the consensus recommendations of SHEER will motivate more widespread incorporation of health spillovers into analyses. The developing nature of spillover research necessitates that this guidance be viewed as an initial roadmap, rather than a strict checklist. Moreover, there is a need for balance between consistency in approach, where valuable in a decision making context, and variation in application, to reflect differing decision maker perspectives and to support innovation.

Health Utility of Drinkers' Family Members: A Secondary Analysis of a US Population Data Set.

Background. Problematic alcohol use is known to harm individuals surrounding the drinker. This study described the health utility of people who reported having a family member(s) whom they perceived as a "problem drinker."Methods. We conducted a secondary analysis of the US National Epidemiologic Survey of Alcohol and Related Conditions Wave 3 (NESARC-III, 2012-13) data to estimate the independent associations of a family member's problem drinking on the respondent's health utility, also known as health-related quality of life, assessed via the SF-6D. Participants included 29,159 noninstitutionalized adults, of whom 21,808 reported perceiving a family member or members as having a drinking problem at any point in that person's life. Respondent drinking was assessed via self-report and diagnostic interview. We used population-weighted multivariate regression to estimate disutility. Results. After adjusting for the respondent's own alcohol consumption, alcohol use disorder (AUD), family structure, and sociodemographic characteristics, the mean decrement in SF-6D score associated with perceiving a family member as a problem drinker ranged from 0.033 (P < 0.001) for a spouse/partner to 0.023 (P < 0.001) for a grandparent, sibling, aunt, or uncle. The mean decrement in SF-6D score from having AUD oneself was 0.039 (P < 0.001). Conclusions. Perceived problem drinking within one's family is associated with statistically significant losses in health utility, the magnitude of which is dependent on relationship type. The adverse consequences associated with problem drinking in the family may rival having AUD oneself. Implications. Family-oriented approaches to AUD interventions may confer outsize benefits, especially if focused on the spouse or partner. Economic evaluation of alcohol misuse could be made more accurate through the inclusion of family spillover effects. Highlights: Spillover effects from problem drinking in the family vary by relationship type.One's perception of their spouse or child as having a drinking problem is associated with a utility decrement of equal magnitude to having alcohol use disorder oneself.Medical decision makers should consider the outsize effects of family spillovers in treatment decisions in the context of alcohol consumption, particularly among spouses and children of problem drinkers.Economic evaluation should consider how to incorporate family spillover effects from problem drinking in alcohol-related models.

The relative value of carer and patient quality of life: A person trade-off (PTO) study.

Carer quality of life is increasingly considered alongside patient quality of life in economic evaluation. Important questions remain about how to value carer and patient quality of life effects alongside one another. In this study, we estimated the relative social value of two conceptualisations of carer quality of life (health-related and care-related) compared to patient quality of life. Relative valuations were estimated using a person trade-off (PTO) study with 990 representative members of the UK public. Participants chose between hypothetical services that improved the quality of life of carers and patients, iterating to a point of indifference. Overall 84% of participants completing the task were willing to trade patient and carer quality of life effects. Relative to a reference point of 1 for patient health-related quality of life, we estimated a social value of 0.74 for carer health-related quality of life effects and 0.69 for carer care-related quality of life effects. In conclusion, public preferences appear to support the inclusion of carer quality of life effects within economic evaluation. The results provide a means to value different carer quality of life outcomes in economic evaluation, where such values are needed and deemed appropriate.

Intergenerational Decision Making: The Role of Family Relationships in Medical Decision Making.

A symposium held at the 42nd annual Society for Medical Decision Making conference on October 26, 2020, focused on intergenerational decision making. The symposium covered existing research and clinical experiences using formal presentations and moderated discussion and was attended by 43 people. Presentations focused on the roles of pediatric patients in decision making, caregiver decision making for a child with complex medical needs, caregiver involvement in advanced care planning, and the inclusion of spillover effects in economic evaluations. The moderated discussion, summarized in this article, highlighted existing resources and gaps in intergenerational decision making in four areas: decision aids, economic evaluation, participant perspectives, and measures. Intergenerational decision making is an understudied and poorly understood aspect of medical decision making that requires particular attention as our society ages and technological advances provide new innovations for life-sustaining measures across all stages of the lifespan.

Estimating an exchange-rate between care-related and health-related quality of life outcomes for economic evaluation: An application of the wellbeing valuation method.

Quality of life outcomes for family carers and patients may be measured in different ways within the same economic evaluation. We used the wellbeing valuation method to calculate "exchange rates" between care-related outcomes (the Carer Experience Scale and CarerQoL-7D) and health-related (the EQ-5D-5L) outcomes. Data on quality of life outcomes were collected through a postal quality of life survey in the UK. A random effects model was used to estimate carers' wellbeing as a function of their EQ-5D-5L, Carer Experience Scale (or CarerQoL-7D) and a set of control variables. When life satisfaction was used as the measure of wellbeing, a one-point gain in the Carer Experience Scale (0-100 scale) was equivalent (in wellbeing terms) to a 0.014 gain in EQ-5D-5L value; and a one point gain in the CarerQoL-7D (0-100 scale) was equivalent to a 0.033 gain in EQ-5D-5L. The exchange rate values were reduced when capability was used as the measure of wellbeing. The exchange rates estimated in this study offer a means to place carer and patient outcomes, measured via different quality of life instruments, on a common scale, although there are important issues to consider in operationalising the technique.

Family-level impact of genetic testing: integrating health economics and ethical, legal, and social implications.

Tweetable abstract Health economics and ELSI can be better integrated to consider the family impacts of genetic and genomic testing.

The health utility of mild and severe dysphonia.

OBJECTIVES/HYPOTHESIS: The impact of disease states can be measured using health state utilities, which are values that reflect economic preferences for health outcomes. Utilities for dysphonia have not been studied using direct methods. The objective of this project was to establish the baseline health utilities of mild and severe dysphonia from a societal perspective. STUDY DESIGN: Direct utility elicitation survey. METHODS: Four health states (monocular blindness, binocular blindness, mild dysphonia, and severe dysphonia) were evaluated by a convenience sample of adults recruited from the general public with three computer-aided estimation techniques (visual analog scale [VAS], standard gamble [SG], and time trade-off [TTO]). Standardized descriptions and voice recordings from multiple dysphonic patients were employed. Perfect health was defined as a utility of 1, with death 0. Analysis of variance with post hoc pairwise comparison was used to calculate significant differences between health states. RESULTS: Three hundred participants were surveyed, and 225 (75.0%) responses met quality thresholds. Severe dysphonia (VAS = 48.3, SG = 0.810, TTO = 0.798) was valued significantly worse than monocular blindness (VAS = 56.2, SG = 0.834, TTO = 0.839) on the VAS (P < .001) and equivalent on SG and TTO; it was preferred over binocular blindness (VAS = 25.7, SG = 0.631, TTO = 0.622; P < .001) with all methods. Mild dysphonia evaluated favorably with all methods to the other health states (VAS = 78.5, SG = 0.902, TTO = 0.908; P < .001). CONCLUSIONS: Voice disorders may have a measurable impact on utility, with severe dysphonia valued equivalently to monocular blindness. Mild dysphonia has a utility decrement from perfect health. These estimates are critical for quality-of-life assessment and could be used to assess cost-effectiveness of treatments for voice disorders. LEVEL OF EVIDENCE: NA Laryngoscope, 130:1256-1262, 2020.

Spillover Effects on Caregivers' and Family Members' Utility: A Systematic Review of the Literature.

BACKGROUND: A growing body of research has identified health-related quality-of-life effects for caregivers and family members of ill patients (i.e. 'spillover effects'), yet these are rarely considered in cost-effectiveness analyses (CEAs). OBJECTIVE: The objective of this study was to catalog spillover-related health utilities to facilitate their consideration in CEAs. METHODS: We systematically reviewed the medical and economic literatures (MEDLINE, EMBASE, and EconLit, from inception through 3 April 2018) to identify articles that reported preference-based measures of spillover effects. We used keywords for utility measures combined with caregivers, family members, and burden. RESULTS: Of 3695 articles identified, 80 remained after screening: 8 (10%) reported spillover utility per se, as utility or disutility (i.e. utility loss); 25 (30%) reported a comparison group, either population values (n = 9) or matched, non-caregiver/family member or unaffected individuals' utilities (n = 16; 3 reported both spillover and a comparison group); and 50 (63%) reported caregiver/family member utilities only. Alzheimer's disease/dementia was the most commonly studied disease/condition, and the EQ-5D was the most commonly used measurement instrument. CONCLUSIONS: This comprehensive catalog of utilities showcases the spectrum of diseases and conditions for which caregiver and family members' spillover effects have been measured, and the variation in measurement methods used. In general, utilities indicated a loss in quality of life associated with being a caregiver or family member of an ill relative. Most studies reported caregiver/family member utility without any comparator, limiting the ability to infer spillover effects. Nevertheless, these values provide a starting point for considering spillover effects in the context of CEA, opening the door for more comprehensive analyses.

Health utilities and parental quality of life effects for three rare conditions tested in newborns.

BACKGROUND: Measurement of health utilities is required for economic evaluations. Few studies have evaluated health utilities for rare conditions; even fewer have incorporated disutility that may be experienced by caregivers. This study aimed to (1) estimate health utilities for three rare conditions currently recommended for newborn screening at the state or federal level, and (2) estimate the disutility, or spillover, experienced by parents of patients diagnosed with a rare, heritable disorder. METHODS: A stated-preference survey using a time trade-off approach elicited health utilities for Krabbe disease, phenylketonuria, and Pompe disease at varying stages (mild, moderate, severe) and onset of disease symptoms (infancy, childhood, and adulthood). We recruited respondents from a nationally representative community sample (n = 862). Respondents valued disease specific health states in three consecutive question frames: (1) adult health state (> = 18 years of age), (2) child health state (< 18 years of age), and (3) as a parent of a child with a condition (parent spillover state). Corresponding mean utilities were calculated for plausible disease states in adulthood and childhood. Mean disutility was estimated for parental spillover. Predictors of utilities were evaluated using a negative binomial regression model. RESULTS: More severe conditions and infant health states received lower estimated utility and greater estimated disutility among parents. Conditions with the lowest estimated health utilities were severe infantile Pompe disease (0.40, CI: 0.34-0.46) and infantile Krabbe disease (0.37, CI: 0.32-0.43). Disutility was evident for all conditions evaluated (range: 0.07-0.19). CONCLUSIONS: Rare childhood conditions are associated with substantial estimated losses in quality of life. Evidence of disutility among parents further warrants the inclusion of spillover effects in cost-effectiveness analyses. Continued research is needed to assess and measure the effects of childhood disease from a family perspective.

Joint Utility Estimators in Substance Use Disorders.

BACKGROUND: Although co-occurring conditions are common with substance use disorders (SUDs), estimation methods for joint health state utilities have not yet been tested in this context. OBJECTIVES: To compare joint health state utility estimators in SUD to inform economic evaluation. METHODS: We conducted two Internet-based surveys of US adults to collect community perspective standard gamble utilities for SUD and common co-occurring conditions. We evaluated six conditions as they occur individually and four combinations of these as they occur in tandem. We applied joint utility estimators using the six individual conditions' utilities to compare their performance relative to the observed combination states' utilities. We assessed performance with bias (estimated utility minus observed utility) and root mean square error (RMSE). RESULTS: Using 3892 utilities from 1502 respondents, the minimum estimator was statistically unbiased (i.e., the 95% confidence interval included 0) for all combination states that we measured. The maximum estimator was unbiased for two states and the linear index and adjusted decrement estimators were unbiased for one state. The maximum estimator had the smallest RMSE for two combination states (back pain and prescription opioid misuse [0.0004] and injection crack and injection opioid use [0.0007]); the linear index and minimum estimators had the smallest RMSE for one combination state each. The additive and multiplicative estimators had the largest RMSE for all states. CONCLUSIONS: Our results demonstrate the usefulness of the minimum estimator in this context, and confirm the inadequacy of the additive and multiplicative estimators. Further research is needed to extend these results to other SUD states.

Using Best-Worst Scaling to Understand Patient Priorities: A Case Example of Papanicolaou Tests for Homeless Women.

PURPOSE: Best-worst scaling (BWS) is a survey method for assessing individuals' priorities. It identifies the extremes-best and worst items, most and least important factors, biggest and smallest influences-among sets. In this article, we demonstrate an application of BWS in a primary care setting to illustrate its use in identifying patient priorities for services. METHODS: We conducted a BWS survey in 2014 in Boston, Massachusetts, to assess the relative importance of 10 previously identified attributes of Papanicolaou (Pap) testing services among women experiencing homelessness. Women were asked to evaluate 11 sets of 5 attributes of Pap services, and identify which attribute among each set would have the biggest and smallest influence on promoting uptake. We show how frequency analysis can be used to analyze results. RESULTS: In all, 165 women participated, a response rate of 72%. We identified the most and least salient influences on encouraging Pap screening based on their frequency of report among our sample, with possible standardized scores ranging from+1.0 (biggest influence) to -1.0 (smallest influence). Most important was the availability of support for issues beyond health (+0.39), while least important was the availability of accommodations for personal hygiene (-0.27). CONCLUSIONS: BWS quantifies patient priorities in a manner that is transparent and accessible. It is easily comprehendible by patients and relatively easy to administer. Our application illustrates its use in a vulnerable population, showing that factors beyond those typically provided in health care settings are highly important to women in seeking Pap screening. This approach can be applied to other health care services where prioritization is helpful to guide decisions.

Measuring benefits of opioid misuse treatment for economic evaluation: health-related quality of life of opioid-dependent individuals and their spouses as assessed by a sample of the US population.

AIMS: To understand how the general public views the quality of life effects of opioid misuse and opioid use disorder on an individual and his/her spouse, measured in terms used in economic evaluations. DESIGN: Cross-sectional internet survey of a US population-representative respondent panel conducted December 2013-January 2014. SETTING: United States. PARTICIPANTS: A total of 2054 randomly selected adults; 51.1% male (before weighting). MEASUREMENTS: Mean (95% confidence interval) and median health 'utility' for six opioid misuse and treatment outcomes: active injection misuse; active prescription misuse; methadone maintenance therapy at initiation and when stabilized in treatment; and buprenorphine therapy at initiation and when stabilized. Utility is a numerical representation of health-related quality of life used in economic evaluations to 'adjust' estimated survival to include peoples' preferences for health states. Utilities are determined by surveying the general population to estimate the value they assign to particular health states on a scale where 0 = the value of being dead and 1.0 = the value of being in perfect health. Spouse spillover utility is assigned to a spouse of an individual who is in a particular health state. FINDINGS: Mean individual utility ranged from 0.574 [95% confidence interval (CI) = 0.538, 0.611] for active injection opioid misuse to 0.766 for stabilized buprenorphine therapy (95% CI = 0.738, 0.795), with other states in between. Female respondents assigned higher utility to the active prescription misuse and buprenorphine therapy at initiation states than did males (P < 0.05); all other states did not differ by respondent gender. Mean spousal utilities were significantly lower than 1.0 but mostly higher than individual utility, and were similar between male and female respondents. CONCLUSIONS: In the opinion of the US public, injection opioid misuse results in worse health-related quality of life than prescription misuse, and methadone therapy results in worse health-related quality of life than buprenorphine therapy. Spouses are negatively affected by their partner's opioid misuse and early treatment.

Measuring family HRQoL spillover effects using direct health utility assessment.

BACKGROUND: Applications of cost-effectiveness analysis do not typically incorporate effects on caregiver quality of life despite increasing evidence that these effects are measurable. METHODS: Using a national sample of US adults, we conducted 2 cross-sectional surveys during December 2011 and January 2012. One version asked respondents to value their own experience as the family member of a person with a chronic illness (experienced sample), and the other version asked respondents to value hypothetical scenarios describing the experience of having a family member with a chronic illness (community sample). Conditions included Alzheimer's disease/dementia, arthritis, cancer, and depression. Using standard gamble questions, respondents were asked to value the spillover effects of a family member's illness. We used regression analysis to evaluate the disutility (loss in health-related quality of life) of having a family member with a chronic illness by condition and relationship type, controlling for the respondent's own conditions and sociodemographic characteristics. RESULTS: For the experienced sample (n = 1389), regression analyses suggested that greater spillover was associated with certain conditions (arthritis, depression) compared with other conditions (Alzheimer's disease, cancer). For the community sample (n = 1205), regression analyses indicated that lower spillover was associated with condition (cancer) but not the type of relationship with the ill family member (parent, child, spouse). CONCLUSIONS: The effects of illness extend beyond the individual patient to include effects on caregivers of patients, parents of ill children, spouses, and other close family and household members. Cost-effectiveness analyses should consider the inclusion of health-related quality of life spillover effects in addition to caregiving time costs incurred by family members of ill individuals.

Variation in the spillover effects of illness on parents, spouses, and children of the chronically ill.

BACKGROUND: Given the broad scope of the spillover effects of illness, it is important to characterize the variability in these outcomes to identify relationship types in which secondary impacts of illness are particularly important to include in health economic evaluations. PURPOSE: To examine heterogeneity in spillover effects of chronic conditions on family members by type of familial relationship with patient. METHODS: Adults (aged ≥18 years) and adolescents (aged 13-17 years) who had a parent, spouse, or child in their household with a chronic condition (Alzheimer's disease/dementia, arthritis, cancer, or depression) were recruited from a US national panel to participate in an on-line survey. Respondents were asked to rate the spillover effect of their family member's illness on their own health on a 0-100 scale, with lower scores indicating greater spillover. Regression analysis was used to evaluate the association between rating scale scores and relationship with an ill family member (ill parent, child, or spouse) for each illness separately, controlling for caregiving responsibility and the health status of the ill family member. RESULTS: 1,267 adults and 102 adolescents met inclusion criteria. In adjusted analyses, having a sick child was significantly (p < 0.05) associated with lower rating scale scores compared with having a spouse with the same condition (cancer: -24.2; depression -9.7). Having a non-elderly or elderly adult parent with a condition, compared with a spouse, was significantly associated with lower rating scale scores for arthritis (-3.8) and depression (-5.3), but not for Alzheimer's disease/dementia or cancer. CONCLUSIONS: The impact of illness on family members, measured with a rating scale, varies by relationship type for certain illnesses. Having a child with cancer, a parent with arthritis, or either with depression, is significantly associated with greater spillover, compared with having a spouse with one of these conditions.

How illness affects family members: a qualitative interview survey.

OBJECTIVE: Spillover effects of illness on family members can be substantial. The objective of this study was to identify the domains of family members' health and well-being that are affected when a relative has a chronic health condition. METHODS: Semi-structured telephone interviews were conducted in February 2012 with 49 individuals whose relatives had any of five chronic health conditions (arthritis, cancer, Alzheimer's disease/dementia, cerebral palsy, and depression), purposively sampled to include different relationships with the ill relative (parent, child, spouse). Subjects were queried on whether and how having an ill relative affected their health and well-being; they were also asked about their caregiving responsibilities and the relative's health. Interview data were analyzed using thematic analysis. RESULTS: Family members in our sample reported experiencing psychological and non-health effects from having an ill relative, and secondarily somatic effects. Effects on emotional health were most commonly reported as psychological spillover; non-health effects frequently included changes in daily activities and provision of caregiving. Spouses of patients reported the broadest range of spillover domains affected and adolescents of ill parents the fewest. Family members reported experiencing effects that were perceived as both positive and negative. CONCLUSIONS: Spillover of illness onto family members encompasses a wide range of domains of health and well-being, extending beyond those included in many existing health-related quality of life measures. Outcomes measurement efforts should be expanded to adequately capture these health and well-being outcomes for analysis, to ensure that the benefits of interventions are accurately estimated and conclusions are valid.

Disutility of illness for caregivers and families: a systematic review of the literature.

BACKGROUND: Caring for an ill or disabled family member imposes a well-documented burden on the caregiver. The benefits of a health intervention may be underestimated if "spillover" effects on family members are not captured, resulting in inaccurate conclusions of economic evaluations. OBJECTIVE: To provide an estimate of, and to summarize measurement approaches for, the spillover disutility of illness on family members, relatives, and caregivers, through a systematic review of the literature. METHODS: The medical (PubMED), psychology (PsycINFO), and economics (EconLit) literatures were searched from inception through February 2012 for published studies measuring spillover disutility of illness on family members and caregivers. Inclusion criteria were (1) studies using preference-based measures of health-related quality of life, and (2) studies reporting spillover disutility, or (3) studies reporting data from which a spillover disutility could be inferred. RESULTS: Fifteen studies were included in this review: seven reported estimates of spillover disutility and eight reported data from which disutility could be inferred. Three studies found no disutility associated with spillover, whereas 12 found measurable effects as large as -0.718 (and two found evidence of positive spillover in subsets of their samples). Generic (indirect) utility instruments were primarily used to measure spillover, including the EQ-5D, QWB, and HUI (n = 13), though two studies used modified versions of the time trade-off technique. Illnesses studied included childhood disorders (e.g., spina bifida, congenital malformations), diseases of the elderly (e.g., Alzheimer's disease and dementia), physically disabling conditions (e.g., arthritis, multiple sclerosis), and medical conditions such as cancer and stroke. The persons affected by spillover included parents, grandparents, spouses/partners, other family caregivers, and household members. CONCLUSIONS: There is a limited literature on the spillover disutility of illness on family members and caregivers, providing some specific estimates of a generally small, negative effect for particular conditions and individuals. Measurement methods vary across studies and a consensus approach has not yet been reached. Evidence suggests that the inclusion of spillover effects in economic evaluations would increase the relative effectiveness of interventions that address conditions with spillover compared to those without, though such differential benefits may be limited to such specific circumstances.

Willingness-to-pay for an area-wide integrated pest management program to control the Asian tiger mosquito in New Jersey.

Using contingent valuation we estimated the perceived value of an area-wide integrated pest management program for the Asian tiger mosquito, Aedes albopictus, implemented in Monmouth and Mercer counties, NJ. We estimated residents' maximum willingness-to-pay and perceived monetary benefits (willingness-to-pay excluding residents who protested all types of payments) and payment modality through a telephone survey of 51 randomly selected households. The mean (+/- SE) perceived monetary benefits for an enhanced mosquito abatement program was $9.54 +/- 2.90 per capita per year. Most respondents would have been willing to pay through taxes (35%) or charitable donations (6%) starting then, or through one of these approaches in the future (43%), whereas 16% were completely unwilling to pay any additional costs whatsoever. We projected that the perceived monetary benefits to the counties' 1.01 million residents for an enhanced mosquito control program would be $9.61 million annually. Thus, collectively residents perceived monetary benefits of 3.67 times the combined 2008 annual operating costs of the counties' existing mosquito control programs of $2.61 million.