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

PharmacoEconomics, Mar 2019

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.

A PDF file should load here. If you do not see its contents the file may be temporarily unavailable at the journal website or you do not have a PDF plug-in installed and enabled in your browser.

Alternatively, you can download the file locally and open with any standalone PDF reader:

https://link.springer.com/content/pdf/10.1007%2Fs40273-019-00768-7.pdf

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

PharmacoEconomics pp 1–25 | Cite as Spillover Effects on Caregivers’ and Family Members’ Utility: A Systematic Review of the Literature AuthorsAuthors and affiliations Eve WittenbergLyndon P. JamesLisa A. Prosser Open Access Systematic Review First Online: 18 March 2019 8 Shares 354 Downloads Abstract 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. Electronic supplementary material The online version of this article ( https://doi.org/10.1007/s40273-019-00768-7) contains supplementary material, which is available to authorized users. Key Points Inclusion of caregiver and family member (‘spillover’) quality-adjusted life-years (QALYs) in cost-effectiveness analyses (CEAs) is recommended by multiple national guidance bodies. Caregiver and family member QALYs can include spillover utilities (the independent utility loss due to a family member’s illness) that are rarely reported in the literature; more common are caregivers’/family members’ utilities, sometimes in combination with a comparator utility. Research gaps remain in spillover effect estimation and incorporation methods, slowing the adoption of these additional measures of burden into cost-effectiveness evaluations. 1 Background The burden of family caregiving is familiar to most [1]. Spouses’ health declines when their partners are hospitalized [2], adult children become anxious and fatigued caring for parents with dementia [3], and parents lose sleep while caring for disabled children [4]. Yet the consequences of illness in a family are in fact a complicated interplay of the physical, psychological, and emotional, ranging from strain, grief, and guilt, to gratification, interdependence, and joy, and affect caregiving as well as non-caregiving members [5]. While some families experience solace and relief when their relative’s health improves, changes in family dynamics and caregiving responsibilities may come as well: extended life for an elderly frail parent incurs extended caretaking needs; successful treatment for a severely ill child may result in a lifelong disability, with the associated care needs and emotional trauma for the parents [5, 6, 7]. The shifting locus of care to outpatient settings and the home increases families’ involvement in care, and the corresponding effects on their health and well-being [1]. Current recommendations for societal perspective economic evaluation include both patients’ and family members’ effects in assessing the cost effectiveness of health technologies and interventions [8, 9, 10, 11]. The effects, both health and otherwise, that are incurred by caregivers and non-caregiving family members (hereafter called ‘spillover effects’) are challenging, both to measure and to incorporate into cost-effectiveness analysis (CEA1). Measures of health-related spillover effects include utility valuations, via direct or indirect utility elicitation techniques, used to calculate quality-adjusted life-years (QALYs), and valuations that adopt a broader perspective, including care-related effects, that cannot be used for QALYs but rather capture the value assigned to the caring experience [12, 13]. A recommended, QALY-based measurement approach that is suitable across the variations in effects, including patient diseases/conditions, patient/caregiver/family member relationship, and extent of caregiver/family member involvement, has yet to be identified. Moreover, incorporating spillover effects into CEA poses its own challenges; although frameworks have been proposed, questions remain and inclusion has not yet become the norm [14, 15, 16]. The costs incurred in the course of providing informal care are also recommended for inclusion in societal perspective CEAs [9]. The time and effort of caregiving are also ‘spillover’ effects of illness, but are included on the cost side of the CEA equation. While out-of-pocket expenses and time spent caregiving are relatively simple to quantify, assigning value to time is more daunting. Multiple valuation approaches have been proposed without clear guidance for a preferred method [17, 18]. Including informal time costs in CEA is becoming more common, although it is still the exception [17, 19]. This review focuses exclusively on QALY-related spillover effects, and readers are referred elsewhere for considerations of cost spillovers [17, 18]. This review presents health utilities associated with caregivers and family members of individuals with health conditions and diseases—including spillover utilities and disutilities,2 and caregiver and family member utilities, reported with and without comparator utilities. We also included preference-based, caregiver-specific utilities (i.e. spillover effects measured from the perspective of caregivers’ experiences and including domains other than health), although these are not consistent with a QALY framework [20]. This compilation serves two functions. First, it provides a state-of-the-field overview of preference-based measures of caregivers’ and family members’ health-related quality of life, and second, it provides a catalog of the available data from which caregiver and family member QALYs may be derived to inform CEAs. Our primary goal for this review was to inform the inclusion of spillover effects in CEAs. Secondarily, we sought to advance the methods of spillover valuation and incorporation by expanding the collective knowledge base of measurement techniques, data, and, subsequently, evaluations that include spillover effects. 2 Methods Our objective was to report the universe of articles that reported a preference-based measure of caregiver or family member spillover effects. We conducted a systematic review of the medical and economic literatures to identify articles containing utilities for family caregivers and non-caregiving family members, including three electronic databases: MEDLINE, EMBASE, and EconLit. We refined search terms by testing them against a set of known-to-us papers to ensure capture of relevant articles. The final search strategy combined terms describing utility measures with terms describing caregivers, family members, and burden: utility, disutility, preference weight, QALY, standard gamble, time trade-off, EuroQoL (EQ-5D), Short-Form 6-Dimension (SF-6D), Health Utilities Index (HUI), Quality of Wellbeing Scale (QWB), CarerQol, Carer Experience Scale (CES), Child Health Utility-9 dimensions (CHU-9D), and variants thereof; spillover, caregiver, family, partner, spouse, child, sibling, parent, grandparent, next of kin, burden, consequence, and associated variants. Figure 1 shows the search process (the full search specifications are included in the online supplementary material). Open image in new window Fig. 1 PRISMA diagram of the search process. *Examples of search terms: [spillover, caregivers, family, partner, spouse, parent, child, sibling, grandparent, next of kin, burden, impact, consequences] AND [utility, disutility, preference weight, standard gamble, time trade-off, visual analog, QALY, SF-6D, EQ-5D, CarerQol, CES, HUI, QWB, CHU-9D]. **No caregiver or family member utility reported (n = 75); duplicate (n = 12); invalid score (utility reported > 1.0 or as WTP utility; n = 4); no English full-text available (n = 4); not peer-reviewed (n = 2). PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses, QALY quality-adjusted life-year, SF-6D Short-Form 6-Dimension, EQ-5D EuroQol-5 dimensions, CES Carer Experience Scale, HUI Health Utilities Index, QWB Quality of Wellbeing Scale, CHU-9D Child Health Utility-9 dimensions, WTP willingness to pay 2.1 Eligibility Criteria We included peer-reviewed articles published in English that reported a preference-based measure of caregiver or family member utility or disutility, including caregiver-focused measures for which population tariffs exist (i.e., CarerQol [20] and CES [21]), from the inception of each database through 3 April 2018. We included articles that reported on multiple patient diseases and/or using multiple preference-based methods/instruments, but excluded articles that reported only the EQ-VAS or a visual analog scale measure unless the scores were transformed into utilities using a known algorithm [22]. We defined family member as anyone identified as having a familial relationship to the patient regardless of distance (e.g., cousins would meet our inclusion criterion). We assumed that all family members classified in articles as caregivers were such; we did not impose any criteria on this role. We included articles reporting on ‘informal caregivers’ unless they were described as exclusively non-familial, such as neighbors, church members, and the like, but excluded paid caregivers. We included articles reporting on all patient diseases and conditions, including those that specified no disease, meaning they included caregivers regardless of the patient’s disease. We also included articles reporting on patient health states, defined as a distinct phase of a disease or condition (such as chemotherapy or hospitalization); a disease was defined as a diagnosed condition. We excluded disease transmission among family members from our definition of spillover effects. We included death as a health state when it was directly related to a disease or condition, such as maternal mortality, but we did not specifically search for bereavement. We imposed no age limit on patients or caregivers/family members. We included articles reporting on studies specifically designed to measure spillover utility, those measuring caregiver/family member utility among other outcomes, and caregiver or patient interventions that included utility as an outcome. We excluded reviews, reports, study protocols, commentaries, editorials, and conference papers, as well as articles that reported what appeared to be invalid utilities, such as scores > 1.0 or those described as ‘WTP utilities’. 2.2 Data Collection After excluding duplicates, two authors (EW and LJ) independently screened titles and abstracts; conflicts were resolved by consensus. We repeated this process with the full-text articles remaining after screening. We recorded the reason for each exclusion using Covidence systematic review software (Veritas Health Innovation, Melbourne, VIC, Australia). We extracted data that would allow a reader to identify potentially useful values for an analysis: patients’ disease/condition; patients’ age (adult/child/either); valuation measure used (EQ-5D, standard gamble, etc.); sample source (e.g., medical centers, patient association, population); country of sample; affected person’s role (i.e., family member/family caregiver/informal caregiver); caregiver/family member age (mean or other summary measure); sample size; utility (mean or median); if relevant to study design: comparison group source, sample size, and utility (mean or median); and if relevant, the reporting of utilities by strata, and other notes. We created a table entry for each patient disease/condition for which a relevant utility was reported in an article; articles that reported utility for more than one patient disease/condition were included in an entry for each. We included multiple utilities measured using different methods (e.g., HUI2 and HUI3) or applying different valuation weights for the same measure (e.g., Canadian and US weights for SF-6D) in one entry. If both caregiver/family member utilities and spillover disutilities were reported, we included each. If utilities were reported for the same condition/disease for multiple countries, we reported the one with the largest country-specific sample size. For all other instances of multiple utilities reported for the same disease/condition, we included those we deemed most salient to most readers and noted the availability of others in the ‘notes’ comment. We included the scores/values as reported by authors, but performed no manipulations or calculations on reported data. We grouped the entries into three categories: (1) spillover utilities or disutilities; (2) caregiver and/or family member utility reported with a matched or population comparison group; and (3) caregiver and/or family member utility reported alone. 3 Results Our search yielded 5205 records. After removing duplicates, we screened 3695 studies by title and abstract, and assessed 177 full-text articles for eligibility; 80 articles remained for inclusion in our review (Fig. 1). Of these 80 articles, 8 (10%) reported spillover utility/disutility: 4 reported spillover disutility as the difference between population utility and the observed family caregiver utility [23, 24, 25, 26], 1 reported disutilities only [27], 1 reported both the difference between the observed caregiver utility and the population utility, as well as a utility for a hypothetical scenario in which the ill relative did not need caregiving [28], and 2 reported spillover utilities only, elicited using a direct method to isolate the spillover effect per se [29, 30]. Twenty-five (30%) reported a comparison group, either general population norms (n = 9; 3 of which also reported disutility) (Table 1) or matched, non-caregiver/family members or hypothetical scenarios’ utilities (n = 16) (Table 2). Fifty (63%) reported caregiver/family member utilities only (Table 3).3 Table 1 Literature reporting spillover utility loss or spillover utility Author, year Patient disease/condition Patients’ age (adult/child/either) Valuation measurea Sample source Country included in the sample Affected person’s role (family member, caregiver, etc.) Caregiver/family member age, years [mean (SD) unless otherwise specified] Sample size Spillover utility loss, or utility when noted [mean (SD) unless otherwise specified] Comparison group source (if any) Comparison group utility [mean (SD) unless otherwise specified] Notes Davidson et al., 2008 [28] Any disease/condition Adult–elderly EQ-5D EURO-FAMCARE study (six-country study of family caregivers) Sweden Family caregivers: partner, child 65.4 910 (a) − 0.015 (b) − 0.062    (a) Family caregiver utility minus age/sex-adjusted population mean (b) ‘R-QALY’ = family caregiver utility minus hypothetical scenario of family member in good health/not needing care Also reported at 12-month follow-up time point and by sex Prosser et al., 2015 [27] Arthritis Adult Standard gamble Internet panel weighted to US population US Family members 18–29: 15.2% 30–44: 22.3% 45–59: 31.0% ≥ 60: 31.5%b 382 0.27 (0.25), median: 0.20 [IQR 0.05–0.50]    1 minus respondent-reported utility for hypothetical family member of patient; also reported for cancer, dementia, depression Prosser et al., 2015 [27] Cancer: not specified Adult Standard gamble Internet panel weighted to US population US Family members 18–29: 15.2% 30–44: 22.3% 45–59: 31.0% ≥60: 31.5%b 506 0.27 (0.25), median: 0.25 [IQR 0.02–0.50]    1 minus respondent-reported utility for hypothetical family member of patient; also reported for arthritis, dementia, depression Basu et al., 2010 [30] Cancer: prostate Adult Time trade-off (modified) 1 hospital US Family members: partner 57.7 (6.6) 26 Spillover utility: incontinence: 0.675 (0.344)    Utility for spillover effect of patient’s health on spouse; also reported for impotence, post-prostatectomy, post-radiation therapy, ‘watchful waiting’, metastasis, and death Poley et al., 2012 [24] Congenital abnormality: ARM, CDH Child EQ-5D 1 hospital Netherlands Family caregivers: parents Females: 35 [range 22–48] Males: 38 [range 24–59] 262 25- to 34-year-old mothers of child with ARM: − 0.10 General population by age category NS Also reported as mean family caregiver utility (Table 2); all utilities reported by mother/father and age group (25–34 and 35–44 years) Prosser et al., 2015 [27] Dementia: Alzheimer’s disease Adult Standard gamble Internet panel weighted to US population US Family members 18–29: 15.2% 30–44: 22.3% 45–59: 31.0% ≥ 60: 31.5%b 206 0.25 (0.24), median: 0.21 [IQR 0.02–0.50]    1 minus respondent-reported utility for hypothetical family member of patient; also reported for cancer, arthritis, depression Prosser et al., 2015 [27] Depression Adult Standard gamble Internet panel weighted to US population US Family members 18–29: 15.2% 30–44: 22.3% 45–59: 31.0% ≥ 60: 31.5%b 541 0.26 (0.24), median: 0.20 [IQR 0.02–0.50]    1 minus respondent-reported utility for hypothetical family member of patient; also reported for cancer, dementia, arthritis Landfeldt et al., 2016 [43] Duchenne muscular dystrophy Child EQ-5D Disease network Germany, Italy, UK, US Family caregivers: parent 44 (8) 770 0.11 Population mean (age 35–44 years) NS Also reported as caregiver utility (Table 2), and by patient ambulation status, health status, and mental status Wittenberg et al., 2016 [29] Opioid use/treatment Adult Standard gamble Nationally representative internet panel US Family members: spouse 18–24: 12.1% 25–44: 33.2% 45–64: 36.6% 65 + : 18.1%b 372 Spillover utility: active injection misuse 0.743, median 0.83 [IQR 0.510–1.0]    Utility for hypothetical spouse of individual in health state; also reported for active prescription misuse, methadone therapy, and buprenorphine therapy Crawford et al., 2017 [26] Otitis media: acute Child EQ-5D 3 hospitals Malaysia Family caregivers: parent NS 110 (0.10) [range −0.07–0.55], median 0 Population norms (gender based) NS Also reported as caregiver utility (Table 3) Brouwer et al., 2004 [25] Rheumatoid arthritis Adult EQ-5D Multicenter Netherlands Family caregivers: partner 61.5 145 0.0173 (0.2218) General population (age- and sex-adjusted) 0.8035 (0.0586) Also reported as mean caregiver utility (Table 2), and by caregiver sex, and patient quality of life NCUtility and measurement methods of articles reporting preference-based measures of caregivers’ and family members’ health-related quality of life published in the medical and economic literatures from inception to April 2018, in alphabetical order by patient disease/condition ARM anorectal malformation, CDH congenital diaphragmatic hernia, SD standard deviation, IQR interquartile range, NS not specified, EQ-5D EuroQol-5 dimensions, US United States, UK United Kingdom; Comparison group sample size not included in any papers in this table. aEQ-5D refers to the 3-level version unless indicated as EQ-5D-5L bSurvey respondent age Some articles reported utilities for multiple conditions or using multiple measurement methods, or for multiple strata of caregivers/family members. Across all 80 articles, Alzheimer’s disease and other types of dementia were the most frequent focus (15 articles), followed by cancer (6 articles) (Tables 1, 2, 3). Over half of the studies focused on caregivers/family members of ill adults (47, or 59%), 14 on ill children (18%), and the remainder focused on adults and children combined. The EQ-5D was the most common instrument used to measure caregiver/family member utility (58, or 69%, of uses among 84 in total; some articles reported multiple measurement methods). Indeed, 95% of articles used generic (i.e., indirect) measurement instruments: the SF-6D was used in 13 instances (16%), and the HUI and QWB were used three and two times, respectively. The caregiver-focused instruments (the CarerQol and CES) were used in seven instances (six uses and one use, respectively; 9%). Six articles (8%) reported caregiver/family member utility in the context of a patient and/or caregiver intervention trial. Most spillover effects research has been conducted in Europe (53 articles, 66%), followed by the US and Canada (20 articles, 25%). The earliest article reporting on this topic was published in 1988; nearly half (49%) were published between 2015 and 2018 (Tables 1, 2, 3). Table 2 Literature reporting caregiver and/or family member utility and matched or population comparison group Author, year Patient disease/condition Patients’ age (adult/child/ either) Valuation measurea Sample source Country included in the sample Affected person’s role (family member, caregiver, etc.) Caregiver/ family member age, years [mean (SD) unless otherwise specified] Sample size Utility [mean (SD) unless otherwise specified] Comparison group source Comparison group sample size Comparison group utility [mean (SD) unless otherwise specified) Notes Matched comparison group Kuhlthau et al., 2010 [44] Activity limitations Child EQ-5D Medical Expenditures Panel Survey US Family caregivers: parents < 25: 3.7% 25–39: 51.8% 40–54: 39.4% 55 + : 5.1% 2412 0.82 Parents of children without activity limitation 13,560 0.9   Thomas et al., 2015 [45] Any disease/condition Either EQ-5D Population survey of primary care patients UK Informal caregivers 8 age categories reported, 18–85 + 195,364 0.81 Non-caregivers 764,633 0.84 Sample is a population of primary care patients in England; also reported by no. of hours caregiving/week Song et al., 2012 [46] Cancer: 3–6 months after death Adult EQ-5D 33 palliative care centers Korea Family members: spouse, non-spouse 53.2 (12.5) 353 0.88 (0.2) Non-bereaved family members 353 0.93 (0.13)   Lee et al., 2015 [47] Cancer Either EQ-5D National survey Korea Family members NS 3406 0.9225 (0.1278) Non-cancer families 160,089 0.9411 Also reported by family member sociodemographic strata and perceived health status of the patient Zhou et al., 2016 [48] Death: maternal death due to pregnancy Adult EQ-5D Childbirth records China Family members: husbands Median: 33 [IQR 27–39] 84 Baseline: 0.73 (0.07) @1 year: 0.78 (0.07) Families without a maternal death 96 Baseline: 0.82 (0.05) @1 year: 0.83 (0.04)   Mohide et al., 1988 [37] Chronic degenerative disorders Adult TTO Visiting nurse agency and community service organization Canada Family caregivers 79.9 (10.9) 28 Caregivers of physically impaired: 0.795 Cognitively impaired: 0.412 Family members living with well elderly relatives 10 0.990 Instrument development study (CQLI); also reported for standardized caregiver wellbeing states: mild, moderate, severe Gupta et al., 2012 [49] Dementia: Alzheimer’s disease NS SF-6D Opt-in panel, weighted to population US Informal caregivers 52.51 (14.51) 1341 0.70 (0.14) Non-caregivers 69,224 0.74 (0.14) Also reported for multiple sclerosis (below) Laks et al., 2016 [50] Dementia: Alzheimer’s disease and other Adult SF-6D Opt-in internet panel, weighted to population Brazil Informal caregivers 42.09 (13.65) 209 0.682 (0.139) Non-caregivers 10,644 0.715 (0.137)   Rochanathimoke et al., 2018 [51] Diarrhea: acute Child EQ-5D 3 hospitals Thailand Family caregivers: parent, grandparent (1 sibling) NS 460 0.620 (0.12), median: 0.635 [IQR 0.514–0.694] Same caregivers imagining child prior to hospital stay 460 0.964 (0.10), median: 1 [IQR 1–1] Also reported by condition severity and whether diarrhea was rotavirus positive or negative Brisson et al., 2010 [52] Gastroenteritis (due to rotavirus) Child EQ-5D 59 outpatient practices Canada Family members: parents NS 186 Baseline: 0.875 @ week 1: 0.945 Parent post-episode 186 @ week 2 0.967 Also calculated as QALY loss compared to end of episode (@ week 2) Al-Janabi et al., 2016 [53] Meningitis (long-term effects) Either EQ-5D-5L Meningitis charity UK Family members 51 (13) 1053 0.87 Family members of meningitis patients with no after effects 517 0.91   Gupta et al., 2012 [49] Multiple sclerosis NS SF-6D Opt-in survey panel, weighted to population US Informal caregivers 43.16 (15.80) 215 0.70 (0.15) Non-caregivers 69,224 0.74 (0.14) Also reported for dementia (above) Acaster et al., 2013 [54] Multiple sclerosis Adult EQ-5D Patient recruitment panel UK Informal caregivers 50.88 (13.48) 200 0.74 (0.28) Matched controls 200 0.82 (0.25)   Gupta et al., 2015 [55] Schizophrenia Adult SF-6D Opt-in panel, weighted to population France, Germany, Italy, Spain, UK Informal caregivers 45.3 (15.8) 398 0.64 (0.12) Non-caregivers 796 0.71 (0.13)   Tilford et al., 2005 [4] Spina bifida Child QWB State birth defects surveillance system US Family caregivers: parents 37.7 (8.9) 98 0.76 (0.11) [range 0.54–1.0] Families with a similar-aged child without spina bifida 49 0.80 (0.10) [range 0.59–1.00] Also reported by location of lesion Persson et al., 2017 [56] Stroke (7 years post) Adult SF-6D 4 stroke units Sweden Family members: spouse 63 (11) 248 0.75 (0.12) [range 0.44–0.94] Spouses of individuals who had not had a stroke 245 0.77 (0.11)   Persson et al., 2017 [57] Stroke Adult SF-6D 4 stroke units Sweden Family members: spouse 67 (8) 247 0.69 (0.12) Spouses of individuals who had not had a stroke 245 0.77 (0.11) Also reported for non-dependent stroke survivors General population comparison group Nogueira et al., 2015 [58] Alcohol dependence Adult SF-6D Treatment program Spain Family caregivers: spouse, child, sibling 18–29: 6.3% 30–44: 29.7% 45–59: 39.1% 60–74: 20.3% 75 + : 4.7% 64 0.724 (0.213), median: 0.758 [IQR 0.626–0.868] General population 600 0.807 (0.159), median: 0.874 [IQR 0.750–0.940]   Sjolander et al., 2012 [59] Cancer: advanced lung or gastrointestinal, after diagnosis Adult EQ-5D 2 hospitals Sweden Family members: partners, children 63 (16) 36 @ 3 months post diagnosis: 0.73 (0.04); median: 0.8 General population (UK; 55–64 years age group)   0.80 (0.01) Also reported by time after diagnosis, age, and relationship to patient Poley et al., 2012 [24] Congenital abnormality: ARM, CDH Child EQ-5D 1 hospital Netherlands Family caregivers: parents Females: 35 [range 22–48] Males: 38 [range 24–59] 262 25- to 34-year-old mothers of child with ARM: 0.83 General population by age category   NS Also reported as the difference between caregiver and population mean (Table 1); all utilities reported by parent and age group (25–34 and 35–44 years) Angelis et al., 2015 [60] Cystic fibrosis Either EQ-5D-5L Cystic Fibrosis Trust UK Informal caregivers 37.3 33 0.836 (0.155) General population age 35–44 years   0.91 (0.16)   Landfeldt et al., 2016 [43] Duchenne muscular dystrophy Child EQ-5D Disease network Germany, Italy, UK, US Family caregivers: parent 44 (8) 770 0.81 Population mean (age 35–44 years)   NS Also reported as the difference between population mean and caregiver utility (Table 1), and by patient ambulation status, health status, and mental status van Andel et al., 2011 [61] Epilepsy Adult EQ-5D 1 medical center Netherlands Family caregivers: partner, parent 52 [range 21–78] 86 0.88 (0.17) Population NS 0.88 (0.19)   Kurien et al., 2017 [62] Gastrostomy Adult EQ-5D 5 hospitals UK Informal caregivers 65 (12.2) 100 0.95 (0.15) Population 200 0.93 (0.14) Also reported 3 months post insertion Brouwer et al., 2004 [25] Rheumatoid arthritis Adult EQ-5D Multicenter Netherlands Family caregivers: partner 61.5 145 0.8203 (0.2229) General population (age- and sex-adjusted)   0.8035 (0.0586) Also reported as the difference between caregiver and population mean (Table 1); also reported by caregiver sex, and patient quality of life van Exel et al., 2005 [63] Stroke (6 months post) Adult EQ-5D 6 hospitals Netherlands Informal caregivers 60.0 (13.9) 135 0.83 (0.24) [range − 0.02–1.0] General population (sex- and age-matched norms)   0.81 Also reported by caregiver burden Utility and measurement methods of articles reporting preference-based measures of caregivers’ and family members’ health-related quality of life published in the medical and economic literatures from inception to April 2018, in alphabetical order by patient disease/condition ARM anorectal malformation, CDH congenital diaphragmatic hernia, CLQI Caregiver Quality of Life Instrument, TTO time trade-off, SF-6D Short Form-6 Dimension, QWB Quality of Wellbeing Scale, NS not specified, IQR interquartile range, QALY quality-adjusted life-year, -EQ-5D EuroQol-5 dimensions, US United States, UK United Kingdom aEQ-5D refers to the 3-level version unless indicated as EQ-5D-5L Table 3 Literature reporting caregiver and/or family member utility Author, year Patient disease/condition Patients’ age (adult/child/ either) Valuation measurea Sample source Country included in the sample Affected person’s role (family member, caregiver, etc.) Caregiver/family member age, years [mean (SD) unless otherwise specified] Sample size Utility [mean (SD) unless otherwise specified] Notes Brouwer et al., 2006 [64] Any disease/condition Adult EQ-5D Regional informal care support centers Netherlands Family caregivers: partner, parent, child 60.8 (13.1) 175 0.75 (0.21) Instrument validation study with primary data Lutomski et al., 2015 [65] Any disease/condition Adult CarerQol-7D National data repository of research projects on older persons’ health Netherlands Family caregivers: partner, child 63 (12) 3269 79.2 (14.7)b [range 14–98] Compilation of data across studies; also reported by sampling frame subgroups: general population, hospital, and primary care settings Bobinac et al., 2010 [35] Any disease/condition NS EQ-5D Informal care support centers Netherlands Informal caregivers 55.34 (12.37) 595 0.82 (0.20) [range −0.11–1.0] Distinguishes between caregiving and caring about, but reported as combined utility Brouwer et al., 2005 [7] Any disease/condition Either EQ-5D Informal care support centers Netherlands Family caregivers: partner, child, parent 60.2 (12.1) [range 17–90] 843 0.76 (0.23)   del rio Lozano et al., 2017 [66] Any disease/condition Either EQ-5D-5L Caregiver registries Spain Family caregivers: parents, children, spouses 59.83 (14.47) 610 0.828 (0.195) Also reported by sex Oldenkamp et al., 2017 [67] Any disease/condition Adult–elderly CarerQol-7D National data repository of research projects on older persons’ health Netherlands Family caregivers: spouse, child 64.6 (12.61) 660 Baseline: median: 83.10b [IQR 73.9–89.6] @ 12 months: median: 80.42 [IQR 74.0–90.0]   Hoefman et al., 2014 [68] Autism spectrum disorder Child ED-5D, SF-6D 2 autism treatment network registries US Family caregivers: parents (mostly mothers) 39.4 (8.3) 224 EQ-5D: 0.85 (0.14) SF-6D: 0.74 (0.12)   Khanna et al., 2013 [69] Autism spectrum disorder Child EQ-5D Autism network US Family caregivers: parents (mostly mothers) NS 316 0.82 (0.16) Psychometric study; also reported by disease severity Khanna et al., 2013 [70] Autism spectrum disorder Child EQ-5D Autism network US Family caregivers: parents (mostly mothers) NS 316 Female caregivers: 0.81 (0.16) Also reported for male caregivers, younger/older caregivers Vrettos et al., 2012 [71] Cancer: during chemotherapy Adult EQ-5D 1 hospital Greece Family caregivers: spouses, parents, children 48.9 [range 20–80] 212 Females: 0.783 (0.228) Males: 0.895 (0.141)   Bradshaw et al., 2013 [72] Cognitive impairment Adult–elderly EQ-5D Acute general hospital wards UK Family caregivers: spouse, child, other Median: 62 [IQR 56–73] 180 Median: 0.8 [IQR 0.62–1.0] Also reported by caregiver/patient living situation Payakachat et al., 2011 [73] Craniofacial malformations Child HUI3, SF-6D, QWB State monitoring study sample US Family members 31.9 (5.3) [range 23.2–45.7] 65 HUI3: 0.84 (0.23) [range − 0.18–1.0] SF-6D: 0.81 (0.13) [range 0.51–1.0] QWB: 0.67 (0.14) [range 0.29–1.0]   Chevreul, 2016 [74] Cystic fibrosis Either EQ-5D Cystic fibrosis associations, registries Bulgaria, France, Germany, Hungary, Italy, Spain, Sweden, UK Informal caregivers 34.5 (5.8)–42.9 (8.0) across countries 271 total; 56 Spain Spain: 0.919 (0.086) Reported by country Chevreul et al., 2015 [75] Cystic fibrosis Either EQ-5D-5L Cystic fibrosis associations France Informal caregivers NS 40 0.761 Also reported by disease duration Fitzgerald et al., 2018 [76] Cystic fibrosis Child CarerQol-7D National cohort study of cystic fibrosis Ireland Family caregivers: parents Mothers: 35.5 (4.9) Fathers: 38.0 (5.5) 195 Mothers: 84.7b [IQR 74.5–88.0] Fathers: 89.2 [IQR 79.6–96.5] Also reported by child age Kraijo et al., 2014 [77] Dementia: not specified Adult CarerQol-7D Patient registries Netherlands Family caregivers: partners and parents 66.4 (13.4) [range 29–93] 223 70.1b (19.7) [range 5–100]   Bell et al., 2001 [78] Dementia: Alzheimer’s disease Adult HUI2 13 community and institutional care sites US Informal caregivers 63 679 0.87 (0.11) Also reported by disease severity and recruitment setting Fang et al., 2016 [79] Dementia: Alzheimer’s disease Adult EQ-5D 9 clinics Canada Caregivers Median: 69 [IQR 59–77] 216 UK weights: 0.8 Canadian weights: 0.83 Reported using UK and Canadian valuation sets; also reported by disease severity Majoni and Oremus, 2017 [80] Dementia: Alzheimer’s disease Adult EQ-5D 9 clinics Canada Informal caregivers Retired median: 74 [IQR 68–80] Employed median: 56 [IQR 51–62] 200 Retired median: 0.8 [IQR 0.73–1.0] Employed median: 0.84 [IQR 0.83–1.0] Reported separately for retired and employed caregivers Neumann et al., 2000 [81] Dementia: Alzheimer’s disease Adult HUI2 and HUI3 13 community and institutional care sites US Caregivers 63 (14) 679 HUI2: 0.87 (0.18) HUI3: 0.87 (0.14) Also reported by disease severity Oremus et al., 2014 [82] Dementia: Alzheimer’s disease Adult EQ-5D Memory and geriatric clinics Canada Informal caregivers Median: 69 [IQR 59–77] 216 US weights: 0.85, median: 0.83 [IQR 0.79–1.0] Canadian weights: 0.80, median: 0.83 [IQR 0.74–0.89] Reported using US and Canadian valuation sets; also reported by disease severity Reed et al., 2017 [83] Dementia: Alzheimer’s disease Adult EQ-5D Memory clinics France, Germany, UK Informal caregivers 67.3 (12.0) 1495 0.84 (0.2), median: 0.89 [IQR 0.79–1.0] Also reported by disease severity Dahlrup et al., 2014 [84] Dementia: not specified Adult–elderly EQ-5D Social service agencies Sweden Family caregivers Intervention median: 62 [IQR 27–90] Control median: 62 [IQR 38–95] 308 Intervention median: 0.848 [IQR 0.725–1.0] Control median: 0.796 [IQR 0.725–1.0] Caregiver intervention trial; also reported by patient living situation and relationship with patient Knapp et al., 2013 [85] Dementia: not specified Adult EQ-5D 4 service settings UK Family caregivers NS 260 Usual treatment: 0.77 (0.23) Intervention: 0.77 (0.22) Caregiver intervention trial; also reported at follow-up period Orrell et al., 2017 [86] Dementia: not specified Adult EQ-5D 8 care centers and disease associations UK Informal caregivers NS 273 Intervention: 0.82 Control: 0.76 Patient and caregiver intervention trial; also reported at mid-way point in trial Stewart et al., 2005 [87] Dementia: not specified Adult–elderly EQ-5D Social services and occupational therapy sites UK Informal caregivers NS 80 Arm 1: 0.69 (0.28) Arm 2: 0.77 (0.21) Patient and caregiver intervention trial, two arms; also reported at follow-up Vroomen et al., 2016 [88] Dementia: not specified Adult EQ-5D Case management clients Netherlands Informal caregivers Intervention 1: 64.5 (12.8) Intervention 2: 64.4 (12.4) Controls: 65.8 (11.7) 521 Intervention 1: 0.8 (0.2) Intervention 2: 0.9 (0.2) Controls: 0.9 (0.2) Patient/caregiver intervention trial Tiberg et al., 2016 [89] Diabetes: type 1 Child SF-6D 1 hospital Sweden Family caregivers: parents Control: mothers: 40.4 (5.3); fathers: 43.6 (6.6); Intervention: mothers: 40.1 (6.2); fathers: 42.6 (5.7) 76 Control: 0.775 Intervention: 0.811 Patient intervention trial; also reported separately at discharge and three follow-up time points Campbell et al., 2018 [90] Dravet syndrome Child EQ-5D-5L 1 hospital US Informal caregivers NS 30 0.78 (0.17) [range 0.31–1]   Cavazza et al., 2016 [91] Duchenne muscular dystrophy Either EQ-5D Patient organizations Bulgaria, France, Germany, Hungary, Italy, Spain, Sweden, UK Informal caregivers 25.0–49.6 across countries 154 Across countries: 0.71 Also reported by country Chevreul et al., 2016 [92] Fragile X syndrome Either EQ-5D Patient associations and registries France, Hungary, Italy, Spain, Sweden, UK Family caregivers: parent, other 37.5 (7.0)–47.9 (11.8) across countries 110 total (56 France) France: 0.754 (0.239) Reported by country Chevreul et al., 2015 [93] Fragile X syndrome Either EQ-5D-5L Patient associations France Informal caregivers NS NS 0.75 (0.24) Also reported by patient age Agren et al., 2013 [94] Heart failure Adult SF-6D 2 hospitals Sweden Family caregivers: partner Intervention: 67 (12) Controls: 70 (10) 109 Intervention group: 0.7112 Controls: 0.7096 RCT of intervention for patient/partner dyads; also reported at 12-month follow-up Iqbal et al., 2010 [95] Heart failure Adult EQ-5D 1 academic hospital NS Informal caregivers   131 0.76 (0.03) Also reported by caregiver sex, patient quality of life Squire et al., 2017 [96] Heart failure Adult EQ-5D-5L and CES 5 care centers England Family caregivers 69 [range 43–88] 72 EQ-5D: 0.75 (0.18), [range 0.28–1.0], median: 0.77   CES 39 (20), median 38b   Cavazza et al., 2016 [97] Hemophilia Either EQ-5D Patient associations Bulgaria, France, Germany, Hungary, Italy, Spain, Sweden, UK Family caregivers: parent, partner 34.7 (8.6)–48.0 (19.8) across countries 62 Across countries: 0.87 (0.15) Also reported by country Al-Janabi et al., 2017 [98] Meningitis (long-term effects) Either EQ-5D-5L Meningitis charity UK Family caregivers: parent, partner, grandparent 52.9 (11.7) 497 0.84 (.20)   Bhadhuri et al., 2017 [39] Meningitis (long-term effects) Either EQ-5D-5L, SF-6D Meningitis charity UK Family caregivers and non-caregiving family members Caregivers: 45.9 (11.9) Non-caregiving family members: 51.2 (12.1) 648 Caregivers: 0.80 (0.20) Non-caregiving family members: 0.85 (0.19) Also reported for  SF-6D and by patient improvement and hours of care provided Hastrup et al., 2011 [99] Mental Illness Either EQ-5D Informal caregivers’ regional support centers Netherlands Informal caregivers 59.92 (13.22) 865 total 0.73 (0.24) Comparison of mental illness to somatic illness; also reported for somatic illness (below) and both co-occurring Péntek et al., 2016 [100] Mucopolysaccharidosis Either EQ-5D Patient organizations Bulgaria, France, Germany, Hungary, Italy, Spain, Sweden Informal caregivers 21.5 (29.0)–47.3 (5.6) across countries 66 Italy: 0.681 (0.383) Reported by country Crawford et al., 2017 [26] Otitis media: acute Child EQ-5D 3 hospitals Malaysia Family caregivers: parent NS 110 0.92 (0.10), [range 0.38–1.0], median: 0.94  Also reported as difference between population norms and caregiver utility (Table 1) Hoefman et al., 2015 [101] Palliative care Adult EQ-5D, CarerQol-7D, CES 1 service provider Australia Family caregivers: partner, parent 62.3 (11.9) 97 EQ-5D: 0.7 (0.2) CarerQol: 73.5b (17.1) CES: 72.5b (16.3)   Carod-Artal et al., 2013 [102] Parkinson’s disease Adult EQ-5D 1 hospital outpatient clinic Brazil Family caregivers: spouse, child 55.7 (13.1) 50 0.7 (0.3) [range −0.031–1]   Martinez-Martin et al., 2007 [103] Parkinson’s disease Adult EQ-5D 7 medical centers Spain Family caregivers: spouse, child 61.3 (13.2) [range 30–85] 78 0.8 (0.2) [range 0.2–1]   Martinez-Martin et al., 2008 [104] Parkinson’s disease Adult EQ-5D Specialized practices Spain Family caregivers: spouse, child 59.4 (13.5) [range 25–87] 286 0.79 (0.24) [range −0.15–1.0]   Chevreul et al., 2016 [105] Prader–Willi syndrome Either EQ-5D-5L Patient associations France Informal caregivers NS 16 0.74 (0.25) Also reported by patient age: child and adult van Dam et al., 2017 [106] Rehabilitation: following geriatric rehabilitation Adult CarerQol-7D 16 skilled nursing facilities Netherlands Family caregivers: partner, child 63 (13.3) 350 Median: 83.9b [IQR 74.4–91.7]   Daltio et al., 2017 [107] Schizophrenia Adult SF-6D 1 hospital Brazil Family caregivers: parent, partner, child 56.05 (12.99) 159 0.78 (0.08) Willingness-to-pay study; utility collected as a descriptive variable Hastrup et al., 2011 [99] Somatic illness (unspecified) Either EQ-5D Informal caregivers’ regional support centers Netherlands Informal caregivers 59.78 (11.86) 865 total 0.78 (0.22) Comparison of mental illness to somatic illness; also reported for mental illness  (above) and both co-occurring Cramm et al., 2012 [108] Stroke Adult EQ-5D 9 stroke service facilities Netherlands Family caregivers: partner, child, sibling 59.14 (14.87) 251 0.74 (0.34)   Carod-Artal et al., 2009 [109] Stroke Adult EQ-5D 1 clinic Brazil Family caregivers: spouse, children, other family 42.0 (14.1) 200 0.7 (0.2) [range 0.04–0.85] Also reported by relationship to patient and patient’s functional status Chevreul et al., 2015 [110] Systemic sclerosis (scleroderma) Adult EQ-5D-5L Patient associations France Informal caregivers NS 14 0.66 (0.41)   Utility and measurement methods of articles reporting preference-based measures of caregivers’ and family members’ health-related quality of life published in the medical and economic literatures from inception to April 2018, in alphabetical order by patient disease/condition IQR interquartile range, NS not specified, SF-6D Short Form-6 dimensions, EQ-5D EuroQol-5 dimensions, CES Carer Experience Scale, HUI Health Utilities Index, QWB Quality of Wellbeing Scale, CI confidence interval, RCT randomized controlled trial, US United States, UK United Kingdom aEQ-5D refers to the 3-level version unless indicated as EQ-5D-5L bCarerQol and CES reported on a 0–100 scale 4 Discussion The past two decades have seen research on spillover health effects progress from a conceptual framework [15] to methods for measurement and incorporation into CEAs [14, 16, 27, 31, 32]. In 2016, the Second Panel on Cost-Effectiveness in Health and Medicine endorsed the inclusion of caregiver and family member effects in societal perspective CEAs, while at the same time acknowledging current limitations in measurement methodology and practice [9]. Dutch and National Institute for Health and Care Excellence (NICE) guidelines also recommend inclusion of spillover effects [10, 11]. This systematic review facilitates adherence to current recommendations by providing a catalog of preference-based values for spillover effects available to date. It is broader and more comprehensive than a previous review that focused on spillover utility only; this review includes caregiver and family member utilities from which spillover can be estimated or derived, and preference-based measures of caregiving effects beyond health [13]. Spillover costs for informal care are also recommended for inclusion, and have been reviewed and discussed elsewhere [17, 18]. Along with this catalog and the opportunity to incorporate spillover effects into CEAs come a host of questions, all of which have practical and policy implications: what is and is not considered spillover by different investigators; how can and cannot spillover be captured using different measures and populations; and how and under what circumstances it should or should not be included in CEAs. 4.1 What is Spillover and How can it be Measured? ‘Spillover’ results from caregiving, simply caring about others, or a combination of the two. What constitutes caregiving for one person may be ordinary behavior for another—the distinction, for example, between ‘regular’ parenting and caregiving for sick children [33]. Caregiving is often shared among family members, it sometimes vacillates between family and paid caregivers (such as when patients cycle between home and hospital), and it changes in nature and intensity over time [34]. Caregiving can provide sustenance to family members who might otherwise feel a lack of control or disengaged from an ill relative, moderating the otherwise burden of care [5]. While the literature tends to focus on primary caregivers, other family members both provide care and experience spillover effects of illness [5, 35]. The inconsistent description of caregiving and family involvement in the literature injects variability into both the estimation of spillover QALYs and how to interpret the policy implications of family-based CEAs. Health utility scores can capture the health-related spillover effects of caregivers and family members if the health-specific spillover effects are isolated; meaning, the utility associated with solely the caring for or caring about component of having an ill relative. These utility scores can be used to calculate QALYs for CEAs. Care-related measures, such as the CarerQOL, albeit preference-based, include non-health domains in addition to health, and as such are incompatible with CEAs. However, utility scores that reflect only the change in health-related quality of life (HRQOL) associated with spillover are available for just a small set of conditions, therefore other measures of caregiver/family member effects may yield values suitable for use in CEAs when certain assumptions hold. Most articles in this review fall into the category of conventionally-defined health utility scores: the utility of a caregiver or non-caregiving family member of an ill relative. These scores may include the impact of spillover but also the underlying health of the individual. Elderly caregivers, for example, are likely to have chronic health conditions simultaneous with their caregiving responsibilities, therefore their utility scores will reflect a combination of both effects. In some of these articles, utilities are reported for a matched sample, such as non-caregivers or family members of healthy individuals, or from general population norms, allowing for the calculation of a ‘spillover utility’. In the majority of articles reviewed, however, a comparison group utility is not reported, but an analysis could use an appropriate population norm to derive a spillover utility, carefully considered to match the demographics of the caregiver sample. The underlying assumption in this literature is that spillover effects are additive, yet this has not been empirically demonstrated; interaction effects have been hypothesized [30]. While a growing supply of spillover utility data is available in the literature, much of it requires assumptions such as this to be able to use these utilities in a CEA. A further challenge is that the current literature rarely distinguishes between caring for and caring about effects, which may be difficult to disentangle. Caregiver-focused ‘utility equivalents’ are preference-based but are distinct from QALYs. These measures—the CarerQol and CES—include a different and more comprehensive set of dimensions than are typically included in QALY-based measures (e.g., fulfillment, financial problems, relational problems). While they may accurately capture caregiver-relevant dimensions [36], their valuations are based on a care-related quality-of-life scale so cannot be used to estimate QALYs, and therefore can neither be combined with patient QALYs in CEAs nor compared with CEAs based on QALYs [20]. They are of particular value, however, for comparatively evaluating caregiver interventions. An early prototype of a caregiver-specific measure that was QALY-based but focused on caregiver-relevant dimensions—the Caregiver Quality of Life Index (CGLI)—was largely supplanted by these instruments [37]. 4.2 How and Under What Circumstances Should Spillover be Included in Cost-Effectiveness Analyses? Incorporation of spillover effects into CEAs faces significant methodological questions, including concerns regarding prioritizing caregiver health over patient health, equity in decision making, and ‘double counting’ of benefits. At the most basic level, spillover and patient QALYs can be summed to arrive at total QALYs, and this is currently the most common approach observed in practice. Some have proposed a weighting factor be applied to adjust for the relative importance of spillover effects compared with changes in health for the primary patient [14]. In the extreme, including spillover QALYs could tilt decisions toward benefiting caregivers/family members over the patient, although this is not the intended purpose of considering these effects [38]. Whose QALYs to include in spillover is also an unanswered question as evidence suggests effects extend beyond the primary caregiver [39] and perceptions of relevance (i.e. ‘closeness’) vary across individuals [40]. The articles in this review provide the data to inform family-based CEAs but do not inform the questions underlying appropriate incorporation approaches. Equity issues are significant in including spillover effects in CEAs. If spillover is included, cost-effectiveness ratios for interventions targeting diseases/conditions that require caretaking and/or negatively affect family members could be favored over diseases/conditions that do not. Interventions that affect oftentimes isolated patients, such as homeless individuals, could be undervalued relative to those that affect more connected individuals, such as children. At the same time, not including spillover could result in policy decisions that disregard the interests of caregivers and families [38, 41]. While it might be sensible to consider the effect of pediatric conditions on parents as well as the child, as successful treatment confers benefits on both, in cases such as dementia, patients’ and families’ interests may at times be at odds: successful treatment may prolong the patient’s life and extend the caretaking burden for the family. Including spillover QALYs in CEAs is both a methodological decision, including the ‘what’ and ‘how’ aspects, and a normative decision, including the ‘if’ and ‘when’ aspects. Whether it is normatively justifiable to include spillover in economic evaluation recognizing the potential reallocation of resources that may ensue is as yet unresolved [38, 41]. It is clear, however, that including spillover necessitates the accurate and normative definition of ‘who qualifies’, as who is or is not included can have an impact on the results, regardless of how those results are used in policy. Another concern raised with regard to including spillover in CEAs is double counting: spillover effects may already be implicitly included in utilities. Patients’ anxiety or depression, for example, may be a function of their condition’s effect on their family, rather than or in addition to its effect on themselves, indicating that family spillover may be at least in part reflected in patient utilities. Moreover, it may be difficult for caregivers or family members to disentangle their health from their ill relative’s, therefore their ‘spillover’ utility may include more than the effect on themselves individually. Although reasonable concerns, difficulty in measurement ought not preclude the incorporation of an endorsed component of effects. Advances in measurements, most of which use direct utility elicitation methods, have been made to attempt to accurately capture spillover independently, although with unconfirmed success [27, 28, 30]. Judicious use of sensitivity analysis may be a reasonable approach for the time being to minimize the effect of potential measurement error on CEA results. 4.3 Study Limitations Considerations should be noted regarding our review. While our search is comprehensive as of our end date, articles including utilities for spillover effects are being published with increasing frequency [19], and will soon render our catalog incomplete. We are in the process of developing an online, open-access repository of spillover effect utilities, which will be updated regularly as a public resource. Moreover, our catalog excludes the gray literature or unpublished sources. Unpublished utilities that are in the pipeline, via conference presentations and abstracts, will likely find their way into the published literature in the future and will be incorporated into successive versions of the catalog. Publication bias is not a concern for this review because our results are descriptive and not intended for inference. We limited the data included in our tables to ensure accessibility for readers—essentially a size that was viewable on a standard size page or computer screen—therefore details that are important to some may have been omitted. Finally, we made subjective judgments about the relative salience of utilities in articles reporting multiples, but describe others in the ‘notes’ section of the tables. 5 Conclusions The scope of CEAs is expanding from patient-based analyses to caregiver/patient dyadic and family-based analyses. While this expansion is consistent with theoretical principles of maximizing health benefits, prevailing methodological consensus, and demographic and health system changes, it raises practical challenges for CEA and highlights data gaps. It is likely, at least for the time being, that QALYs are here to stay [42]. Caregiver and family member spillover effects will therefore be primarily measured in QALYs and will consequently require utilities. This review provides a catalog of utilities to facilitate the calculation of QALYs and inform CEAs. Additional research is needed on methods of measuring and incorporating spillover QALYs to promote, among other things, an accurate reflection of societal preferences for caregiver/family effects relative to patients’ effects. It is our goal to advance the inclusion of spillover in CEA by providing this accessible overview of the spillover effects of HRQOL literature. We also aspire to expand the knowledge base of spillover-based CEAs, from which we will answer these remaining questions. Footnotes 1. We use ‘CEA’ to include cost-utility analysis for ease of reading. 2. Disutility is the utility loss associated with a particular state of health, as opposed to the utility of that state of health. 3. Multiple studies reported utilities for more than one disease/condition, each of which is represented in the tables as a separate entry. Notes Acknowledgements The authors are grateful for the invaluable assistance of Paul Bain, PhD, Research and Education Librarian, Countway Library of Medicine, in developing and implementing the literature search strategy, and Angela Rose, University of Michigan Medical School, for research assistance. Author Contributions EW and LAP conceptualized the study; EW and LPJ developed the search strategy and reviewed articles; LPJ conducted the search and developed tables/figures of the results; EW wrote the first draft of the manuscript; EW, LPJ, and LAP provided feedback and edited interim drafts; EW completed the final draft. Compliance with Ethical Standards Funding No funding was received for the conduct of this study. Conflict of interest Eve Wittenberg, Lyndon James, and Lisa Prosser have no conflicts of interest to report. Supplementary material 40273_2019_768_MOESM1_ESM.docx (24 kb) Supplementary material 1 (DOCX 23 kb) References 1. Wittenberg E, Prosser LA. Health as a family affair. N Engl J Med. 2016;374(19):1804–6.CrossRefPubMedGoogle Scholar 2. Christakis NA, Allison PD. Mortality after the hospitalization of a spouse. N Engl J Med. 2006;354(7):719–30.CrossRefPubMedGoogle Scholar 3. Richardson TJ, Lee SJ, Berg-Weger M, Grossberg GT. Caregiver health: health of caregivers of Alzheimer’s and other dementia patients. Curr Psychiatry Rep. 2013;15(7):367.CrossRefPubMedGoogle Scholar 4. Tilford JM, Grosse SD, Robbins JM, Pyne JM, Cleves MA, Hobbs CA. Health state preference scores of children with spina bifida and their caregivers. Qual Life Res. 2005;14(4):1087–98.CrossRefPubMedGoogle Scholar 5. Wittenberg E, Saada A, Prosser LA. How illness affects family members: a qualitative interview survey. Patient. 2013;6(4):257–68.CrossRefPubMedGoogle Scholar 6. Roth DL, Fredman L, Haley WE. Informal caregiving and its impact on health: a reappraisal from population-based studies. Gerontologist. 2015;55(2):309–19.CrossRefPubMedGoogle Scholar 7. Brouwer WBF, van Exel NJA, van den Berg B, van den Bos GAM, Koopmanschap MA. Process utility from providing informal care: the benefit of caring. Health Policy. 2005;74(1):85–99.CrossRefPubMedGoogle Scholar 8. National Institute for Health and Care Excellence. Methods for the development of NICE public health guidance. 3rd ed. 2012. https://www.nice.org.uk/process/pmg4/chapter/incorporating-health-economics. Accessed 18 Aug 2017. 9. Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, et al. Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. JAMA. 2016;316(10):1093–103.CrossRefPubMedGoogle Scholar 10. Versteegh M, Knies S, Brouwer W. From good to better: new Dutch guidelines for economic evaluations in healthcare. Pharmacoeconomics. 2016;34(11):1071–4.CrossRefPubMedGoogle Scholar 11. Cowles E, Marsden G, Cole A, Devlin N. A review of NICE methods and processes across health technology assessment programmes: why the differences and what is the impact? Appl Health Econ Health Policy. 2017;15(4):469–77.CrossRefPubMedGoogle Scholar 12. Al-Janabi H, Flynn TN, Coast J. QALYs and carers. Pharmacoeconomics. 2011;29(12):1015–23.CrossRefPubMedGoogle Scholar 13. Wittenberg E, Prosser LA. Disutility of illness for caregivers and families: a systematic review of the literature. Pharmacoeconomics. 2013;31(6):489–500.CrossRefPubMedPubMedCentralGoogle Scholar 14. Al-Janabi H, van Exel J, Brouwer W, Coast J. A framework for including family health spillovers in economic evaluation. Med Decis Making. 2016;36(2):176–86.CrossRefPubMedPubMedCentralGoogle Scholar 15. Basu A, Meltzer D. Implications of spillover effects within the family for medical cost-effectiveness analysis. J Health Econ. 2005;24(4):751–73.CrossRefPubMedGoogle Scholar 16. Hoefman RJ, van Exel J, Brouwer W. How to include informal care in economic evaluations. Pharmacoeconomics. 2013;31(12):1105–19.CrossRefPubMedGoogle Scholar 17. Krol M, Papenburg J, van Exel J. Does including informal care in economic evaluations matter? A systematic review of inclusion and impact of informal care in cost-effectiveness studies. Pharmacoeconomics. 2015;33(2):123–35.CrossRefPubMedGoogle Scholar 18. Grosse S, Jamison P, Soelaeman R, Tilford JM. Quantifying family spillover effects in economic evaluations: measurement and valuation of informal care time. Pharmacoeconomics. 2019.  https://doi.org/10.1007/s40273-019-00782-9.CrossRefGoogle Scholar 19. Lin P-J, D’Cruz B, Leech A, Neumann P, Aigbogun M, Oberdhan D, et al. Family and caregiver spillover effects in cost-effectiveness analyses of Alzheimer’s disease interventions. Pharmacoeconomics. 2019.  https://doi.org/10.1007/s40273-019-00788-3.CrossRefGoogle Scholar 20. Hoefman RJ, van Exel J, Brouwer WB. Measuring care-related quality of life of caregivers for use in economic evaluations: CarerQol tariffs for Australia, Germany, Sweden, UK, and US. Pharmacoeconomics. 2017;35(4):469–78.CrossRefPubMedGoogle Scholar 21. Al-Janabi H, Flynn TN, Coast J. Estimation of a preference-based carer experience scale. Med Decis Making. 2011;31(3):458–68.CrossRefPubMedGoogle Scholar 22. Hunink M, Weinstein M, Wittenberg E. Decision making in health and medicine integrating evidence and values. 2nd ed. Cambridge: Cambridge University Press; 2014.CrossRefGoogle Scholar 23. Landfeldt E, Lindgren P, Bell CF, Guglieri M, Straub V, Lochmuller H, et al. Quantifying the burden of caregiving in Duchenne muscular dystrophy. J Neurol. 2016;263(5):906–15.CrossRefPubMedPubMedCentralGoogle Scholar 24. Poley MJ, Brouwer WB, van Exel NJ, Tibboel D. Assessing health-related quality-of-life changes in informal caregivers: an evaluation in parents of children with major congenital anomalies. Qual Life Res. 2012;21(5):849–61.CrossRefPubMedGoogle Scholar 25. Brouwer WBF, van Exel NJA, van de Berg B, Dinant HJ, Koopmanschap MA, van den Bos GAM. Burden of caregiving: evidence of objective burden, subjective burden, and quality of life impacts on informal caregivers of patients with rheumatoid arthritis. Arthritis Rheumatol. 2004;51(4):570–7.CrossRefGoogle Scholar 26. Crawford B, Hashim SSM, Prepageran N, See GB, Meier G, Wada K, et al. Impact of pediatric acute otitis media on child and parental quality of life and associated productivity loss in Malaysia: a prospective observational study. Drugs Real World Outcomes. 2017;4(1):21–31.CrossRefPubMedGoogle Scholar 27. Prosser LA, Lamarand K, Gebremariam A, Wittenberg E. Measuring family HRQoL spillover effects using direct health utility assessment. Med Decis Making. 2015;35(1):81–93.CrossRefPubMedPubMedCentralGoogle Scholar 28. Davidson T, Krevars B, Levin LA. In pursuit of QALY weights for relatives: empirical estimates in relatives caring for older people. Eur J Health Econ. 2008;9(3):285–92.CrossRefPubMedGoogle Scholar 29. Wittenberg E, Bray JW, Aden B, Gebremariam A, Nosyk B, Schackman BR. 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. Addiction. 2016;111(4):675–84.CrossRefPubMedGoogle Scholar 30. Basu A, Dale W, Elstein A, Meltzer D. A time tradeoff method for eliciting partner’s quality of life due to patient’s health states in prostate cancer. Med Decis Making. 2010;30(3):355–65.CrossRefPubMedGoogle Scholar 31. Tilford JM, Payakachat N. Progress in measuring family spillover effects for economic evaluations. Expert Rev Pharmacoecon Outcomes Res. 2015;15(2):195–8.CrossRefPubMedGoogle Scholar 32. Brown Tilford JM. Measuring caregiver spillover effects associated with autism spectrum disorder: a comparison of the EQ-5D-3L and SF-6D. Pharmacoeconomics. 2019.  https://doi.org/10.1007/s40273-019-00789-2.CrossRefPubMedGoogle Scholar 33. Ungar WE. Economic evaluation in child health. New York: Oxford University Press; 2010.Google Scholar 34. Caregiving in the US 2015. Bethesda: National Alliance for Caregiving (NAC) and the AARP Public Policy Institute; 2015.Google Scholar 35. Bobinac A, van Exel NJA, Rutten FFH, Brouwer WBF. Caring for and caring about: disentangling the caregiver effect and the family effect. J Health Econ. 2010;29(4):549–56.CrossRefPubMedGoogle Scholar 36. Hoefman RJ, van Exel J, Brouwer WB. Measuring the impact of caregiving on informal carers: a construct validation study of the CarerQol instrument. Health Qual Life Outcomes. 2013;11:173.CrossRefPubMedPubMedCentralGoogle Scholar 37. Mohide EA, Torrance GW, Streiner DL, Pringle DM, Gilbert R. Measuring the wellbeing of family caregivers using the time trade-off technique. J Clin Epidemiol. 1988;41(5):475–82.CrossRefPubMedGoogle Scholar 38. McCabe C. Spillover effects and economic evaluations in health: some words of caution. Pharmacoeconomics. 2018.  https://doi.org/10.1007/s40273-018-0729-z.CrossRefPubMedGoogle Scholar 39. Bhadhuri A, Jowett S, Jolly K, Al-Janabi H. A comparison of the validity and responsiveness of the EQ-5D-5L and SF-6D for measuring health spillovers: a study of the family impact of Meningitis. Med Decis Making. 2017;37(8):882–93.CrossRefPubMedGoogle Scholar 40. Canaway A, Al-Janabi H, Kinghorn P, Coast J. Close-person spill-overs in end-of-life care: using hierarchical mapping to identify whose outcomes to include in economic evaluation. Phamacoeconomics. 2019.  https://doi.org/10.1007/s40273-019-00786-5.CrossRefGoogle Scholar 41. Brouwer W. The inclusion of spill-over effects in economic evaluations: not an optional extra. Pharmacoeconomics. 2018.  https://doi.org/10.1007/s40273-018-0730-6.CrossRefPubMedPubMedCentralGoogle Scholar 42. Neumann PJ, Cohen JT. QALYs in 2018—advantages and concerns. JAMA. 2018;319(24):2473–4.CrossRefPubMedGoogle Scholar 43. Landfeldt E, Lindgren P, Bell CF, Guglieri M, Straub V, Lochmuller H, et al. Health-related quality of life in patients with Duchenne muscular dystrophy: a multinational, cross-sectional study. Dev Med Child Neurol. 2016;58(5):508–15.CrossRefPubMedGoogle Scholar 44. Kuhlthau K, Kahn R, Hill KS, Gnanasekaran S, Ettner SL. The well-being of parental caregivers of children with activity limitations. Matern Child Health J. 2010;14(2):155–63.CrossRefPubMedGoogle Scholar 45. Thomas GPA, Saunders CL, Roland MO, Paddison CAM. Informal carers’ health-related quality of life and patient experience in primary care: evidence from 195,364 carers in England responding to a national survey. BMC Fam Pract. 2015;16:62.CrossRefPubMedPubMedCentralGoogle Scholar 46. Song JI, Shin DW, Choi J-Y, Kang J, Baek Y-J, Mo H-N, et al. Quality of life and mental health in the bereaved family members of patients with terminal cancer. Psychooncology. 2012;21(11):1158–66.CrossRefPubMedGoogle Scholar 47. Lee HJ, Park E-C, Kim SJ, Lee SG. Quality of life of family members living with cancer patients. Asian Pac J Cancer Prev. 2015;16(16):6913–7.CrossRefPubMedGoogle Scholar 48. Zhou H, Zhang L, Ye F, Wang H-J, Huntington D, Huang Y, et al. The effect of maternal death on the health of the husband and children in a rural area of China: a prospective cohort study. PLoS One. 2016;11(6):e0157122.CrossRefPubMedPubMedCentralGoogle Scholar 49. Gupta S, Goren A, Phillips AL, Stewart M. Self-reported burden among caregivers of patients with multiple sclerosis. Int J MS Care. 2012;14(4):179–87.CrossRefPubMedPubMedCentralGoogle Scholar 50. Laks J, Goren A, Duenas H, Novick D, Kahle-Wrobleski K. Caregiving for patients with Alzheimer’s disease or dementia and its association with psychiatric and clinical comorbidities and other health outcomes in Brazil. Int J Geriatr Psychiatry. 2016;31(2):176–85.CrossRefPubMedGoogle Scholar 51. Rochanathimoke O, Riewpaiboon A, Postma MJ, Thinyounyong W, Thavorncharoensap M. Health related quality of life impact from rotavirus diarrhea on children and their family caregivers in Thailand. Expert Rev Pharmacoecon Outcomes Res. 2018;18(2):215–22.CrossRefPubMedGoogle Scholar 52. Brisson M, Senecal M, Drolet M, Mansi JA. Health-related quality of life lost to rotavirus-associated gastroenteritis in children and their parents: a Canadian prospective study. Pediatr Infect Dis J. 2010;29(1):73–5.CrossRefPubMedGoogle Scholar 53. Al-Janabi H, Van Exel J, Brouwer W, Trotter C, Glennie L, Hannigan L, et al. Measuring health spillovers for economic evaluation: a case study in meningitis. Health Econ. 2016;25(12):1529–44.CrossRefPubMedGoogle Scholar 54. Acaster S, Perard R, Chauhan D, Lloyd AJ. A forgotten aspect of the NICE reference case: an observational study of the health related quality of life impact on caregivers of people with multiple sclerosis. BMC Health Serv Res. 2013;13:346.CrossRefPubMedPubMedCentralGoogle Scholar 55. Gupta S, Isherwood G, Jones K, Van Impe K. Assessing health status in informal schizophrenia caregivers compared with health status in non-caregivers and caregivers of other conditions. BMC Psychiatry. 2015;15:162.CrossRefPubMedPubMedCentralGoogle Scholar 56. Persson J, Levin L-A, Holmegaard L, Redfors P, Jood K, Jern C, et al. Stroke survivors’ long-term QALY-weights in relation to their spouses’ QALY-weights and informal support: a cross-sectional study. Health Qual Life Outcomes. 2017;15(1):150.CrossRefPubMedPubMedCentralGoogle Scholar 57. Persson J, Aronsson M, Holmegaard L, Redfors P, Stenlof K, Jood K, et al. Long-term QALY-weights among spouses of dependent and independent midlife stroke survivors. Qual Life Res. 2017;26(11):3059–68.CrossRefPubMedPubMedCentralGoogle Scholar 58. Nogueira JM, Rodriguez-Miguez E. Using the SF-6D to measure the impact of alcohol dependence on health-related quality of life. Eur J Health Econ. 2015;16(4):347–56.CrossRefPubMedGoogle Scholar 59. Sjolander C, Rolander B, Järhult J, Mårtensson J, Ahlstrom G. Health-related quality of life in family members of patients with an advanced cancer diagnosis: a one-year prospective study. Health Qual Life Outcomes. 2012;10:89.CrossRefPubMedPubMedCentralGoogle Scholar 60. Angelis A, Kanavos P, Lopez-Bastida J, Linertova R, Nicod E, Serrano-Aguilar P, et al. Social and economic costs and health-related quality of life in non-institutionalised patients with cystic fibrosis in the United Kingdom. BMC Health Serv Res. 2015;15:428.CrossRefPubMedPubMedCentralGoogle Scholar 61. van Andel J, Westerhuis W, Zijlmans M, Fischer K, Leijten FSS. Coping style and health-related quality of life in caregivers of epilepsy patients. J Neurol. 2011;258(10):1788–94.CrossRefPubMedPubMedCentralGoogle Scholar 62. Kurien M, Andrews RE, Tattersall R, McAlindon ME, Wong EF, Johnston AJ, et al. Gastrostomies preserve but do not increase quality of life for patients and caregivers. Clin Gastroenterol Hepatol. 2017;15(7):1047–54.CrossRefPubMedGoogle Scholar 63. van Exel NJ, Koopmanschap MA, van den Berg B, Brouwer WB, van den Bos GA. Burden of informal caregiving for stroke patients. Identification of caregivers at risk of adverse health effects. Cerebrovasc Dis. 2005;19(1):11–7.CrossRefPubMedGoogle Scholar 64. Brouwer WBF, van Exel NJA, van Gorp B, Redekop WK. The CarerQol instrument: a new instrument to measure care-related quality of life of informal caregivers for use in economic evaluations. Qual Life Res. 2006;15(6):1005–21.CrossRefPubMedGoogle Scholar 65. Lutomski JE, van Exel NJA, Kempen GIJM, Moll van Charante EP, den Elzen WPJ, Jansen APD, et al. Validation of the Care-Related Quality of Life Instrument in different study settings: findings from The Older Persons and Informal Caregivers Survey Minimum DataSet (TOPICS-MDS). Qual Life Res. 2015;24(5):1281–93.CrossRefPubMedGoogle Scholar 66. del Rio Lozano M, Garcia-Calvente MDM, Calle-Romero J, Machon-Sobrado M, Larranaga-Padilla I. Health-related quality of life in Spanish informal caregivers: gender differences and support received. Qual Life Res. 2017;26(12):3227–38.CrossRefPubMedGoogle Scholar 67. Oldenkamp M, Hagedoorn M, Wittek R, Stolk R, Smidt N. The impact of older person’s frailty on the care-related quality of life of their informal caregiver over time: results from the TOPICS-MDS project. Qual Life Res. 2017;26(10):2705–16.CrossRefPubMedPubMedCentralGoogle Scholar 68. Hoefman R, Payakachat N, van Exel J, Kuhlthau K, Kovacs E, Pyne J, et al. Caring for a child with autism spectrum disorder and parents’ quality of life: application of the CarerQol. J Autism Dev Disord. 2014;44(8):1933–45.PubMedPubMedCentralGoogle Scholar 69. Khanna R, Jariwala K, Bentley JP. Psychometric properties of the EuroQol Five Dimensional Questionnaire (EQ-5D-3L) in caregivers of autistic children. Qual Life Res. 2013;22(10):2909–20.CrossRefPubMedGoogle Scholar 70. Khanna R, Jariwala K, Bentley JP. Health utility assessment using EQ-5D among caregivers of children with autism. Value Health. 2013;16(5):778–88.CrossRefPubMedGoogle Scholar 71. Vrettos I, Kamposioras K, Kontodimopoulos N, Pappa E, Georgiadou E, Haritos D, et al. Comparing health-related quality of life of cancer patients under chemotherapy and of their caregivers. ScientificWorldJournal. 2012;2012:135283.CrossRefPubMedPubMedCentralGoogle Scholar 72. Bradshaw LE, Goldberg SE, Schneider JM, Harwood RH. Carers for older people with co-morbid cognitive impairment in general hospital: characteristics and psychological well-being. Int J Geriatr Psychiatry. 2013;28(7):681–90.CrossRefPubMedGoogle Scholar 73. Payakachat N, Tilford JM, Brouwer WB, van Exel NJ, Grosse SD. Measuring health and well-being effects in family caregivers of children with craniofacial malformations. Qual Life Res. 2011;20(9):1487–95.CrossRefPubMedGoogle Scholar 74. Chevreul K. Social/economic costs and health-related quality of life in patients with cystic fibrosis in Europe. Eur J Health Econ. 2016;17:s7–18.CrossRefGoogle Scholar 75. Chevreul K, Berg Brigham K, Michel M, Rault G. Costs and health-related quality of life of patients with cystic fibrosis and their carers in France. J Cyst Fibros. 2015;14(3):384–91.CrossRefPubMedGoogle Scholar 76. Fitzgerald C, George S, Somerville R, Linnane B, Fitzpatrick P. Caregiver burden of parents of young children with cystic fibrosis. J Cyst Fibros. 2018;17(1):125–31.CrossRefPubMedGoogle Scholar 77. Kraijo H, Brouwer W, de Leeuw R, Schrijvers G, van Exel J. The perseverance time of informal carers of dementia patients: validation of a new measure to initiate transition of care at home to nursing home care. J Alzheimers Dis. 2014;40(3):631–42.CrossRefPubMedGoogle Scholar 78. Bell CM, Araki SS, Neumann PJ. The association between caregiver burden and caregiver health-related quality of life in Alzheimer disease. Alzheimer Dis Assoc Disord. 2001;15(3):129–36.CrossRefPubMedGoogle Scholar 79. Fang M, Oremus M, Tarride J-E, Raina P, Canadian Willingness-to-pay Study Group. A comparison of health utility scores calculated using United Kingdom and Canadian preference weights in persons with Alzheimer’s disease and their caregivers. Health Qual Life Outcomes. 2016;14(1):105.CrossRefPubMedPubMedCentralGoogle Scholar 80. Majoni M, Oremus M. Does being a retired or employed caregiver affect the association between behaviours in Alzheimer’s disease and caregivers’ health-related quality-of-life? BMC Res Notes. 2017;10(1):766.CrossRefPubMedPubMedCentralGoogle Scholar 81. Neumann PJ, Sandberg EA, Araki SS, Kuntz KM, Feeny D, Weinstein MC. A comparison of HUI2 and HUI3 utility scores in Alzheimer’s disease. Med Decis Making. 2000;20(4):413–22.CrossRefPubMedGoogle Scholar 82. Oremus M, Tarride J-E, Clayton N, Canadian Willingness-to-Pay Study Group, Raina P. Health utility scores in Alzheimer’s disease: differences based on calculation with American and Canadian preference weights. Value Health. 2014;17(1):77–83.CrossRefPubMedGoogle Scholar 83. Reed C, Barrett A, Lebrec J, Dodel R, Jones RW, Vellas B, et al. How useful is the EQ-5D in assessing the impact of caring for people with Alzheimer’s disease? Health Qual Life Outcomes. 2017;15(1):16.CrossRefPubMedPubMedCentralGoogle Scholar 84. Dahlrup B, Nordell E, Steen Carlsson K, Elmstahl S. Health economic analysis on a psychosocial intervention for family caregivers of persons with dementia. Dement Geriatr Cogn Disord. 2014;37(3–4):181–95.CrossRefPubMedGoogle Scholar 85. Knapp M, King D, Romeo R, Schehl B, Barber J, Griffin M, et al. Cost effectiveness of a manual based coping strategy programme in promoting the mental health of family carers of people with dementia (the START (STrAtegies for RelaTives) study): a pragmatic randomised controlled trial. BMJ. 2013;347:f6342.CrossRefPubMedPubMedCentralGoogle Scholar 86. Orrell M, Yates L, Leung P, Kang S, Hoare Z, Whitaker C, et al. The impact of individual Cognitive Stimulation Therapy (iCST) on cognition, quality of life, caregiver health, and family relationships in dementia: a randomised controlled trial. PLoS Med. 2017;14(3):e1002269.CrossRefPubMedPubMedCentralGoogle Scholar 87. Stewart S, Harvey I, Poland F, Lloyd-Smith W, Mugford M, Flood C. Are occupational therapists more effective than social workers when assessing frail older people? Results of CAMELOT, a randomised controlled trial. Age Ageing. 2005;34(1):41–6.CrossRefPubMedGoogle Scholar 88. Vroomen JM, Bosmans JE, Eekhout I, Joling KJ, Van Mierlo LD, Meiland FJM, et al. The cost-effectiveness of two forms of case management compared to a control group for persons with dementia and their informal caregivers from a societal perspective. PLoS One. 2016;11(9):e0160908.CrossRefGoogle Scholar 89. Tiberg I, Lindgren B, Carlsson A, Hallstrom I. Cost-effectiveness and cost-utility analyses of hospital-based home care compared to hospital-based care for children diagnosed with type 1 diabetes; a randomised controlled trial; results after two years’ follow-up. BMC Pediatr. 2016;16:94.CrossRefPubMedPubMedCentralGoogle Scholar 90. Campbell JD, Whittington MD, Kim CH, VanderVeen GR, Knupp KG, Gammaitoni A. Assessing the impact of caring for a child with Dravet syndrome: results of a caregiver survey. Epilepsy Behav. 2018;80:152–6.CrossRefPubMedGoogle Scholar 91. Cavazza M, Kodra Y, Armeni P, De Santis M, López-Bastida J, Linertová R, et al. Social/economic costs and health-related quality of life in patients with Duchenne muscular dystrophy in Europe. Eur J Health Econ. 2016;17:19–29.CrossRefPubMedGoogle Scholar 92. Chevreul K, Gandré C, Brigham KB, López-Bastida J, Linertová R, Oliva-Moreno J, et al. Social/economic costs and health-related quality of life in patients with fragile X syndrome in Europe. Eur J Health Econ. 2016;17:43–52.CrossRefPubMedGoogle Scholar 93. Chevreul K, Berg Brigham K, Brunn M, des Portes V, Network B-RR. Fragile X syndrome: economic burden and health-related quality of life of patients and caregivers in France. J Intellect Disabil Res. 2015;59(12):1108–20.CrossRefPubMedGoogle Scholar 94. Agren S, Evangelista L, Davidson T, Stromberg A. Cost-effectiveness of a nurse-led education and psychosocial programme for patients with chronic heart failure and their partners. J Clin Nurs. 2013;22(15–16):2347–53.CrossRefPubMedPubMedCentralGoogle Scholar 95. Iqbal J, Francis L, Reid J, Murray S, Denvir M. Quality of life in patients with chronic heart failure and their carers: a 3-year follow-up study assessing hospitalization and mortality. Eur J Heart Fail. 2010;12(9):1002–8.CrossRefPubMedGoogle Scholar 96. Squire L, Glover J, Corp J, Haroun R, Kuzan D, Gielen V. Impact of HF on HRQoL in patients and their caregivers in England: results from the ASSESS study. Br J Cardiol. 2017;24(1):30–4.Google Scholar 97. Cavazza M, Kodra Y, Armeni P, De Santis M, López-Bastida J, Linertová R, et al. Social/economic costs and quality of life in patients with haemophilia in Europe. Eur J Health Econ. 2016;17:53–65.CrossRefPubMedGoogle Scholar 98. Al-Janabi H, Manca A, Coast J. Predicting carer health effects for use in economic evaluation. PLoS One. 2017;12(9):e0184886.CrossRefPubMedPubMedCentralGoogle Scholar 99. Hastrup LH, Van Den Berg B, Gyrd-Hansen D. Do informal caregivers in mental illness feel more burdened? A comparative study of mental versus somatic illnesses. Scand J Public Health. 2011;39(6):598–607.CrossRefPubMedGoogle Scholar 100. Péntek M, Gulácsi L, Brodszky V, Baji P, Boncz I, Pogány G, et al. Social/economic costs and health-related quality of life of mucopolysaccharidosis patients and their caregivers in Europe. Eur J Health Econ. 2016;17:89–98.CrossRefPubMedGoogle Scholar 101. Hoefman R, Al-Janabi H, McCaffrey N, Currow D, Ratcliffe J. Measuring caregiver outcomes in palliative care: a construct validation study of two instruments for use in economic evaluations. Qual Life Res. 2015;24(5):1255–73.CrossRefPubMedGoogle Scholar 102. Carod-Artal FJ, Mesquita HM, Ziomkowski S, Martinez-Martin P. Burden and health-related quality of life among caregivers of Brazilian Parkinson’s disease patients. Parkinsonism Relat Disord. 2013;19(11):943–8.CrossRefPubMedGoogle Scholar 103. Martinez-Martin P, Forjaz MJ, Frades-Payo B, Rusinol AB, Fernandez-Garcia JM, Benito-Leon J, et al. Caregiver burden in Parkinson’s disease. Mov Disord. 2007;22(7):924–1060.CrossRefPubMedGoogle Scholar 104. Martinez-Martin P, Arroyo S, Rojo-Abuin JM, Rodriguez-Blazquez C, Frades B, de Pedro Cuesta J, et al. Burden, perceived health status, and mood among caregivers of Parkinson’s disease patients. Mov Disord. 2008;23(12):1673–80.CrossRefPubMedGoogle Scholar 105. Chevreul K, Berg Brigham K, Clément MC, Poitou C, Tauber M. Economic burden and health-related quality of life associated with Prader–Willi syndrome in France. J Intellect Disabil Res. 2016;60(9):879–90.CrossRefPubMedGoogle Scholar 106. van Dam PH, Achterberg WP, Caljouw MAA. Care-related quality of life of informal caregivers after geriatric rehabilitation. J Am Med Direct Assoc. 2017;18(3):259–64.CrossRefGoogle Scholar 107. Daltio CS, Attux C, Ferraz MB. Willingness to pay in caregivers of patients affected by schizophrenia. J Mental Health Policy Econ. 2017;20(1):3–10.Google Scholar 108. Cramm JM, Strating MMH, Nieboer AP. Satisfaction with care as a quality-of-life predictor for stroke patients and their caregivers. Qual Life Res. 2012;21(10):1719–25.CrossRefPubMedPubMedCentralGoogle Scholar 109. Carod-Artal FJ, Ferreira Coral L, Trizotto DS, Menezes Moreira C. Burden and perceived health status among caregivers of stroke patients. Cerebrovasc Dis. 2009;28(5):472–80.CrossRefPubMedGoogle Scholar 110. Chevreul K, Brigham KB, Gandré C, Mouthon L, Serrano-Aguilar P, Linertová R, et al. The economic burden and health-related quality of life associated with systemic sclerosis in France. Scand J Rheumatol. 2015;44(3):238–46.CrossRefPubMedGoogle Scholar Copyright information © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Authors and Affiliations Eve Wittenberg1Email authorLyndon P. James1Lisa A. Prosser21.Center for Health Decision ScienceHarvard TH Chan School of Public HealthBostonUSA2.Susan B. Meister Child Health Evaluation and Research CenterUniversity of Michigan Medical SchoolAnn ArborUSA


This is a preview of a remote PDF: https://link.springer.com/content/pdf/10.1007%2Fs40273-019-00768-7.pdf

Eve Wittenberg, Lyndon P. James, Lisa A. Prosser. Spillover Effects on Caregivers’ and Family Members’ Utility: A Systematic Review of the Literature, PharmacoEconomics, 2019, 1-25, DOI: 10.1007/s40273-019-00768-7