Lisa A. Prosser

If your parents are in their 80s, you probably have a conditioned response to middle-of-the-night phone calls: “What happened?” The first time, it may be your father who’s in trouble, and your mother is calling from the hospital. When he returns home, she becomes the de facto caregiver, despite being equally elderly and hardly up for the responsibility. The next phone call may be about your mother — perhaps she’s had a fall, and your sibling is calling from the hospital. Now, care becomes more complicated: the siblings negotiate, one of your sisters volunteers to take primary responsibility, even move in, and her life changes. She cuts back to part-time work and takes over managing your parents’ medications, appointments, and checkbook. Each successive call brings more responsibilities and decisions — a home health aide, a life alert bracelet, equipping their home with grab bars and nonslip floors, working out coverage during your sister’s trips and vacations. Resources become strained, emotional health is challenged, and sometimes physical health suffers.

Background: Utilities are the quantification of the perceived quality of life associated with any health state. They are used to calculate QALYs, the outcome measure in cost-utility analysis. Generally measured through surveys of individuals, utilities often contain apparent or unapparent errors that can bias resulting values and QALYs calculated from these values. Objective: The aim of this study was to improve direct health utility elicitation methodology through the identification of the types of survey responses that indicate errors and objections, and the reasons underlying them. Methods: We conducted a systematic review of the medical (PubMed), economics (EconLit) and psychology (PsycINFO) literature from 1975 through June 2010 for articles describing the types and frequency of errors and objections in directly elicited utility survey responses, and strategies to address these responses. Primary data were collected through an internet-based utility survey (standard gamble) of community members to identify responses that indicate error or objections. A qualitative telephone survey was conducted among a subset of respondents with these types of responses using an open-ended protocol to elicit rationales for them. Results: A total of 11 papers specifically devoted to errors, objections and invariance in utility responses have been published since the mid-1990s. Error/objection responses can be broadly categorized into ordering errors (which include illogical and inconsistent responses) and objections/invariance (which include missing data, protest responses and refusals to trade time or risk in utility questions). Reported frequencies of respondents making ordering errors ranged from 5% to 100%, and up to 35% of respondents have been reported as objecting to the survey or task in some manner. Changes in the design, administration and analysis of surveys can address these potentially problematic responses. Survey data (n = 398) showed that individuals who provided invariant responses (n = 26) reported the lowest level of difficulty with the survey and often identified as religious (23% of invariant responders found the survey difficult vs 63% of all responders, and 77% of invariant responders identified as religious compared with 56% of entire sample; p < 0.05 for both). Respondents who provided illogical responses (n = 50) were less likely to be college educated (56% of illogical responders vs 73% of entire sample; p < 0.05), and less likely to be confident in their responses (62% vs 75% of entire sample; p < 0.05). Qualitative interviews (n = 42) following the survey revealed that the majority of ordering errors were a result of confusion, lack of attention or difficulty in responding to the survey on the part of the respondent, while invariant responses were often considered and thoughtful reactions to the premise of valuing health using the standard gamble task. Conclusions: Rationales for error/objection responses include difficulty in articulating preferences or misunderstanding with a complex survey task, and also thoughtful and considered protestations to the task. Mechanisms to correct unintentional errors may be useful, but cannot address intentional responses to elements of the measurement task. Identification and analysis of the prevalence of errors and objections in responses in utility data sets are essential to understanding the accuracy and precision of utility estimates and analyses that depend thereon.

Child maltreatment causes substantial morbidity and mortality in the U.S. Morbidity associated with child maltreatment can reduce health-related quality of life. Accurately measuring the reduction in quality of life associated with child maltreatment is essential to the economic evaluation of educational programs and interventions to reduce the incidence of child maltreatment. The objective of this study was to review the literature for existing approaches and instruments for measuring quality-of-life for child maltreatment outcomes.

Objective . To evaluate differences in risk attitude across the domains of health and money for 2 types of respondents, patients and community members. Methods . Two groups of respondents, patients with multiple sclerosis (n = 56) and members of the general community (n = 57), completed a survey that collected information on risk attitudes and socioeconomic and clinical variables (e.g., disability level). Risk attitude was measured using 2 standard-gamble questions on money and 1 standard-gamble question on health outcomes. Multivariate regression was used to evaluate the relationship between risk attitude and respondent type (patient v. community), adjusting for covariates that could affect risk attitude. Results . The median certainty equivalents for money gambles were significantly different from and less than the expected value of the gamble for both types of respondents. Median certainty equivalents for the health gamble were not significantly different from the expected value for either group of respondents. For all 3 gambles, there was no difference in median certainty equivalents between the 2 types of respondents in both unadjusted and adjusted analyses. Conclusions . Risk attitude varied across domains but not by respondent type. Patients and community members were predominantly risk neutral with respect to health outcomes and risk averse with respect to money. Research on risk preferences on money outcomes may not be an appropriate proxy for risk preferences regarding health outcomes. Risk preferences may depend more on characteristics of the choice than on respondent type.

The objective of this review was to analyse the methods of paediatric and adult cost-utility analyses (CUAs) conducted in US populations, and to compare the cost-utility ratios of health interventions by classifying them by disease prevention stage, intervention category and primary disease type. A CUA database developed by the Tufts-New England Medical Center, Boston, MA, USA was used to compare the descriptive and methodological characteristics of paediatric and adult studies. The final dataset included 35 paediatric and 491 adult studies, which generated a total of 91 paediatric and 1498 adult cost-utility ratios. In paediatric studies, the most common intervention types were immunisations and pharmaceutical interventions, which each accounted for 17% of studies. Pharmaceutical interventions accounted for the plurality of adult studies (36%). In studies that used a single source of preferences to determine quality-of-life weights, preferences most frequently came from the author in paediatric studies (29%) and the patient in adult studies (14%). Almost all studies with available discount rate data used the same rate (most commonly 3%) for costs and benefits. Few studied used generic health-state classification instruments; preferences for health states were most often based on author and community preferences in paediatric studies, and author and patient preferences in adult studies. The overall median cost-utility ratio was $US7300/QALY (year 2002 values) in child studies and $US26 000/QALY in adult studies; child studies tended to have lower published cost-utility ratios than adult studies, even when categorised according to intervention or disease. In conclusion, CUAs of paediatric and adult health interventions vary across descriptive characteristics, but are largely similar methodologically. Further, costutility ratios for interventions evaluated in the literature tend to be lower for paediatric interventions than for adult ones. When allocating resources, policy makers who use economic analysis as a decision-making aid can take some comfort in the methodological similarities between paediatric and adult studies, but more work is required to standardise methods in both groups.

Valuing the health of children for cost-utility or cost-benefit analysis poses a number of additional challenges when compared with valuing adult health. Some of these challenges relate to the inability of young children to value changes in health directly and the potential biases associated with using proxy respondents. Other challenges arise from children not being able to perform as independent economic actors, but dependent on others for care and decision making. In addition, illness in children may affect parent/caregiver quality of life, further complicating the measurement of value associated with a change in a child’s health status. We review the most common approaches (QALYs and willingness-to-pay values) for valuing health in economic evaluations and consider the methodological and practical issues associated with measuring child health using each framework. Recommendations for advancing the field of valuing child health for economic evaluations will vary by age; a ‘one size fits all’ approach does not readily fit. Although limitations exist for all of the methods considered for valuing child health, the currently recommended approach for infants and preschoolers is direct valuation by a proxy respondent. For school-age children and adolescents, existing multi-attribute instruments can be applied in some situations but direct valuation may be required for others. Future research should focus on minimising bias from proxy respondents, consideration of a family- or household-based approach to valuing health effects, and development of generic instruments with domains that are appropriate to children and that vary with age.

We estimated cost-effectiveness of annually vaccinating children not at high risk with inactivated influenza vaccine (IIV) to range from US $12,000 per quality-adjusted life year (QALY) saved for children ages 6–23 months to $119,000 per QALY saved for children ages 12–17 years. For children at high risk (preexisting medical conditions) ages 6–35 months, vaccination with IIV was cost saving. For children at high risk ages 3–17 years, vaccination cost $1,000–$10,000 per QALY. Among children not at high risk ages 5–17 years, live, attenuated influenza vaccine had a similar cost-effectiveness as IIV. Risk status was more important than age in determining the economic effects of annual vaccination, and vaccination was less cost-effective as the child's age increased. Thus, routine vaccination of all children is likely less cost-effective than vaccination of all children ages 6–23 months plus all other children at high risk.

Influenza vaccination recently has been recommended for children 6–23 months old, but is not currently recommended for routine use in non-high-risk older children. Information on disease impact, costs, benefits, risks, and community preferences could help guide decisions about which age and risk groups should be vaccinated and strategies for improving coverage. The objective of this study was to measure preferences and willingness-to-pay for changes in health-related quality of life associated with uncomplicated influenza and two rarely-occurring vaccination-related adverse events (anaphylaxis and Guillain-Barré syndrome) in children.

Objective. To measure parents’ and other adults’ values for preventing disease associated with pneumococcal infection and to evaluate how including these values changes the economic appraisal of pneumococcal conjugate vaccine. Methods. Data on preferences and willingness to pay to reduce risk of illness were collected for 6 illnesses that are preventable by pneumococcal conjugate vaccine (simple otitis media, complex otitis media, moderate pneumonia, severe pneumonia, bacteremia, and meningitis) and 1 vaccine-related adverse event (fever and fussiness after vaccine). Interviews were conducted with 2 groups of respondents: 1) parents of children who had experienced 1 or more of the outcomes described in the survey (n = 101) and 2) a US community sample (n = 109). The 30-minute telephone interview used modified time trade-off questions and willingness-to-pay questions. Values from the interview were incorporated in an existing decision-analytic model that simulated the cost-effectiveness and cost-benefit of pneumococcal conjugate vaccine in a hypothetical cohort of newborns. Results. Among parents, the median amount of time that respondents said that they would be willing to trade to avoid diseases ranged from 0 days for otitis media to 1 year for severe pneumonia and 2 years for meningitis. Among the US community sample, the median amounts of time traded were higher, ranging from 7 days for otitis media to 3 years for meningitis. Median willingness-to-pay amounts varied from $100 to prevent 1 episode of otitis media and $500 to reduce the risk of meningitis from 21 in 100 000 to 6 in 100 000 and were similar between parents and community members. Incorporating time trade-off amounts into the existing economic model for pneumococcal conjugate vaccine resulted in cost-effectiveness ratios <$10 000 per quality-adjusted life year at a vaccine cost of $58 per dose. Conclusions. Both parents and community members assign relatively high values to preventing meningitis, pneumonia, and complex otitis media. When the value of preventing pneumococcal diseases is incorporated into economic analyses, pneumococcal conjugate vaccine has a cost-effectiveness ratio in the range of other widely used health interventions.