Effects of physical and mental health on health-state preferences

Choice Defines QALYs: A US Valuation of the EQ-5D-5L

BACKGROUND

The 5-level version of the EQ-5D (EQ-5D-5L) was introduced as an improvement on the original 3-level version (EQ-5D-3L). To date, 6 country-specific value sets have been published for EQ-5D-5L and 9 US value sets have been published for other instruments. Our aims were to (1) produce EQ-5D-5L values on a quality-adjusted life year (QALY) scale from the perspective of US adults and (2) compare them with US EQ-5D-3L values and the other country-specific EQ-5D-5L values.

METHODS

In 2016, 8222 US respondents from all 50 states and Washington, DC completed an online survey including a discrete choice experiment with 20 paired comparisons. Each comparison asked respondents, "Which do you prefer?" regarding a pair of alternatives described using EQ-5D-5L and lifespan attributes. On the basis of more than 50 choices on each of the 3160 pairs, we estimated EQ-5D-5L values on a QALY scale and compared them with the US EQ-5D-3L values and the other country-specific EQ-5D-5L values.

RESULTS

Ranging from -0.287 (55555) to 0.992 (11121) on a QALY scale, the estimated EQ-5D-5L values were similar to the US EQ-5D-3L values. Compared with the US EQ-5D-3L values, the values exhibited greater sensitivity and specificity and higher correlation with the EQ-5D-5L values of other countries, particularly England.

CONCLUSIONS

Like previous US valuation studies, this study produced nationally representative EQ-5D-5L values on a QALY scale. The results further demonstrate the advantages of the EQ-5D-5L over its 3-level predecessor as a preference-based summary measure of health-related quality of life from the perspective of US adults.

Exploring health preferences in sociodemographic and health related groups through the paired comparison of the items of the Nottingham health profile

BACKGROUND

Preference weighted measures of health related quality of life are necessary for cost effectiveness calculations involving quality of life adjustment. There are conflicting data about the influence of factors such as sociodemographic and health related variables on health preferences.

STUDY OBJECTIVE

The relative values attached to the items of the Spanish version of the Nottingham Health Profile (NHP) were assessed to make comparisons across social and health subgroups.

DESIGN AND PARTICIPANTS

Preference values were obtained in sets of 250 to 253 persons (total n=1258) using the method of paired comparisons after all possible pairs of NHP items had been presented to respondents for judgement of severity. chi(2) Tests and Spearman's correlations among item ranks were calculated.

MAIN RESULTS

Findings show that preferences elicited with the method of paired comparisons are consistent and independent of the sample from which they are obtained (mean correlation coefficients across subgroups range from 0.87 to 0.96). Conclusion-The evaluation of health did not seem to be related to sociodemographic variables (gender, age, social class) or to the health status of the respondents, suggesting that health preferences are stable across different populations.

Elderly adults' preferences for life-sustaining treatments: the role of impairment, prognosis, and pain

Elderly adults' preferences for life-sustaining treatment are known to vary by type of medical condition and treatment. Less is known about how treatment preferences vary based on underlying health dimensions, such as the nature of the impairment, prognostic information, and the experience of pain. Fifty elderly adults stated preferences for 4 life-sustaining treatments in response to 4 pairs of health state scenarios. Overall, life-sustaining treatments were preferred less in response to (a) cognitive versus physical impairment, (b) when the prognosis described no chance versus a very slight chance of recovery/improvement, and (c) if pain was present. These findings have implications for the way in which preferences for life-sustaining treatments are recorded in advance directives. Historically, advance directives have been limited by overly broad or overly specific statements about treatment preferences. Recording underlying health dimensions that guide treatment decisions may allow decision makers to generalize and apply patient preferences to novel health conditions.

A cardiovascular extension of the Health Measurement Questionnaire

OBJECTIVE

To investigate the psychometric properties of a cardiovascular extension of an existing utility-based quality of life questionnaire (Health Measurement Questionnaire). The new instrument has been named the Utility Based Quality of life--Heart questionnaire, or UBQ-H.

DESIGN

Explored the test-retest reliability, construct validity, and responsiveness of the UBQ-H.

PATIENTS

A sample of 322 patients attending cardiac outpatient clinics were recruited from two large metropolitan teaching hospitals. A second sample of 1112 patients taking part in the LIPID trial was also used to investigate the validity and responsiveness of the UBQ-H.

RESULTS

Ninety per cent of all UBQ-H questionnaires were returned, and item completion rates were high (median of less than 1% missing or N/A answers). Cronbach's alpha measure of internal consistency for the scales ranged between 0.79-0.91, and each item was also most strongly correlated with its hypothesised domain than alternative domains. The intra-class test-retest reliability of the UBQ-H scales ranged from 0.65 to 0.81 for patients with stable health. Results supported the construct validity of the UBQ-H. The UBQ-H was significantly correlated with other information on quality of life (for example, General Health Questionnaire) as anticipated. The instrument was able to distinguish between contrasted groups of patients (for example, with versus without symptoms of dyspnoea, prior myocardial infarction versus none, etc), and was responsive to changes in health associated with adverse events requiring hospitalisation.

CONCLUSIONS

The modifications made to the Health Measurement Questionnaire has resulted in an assessment designed for cardiovascular patients that has proved to be both reliable and valid.

Development of a direct weighting procedure for quality of life domains

The Schedule for the Evaluation of Individual Quality of Life allows individuals to nominate the domains they consider most important to their quality of life and to use their own value system when describing the functional status and relative importance of those domains. The weights for domain importance are derived through a procedure called judgement analysis. As judgement analysis is impractical for individuals with cognitive impairment and in many clinical situations, a shorter, direct weighting procedure has been developed. To test the new procedure, 40 healthy individuals completed both direct and judgement analysis weightings, at t1 and 7-10 days later (t2). After a further 7-10 days (t3), they were asked to identify the weight profiles they had previously produced using each method. The weights produced by the two methods differed on average by 7.8 points at t1 and 7.2 points at t2. The direct weights changed on average by 4.5 points from t1 to t2, while the judgement analysis weights changed by 8.4 points. At t2, 55% of individuals were able to identify the direct weights they had previously produced. The new procedure demonstrates stability and validity but is not interchangeable with judgement analysis. The most appropriate ways of using and interpreting both procedures are discussed.

Judgment processes for medication acceptance: self-reports and configural information use

In the present study college student (N = 186) made judgments of the likelihood of accepting a medication for treatment of a hypothetically experienced clinical depression. Three types of information were manipulated: effectiveness of the medication for alleviating the symptoms of depression, potential side effects of the medication, and severity of depression hypothetically being experienced. The functional-measurement approach was used to examine whether self-reports are related to judgments and whether there is configurality in judging likelihood of medication acceptance. The results showed that subjects who reported different variables to be most important had predictably different effects of the variables in their judgments. There was also evidence for configural combination of information, and the nature of the configurality differed between subjects who reported Depression versus Side Effects as the most important type of information, respectively. The results show how the same information can be used differently by different individuals in making judgments, and that self-reports may reveal some important aspects of how information is used. The implications of the individual differences for health care consumer decision making and health care professionals' assessments and interventions are discussed.

Relationship between psychometric and utility-based approaches to the measurement of health-related quality of life

This paper summarizes selected evidence pertaining to the relationship between psychometric health status measures and utility/preference measures of health outcome. Few studies contain measures of both health status and utility/preference. The evidence to date suggests that various health status measures are at best only moderately correlated with standard gamble (SG) and time trade-off (TTO) utilities. Results from regression analysis, predicting SG or TTO utilities from combinations of health status scales, typically have an R2 of 0.18 to 0.43. Preferences determined by rating scale methods are more strongly related to health status scores, but correlations are variable ranging from 0.17 to 0.46 and only about 27% to 34% of variance can be explained in regression models. The Quality of Well-Being Scale and other multi-attribute preference measures have low to moderate correlations with health status measures (r = 0.03 to 0.71). Health utility/preference measures and psychometric health status scores are only moderately correlated. Health utility and psychometric health status scales may measure different attributes of health. Although both approaches are useful for evaluating medical outcomes, they are not interchangeable indicators of health-related quality of life.

Cancer patients' evaluations of their current health states: the influences of expectations, comparisons, actual health status, and mood

A study was done to determine the extent to which patients' subjective evaluations of their current health are determined by their expectations, their actual health, and how they compare themselves with others. At the initiation of radiation therapy, 61 laryngeal cancer patients described the health status they expected at the end of therapy, using standardized and individualized dimensions. Objective summative scores were derived for these descriptions. At the end of therapy, these respondents described their current health status and the status they believed others their age were experiencing, on the same dimensions, and objective summative scores were derived for these actual and social comparison states. Rating scales and standard gambles were used to obtain values and utilities ("subjective evaluations") for current health at the end of therapy. Multiple linear regression was used to determine the extent to which variation in the subjective evaluations was explained by the objective scores for actual, expected, and social comparison states, under these different methodologic conditions. Actual health state was a consistently significant predictor. Most variance was explained in the model using individualized dimensions and value scores (r2 = 46.0%). Further investigation is needed to determine whether differences in the amounts of variance explained are due to aversion to gambling, dimension salience, order effects, or respondent fatigue.

Methodology for measuring health-state preferences--I: Measurement strategies

Values play a critical part in decision making at both the individual and policy levels. Numerous methodologies for determining the preferences of individuals and groups have been proposed, but agreement has not been reached regarding their scientific adequacy and feasibility. This is the first of a four-part series of papers that analyzes and critiques the state-of-the-art in measuring preferences, particularly the measurement of health-state preferences. In this first paper we discuss the selection of relevant attributes to comprise the health-state descriptions, and the relative merits of three measurement strategies: holistic, explicitly decomposed, and statistically inferred decomposed. The functional measurement approach, a statistically inferred decomposed strategy, is recommended because it simultaneously validates the process by which judges combine attributes, the scale values they assign to health states, and the interval property of the scale.

Methodology for measuring health-state preferences--II: Scaling methods

This paper begins with a discussion of measurement principles relevant to determining health-state preferences. Six scaling methods are described and evaluated on the basis of their reliability, validity, and feasibility. They are the standard gamble, time trade-off, rating scale, magnitude estimation, equivalence, and willingness-to-pay methods. Reliability coefficients for most methods are acceptable although the low coefficients for measurements taken a year apart suggest that preferences change over time. Convergent validity among methods has been supported in some but not all studies, and there are limited data supporting hypothetical relationships between preferences and other variables. The category ratings method is easiest to administer and appears to yield valid scale values; thus, it is recommended for large-sample studies. However, decision-oriented methods, particularly the time trade-off and standard gamble, may be more effective in small-scale investigations and individual decision making.

Psychosocial status in chronic illness. A comparative analysis of six diagnostic groups

Assumptions that psychological attributes are specific to particular diagnoses characterize many investigations of chronically ill patients. We studied 758 patients, each of whom had one of six different chronic illnesses, to determine and compare their scores on the Mental Health Index. Five groups of physically ill patients (with arthritis, diabetes, cancer, renal disease, or dermatologic disorders) did not differ significantly from one another or from the general public, but all had significantly higher scores for psychological status when compared with the sixth group, patients under treatment for depression. There was a significant direct relation between higher mental-health scores and advancing age across all patient populations. Patients with recently diagnosed illness in all groups had poorer mental-health scores than did patients whose illness had been diagnosed more than four months previously. A direct relation between declining physical status and mental-health scores was observed. These results suggest that psychological adaptation among patients with chronic illnesses is remarkably effective and fundamentally independent of specific diagnosis.

Methodology in behavioral and psychosocial cancer research. Conceptualizing disease impact and treatment outcomes

The focus of assessment of disease impact is moving beyond survival and biomedical outcomes to include a comprehensive set of health status and quality of life concepts. We have discussed four socially relevant concepts that can be thought of as dimensions of health status or well being: physiologic status, personal (physical) functioning, mental health, and social well-being. Quality of life was also discussed briefly as a very global concept encompassing these health status dimensions and a broader set of concepts including finances, housing, and employment. Five categories of measures based on manifest content were also discussed, including measures of disease/diagnostic status, personal functioning, mental health, general health perceptions, and social/role functioning. The physiologic dimension of health is very heterogeneous and includes many concepts and measures that vary largely independently of each other and that differ in terms of their impact on the other dimensions of health status. The physical, mental, and social dimensions of health and well-being also can be measured many different ways, and each can be broken down into distinct concepts that may vary in importance from one study to another. Of these three concepts, social well-being is the most heterogeneous. To assist investigators searching for valid measures of specific health status and quality of life concepts, we recommended formal estimations of measurement models. A preliminary model of 15 health status measures was presented to illustrate the usefulness of such a model.