Broadening the Measurement and Valuation of Health and Quality of Life

University of Technology Sydney. Faculty of Business.Economic evaluation is an important tool in health care resource allocation. Interventions are typically evaluated through a cost utility analysis (CUA) using the Quality Adjusted Life Year (QALY), a metric combining length of life and quality of life (QoL) into a single outcome. The quality aspect of the QALY is often provided by a preference-based measure (PBM) that includes a way of measuring health, and a preference-based value set. The most commonly used PBMs focus on health-related quality of life (HRQoL). However, there is a case for broadening what is measured and valued by including other aspects of QoL (such as social care related QoL) alongside HRQoL. This thesis explores how methods for the measurement and valuation of health and QoL can be extended to inform the development of broader and more widely applicable instruments. This was investigated by first exploring how to incorporate QoL concepts into PBMs, and second by testing the further application of Discrete Choice Experiment (DCE) methods to value QoL. Three empirical studies were conducted The first study assessed existing measures of health and QoL using Item Response Theory (IRT), and tested two ways in which PBMs could be broadened to incorporate wider QoL concepts. The results demonstrated overlap and divergence in what is measured. This informed where extra dimensions of QoL could broaden the information collected, and how the information collected within existing HRQoL frameworks could be extended. The second study used DCE to understand respondent preferences for diverse dimensions of QoL. The results provided evidence respondents do trade across different concepts of QoL. This supports the need for broader measures, and also the use of DCE to value broader outcomes. The third study focuses on DCE methods, and particularly on the construction of designs for DCEs. The results provided detailed information about different design strategies for the valuation of QoL outcomes. The overall findings raise key issues about what should be captured in PBMs, and also provide novel information about methods that can be used to inform the assessment, development and valuation of future instruments. For example, the results inform how IRT can be used in PBM development. They also suggest how DCE can be used to value diverse QoL concepts. This can inform the development and valuation of broader measurement systems of QoL outcomes that can increase the scope and enhance the applicability of QALY values used in resource allocation decision making

How are debriefing questions used in health discrete choice experiments? An online survey

We thank the respondents who completed our survey. This work was funded by a University of Technology Sydney Faculty of Business Research Grant 2017. Alison M. Pearce was supported by a University of Technology Sydney Chancellor’s Postdoctoral Research Fellowship.Peer reviewedPostprin

Comparing Generic and Condition-Specific Preference-Based Measures in Epilepsy: EQ-5D-3L and NEWQOL-6D

Background: There is debate about the psychometric characteristics of the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) for use in epilepsy. In response to the concerns, an epilepsy-specific preference-based measure (NEWQOL-6D) was developed. The psychometric characteristics of the NEWQOL-6D, however, have not been assessed. Objectives: To investigate the validity and responsiveness of the EQ-5D-3L and the Quality of Life in Newly Diagnosed Epilepsy Instrument-six dimensions (NEWQOL-6D) for use in the assessment of treatments for newly diagnosed focal epilepsy. Methods: The analysis used data from the Standard And New Antiepileptic Drugs trial including patients with focal epilepsy. We assessed convergent validity using correlations, and known-group validity across different epilepsy and general health severity indicators using analysis of variance and effect sizes. The responsiveness of the measures to change over time was assessed using standardized response means. We also assessed agreement between the measures. Results: There was some level of convergence and agreement between the measures in terms of utility score but divergence in the concepts measured by the descriptive systems. Both instruments displayed known-group validity, with significant differences between severity groups, and generally slightly larger effect sizes for the NEWQOL-6D across the epilepsy-specific indicators. Evidence for responsiveness was less clear, with small to moderate standardized response means demonstrating different levels of change across different indicators. Conclusions: There was an overall tendency for the NEWQOL-6D to better reflect differences across groups, but this does not translate into large absolute utility differences. Both the EQ-5D-3L and the NEWQOL-6D show some evidence of validity for providing utility values for economic evaluations in newly diagnosed focal epilepsy

An Integrated Framework for Team Formation and Winner Prediction in the FIRST Robotics Competition: Model, Algorithm, and Analysis

This research work aims to develop an analytical approach for optimizing team formation and predicting team performance in a competitive environment based on data on the competitors' skills prior to the team formation. There are several approaches in scientific literature to optimize and predict a team's performance. However, most studies employ fine-grained skill statistics of the individual members or constraints such as teams with a set group of members. Currently, no research tackles the highly constrained domain of the FIRST Robotics Competition. This research effort aims to fill this gap by providing an analytical method for optimizing and predicting team performance in a competitive environment while allowing these constraints and only using metrics on previous team performance, not on each individual member's performance. We apply our method to the drafting process of the FIRST Robotics competition, a domain in which the skills change year-over-year, team members change throughout the season, each match only has a superficial set of statistics, and alliance formation is key to competitive success. First, we develop a method that could extrapolate individual members' performance based on overall team performance. An alliance optimization algorithm is developed to optimize team formation and a deep neural network model is trained to predict the winning team, both using highly post-processed real-world data. Our method is able to successfully extract individual members' metrics from overall team statistics, form competitive teams, and predict the winning team with 84.08% accuracy

Implausible states: prevalence of EQ-5D-5L states in the general population and its effect on health state valuation

The EQ-5D is made up of health state dimensions and levels, in which some combinations seem less “plausible” than others. If “implausible” states are used in health state valuation exercises, then respondents may have difficulty imagining them, causing measurement error. There is currently no standard solution: some valuation studies exclude such states, whereas others leave them in. This study aims to address 2 gaps in the literature: 1) to propose an evidence-based set of the least prevalent two-way combinations of EQ-5D-5L dimension levels and 2) to quantify the impact of removing perceived implausible states from valuation designs. For the first aim, we use data from 2 waves of the English General Practitioner Patient Survey (n = 1,639,453). For the second aim, we remodel a secondary data set of a Discrete Choice Experiment (DCE) with duration that valued EQ-5D-5L and compare across models that drop observations involving different health states: 1) implausible states as defined in the literature, 2) the least prevalent states identified in stage 1, and 3) randomly select states, alongside 4) a model that does not drop any observations. The results indicate that two-way combinations previously thought to be implausible actually exist among the general population; there are other combinations that are rarer, and removing implausible states from an experimental design of a DCE with duration leads to value sets with potentially different characteristics depending on the criterion of implausible states. We advise against the routine removal of implausible states from health state valuation studies

Preparatory study for the revaluation of the EQ-5D tariff: methodology report.

BACKGROUND: EQ-5D is a widely used generic measure of health with a 'tariff', or preference weights, obtained from the general population, using time trade-off (TTO). PRET (Preparatory study for the Re-valuation of the EQ-5D Tariff project) contributes towards the methodology for its revaluation. METHODS: Stage 1 examined key assumptions typically involved in health-state valuations through a series of binary choice exercises, namely that health-state preferences are independent of (1) duration of the state; (2) whose health it is (i.e. perspective); (3) length of 'lead time' (a mechanism to value all states on the same scale, including those who are worse than being dead); (4) when health events take place (time preference); and (5) satisfaction associated with the state. Further topics addressed were (6) exhaustion of lead time in the worst state; (7) health-state valuation using discrete choice experiments (DCEs) with a duration attribute; and (8) binary choice administration of lead time - time trade-off (LT-TTO). Stage 1 consisted of an online survey with 6000 respondents. Stage 2 compared the results above to those of an identical survey conducted in 200 face-to-face computer-assisted personal interviews (CAPIs), covering topics (1) to (7). Stages 3 and 4 examined - in more detail and depth - issues taken from stage 1. Stage 3 consisted of CAPI surveys of a representative UK sample of 300, using examples of TTO, LT-TTO, and DCE with duration, each followed by extensive feedback questions. Stage 4 was a more intensive exercise involving a qualitative analysis of people's thought processes during both binary choice and iterative health-state valuation exercises. Data were collected through 'think-aloud' methods in 30 interviews of a convenience sample. RESULTS: Stage 1 found that health-state values are not independent of (1) duration of the state but there is no clear pattern; (2) whose health it is; (3) the duration of 'lead time' but there was no clear pattern; (4) when health events take place; or (5) satisfaction associated with the state. Furthermore, (6) exhaustion of lead time in the worst state was subject to substantial framing effects; (7) the five-level version of the EQ-5D (EQ-5D-5L) can be valued using DCE with duration as an attribute; and (8) binary choice LT-TTO can be administered in an online environment. Stage 2 found that although online surveys and CAPI surveys resulted in different compositions of respondents, at the aggregate, their responses to the experimental questions covering (1) to (7) above were not statistically significantly different from each other. Stages 3 and 4 found that TTO and LT-TTO were easier than DCE with duration; respondents did not necessarily trade across all attributes of EQ-5D; some respondents found it difficult to distinguish between the two worst levels of EQ-5D-5L, and some respondents may be thinking about the impact of their ill health on their family. CONCLUSIONS: In order for the National Institute for Health and Care Excellence to make the most appropriate decisions, the EQ-5D tariff needs to incorporate the latest understanding of health-state preferences. PRET contributed to the knowledge base on the conduct of health-state valuation studies. FUNDING: The Medical Research Council (MRC)-National Institute for Health Research (NIHR) Methodology Research Programme funded the PRET project (MRC ref. G0901500), and the EuroQol Group funded the PRET-AS project (Preparatory study for the Re-valuation of the EQ-5D Tariff project - Additional Sample) as an extension to the PRET project with formal agreement from the MRC

Using Discrete Choice Experiment with duration to model EQ-5D-5L health state preferences: Testing experimental design strategies

Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more “difficult” choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised “respondent efficiency”, suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies

Comparison of general population, patient, and carer utility values for dementia health states.

Utility values to estimate quality-adjusted life years (QALYs) for use in cost-utility analyses are usually elicited from members of the general population. Public attitudes and understanding of dementia in particular may mean that values elicited from the general population may differ from patients and carers for dementia health states. This study examines how the population impacts utility values elicited for dementia health states using interviewer-administered time tradeoff valuation of health states defined by the dementia-specific preference-based measures DEMQOL-U (patient-report) and DEMQOL-Proxy-U (carer-report). Eight DEMQOL-U states were valued by 78 members of the UK general population and 71 patients with dementia of mild severity. Eight DEMQOL-Proxy-U states were valued by 77 members of the UK general population and 71 carers of patients with dementia of mild severity. Random-effects generalized least squares regression estimated the impact of population, dementia health state, and respondent sociodemographic characteristics on elicited values, finding that values for dementia health states differed by population and that the difference varied across dementia health states. Patients with dementia and carers of patients with dementia gave systematically lower values than members of the general population that were not due to differences in the sociodemographic characteristics of the populations. Our results suggest that the population used to produce dementia health state values could impact the results of cost-utility analyses and potentially affect resource allocation decisions; yet, currently, only general population values are available for usage

Manipulating the 5 dimensions of the EuroQol instrument: the effects on self-reporting actual health and valuing hypothetical health states

Background. The EQ-5D instrument has 5 dimensions. This article reports on the effects of manipulating a) the order in which the 5 dimensions are presented (appearing first v. last), b) splitting of the composite dimensions (“pain or discomfort” and “anxiety or depression”), and c) removing or “bolting off” 1 of the 5 EQ-5D dimensions at a time. The effects were examined in 2 contexts: 1) self-reporting health and 2) health state valuations. Methods. Three different types of discrete choice experiments (DCE) including a duration attribute were designed. An online survey with 12 subtypes, each with 10 DCE tasks, was designed and completed by 2494 members of the UK general public. Results. Of the 3 manipulations in the self-reporting context, only b) splitting anxiety or depression had a significant effect. In the health state valuation context, b) splitting level 5 pain or discomfort (relative to pain) and splitting level 5 anxiety or depression (relative to anxiety) had significant effects as did c) bolting off dimensions. Conclusions. We find that the values given to certain health dimensions are sensitive to the way in which it is described and the other health dimensions presented. Of particular interest is the effect of splitting composite dimensions: a given EQ-5D(-5L) profile may mean different things depending on whether the profile is used to self-report one’s health or to value hypothetical states, so that the health state values of EQ-5D(-5L) in population tariffs may not correspond to the states that patients self-report themselves in

Measurement invariance of the Functional Assessment of Cancer Therapy—Colorectal quality-of-life instrument among modes of administration

OBJECTIVES: To test for the measurement invariance of the Functional Assessment of Cancer Therapy—Colorectal (FACT-C) in patients with colorectal neoplasms between two modes of administration (self- and interviewer administrations). It is important to establish the measurement invariance of the FACT-C across different modes of administration to ascertain whether it is valid to pool FACT-C data collected by different modes or to assess each group separately. METHODS: A cross-sectional sample of 391 Chinese patients with colorectal neoplasms was recruited from specialist outpatient clinics between September 2009 and July 2010. Confirmatory factor analysis (CFA) was used to test the original five-factor model of the FACT-C on data collected by self- and interviewer administrations in single-group analysis. Multiple-group CFA was then used to compare the factor structure between the two modes of administration using chi-square tests and other goodness-of-fit statistics. RESULTS: The hypothesized five-factor model of FACT-C demonstrated good fit in each group. Configural invariance and metric invariance were fully supported in multiple-group CFA. Some item intercepts and their corresponding error variances were not identical between administration groups, suggesting evidence of partial strict factorial invariance. CONCLUSIONS: Our results confirmed that the five-factor structure of FACT-C was invariant in Chinese patients using both self- and interviewer administrations. It is appropriate to pool or compare data in the emotional well-being and colorectal cancer subscale scores collected by both administrations. Measurement invariance in three items, one from each of the other subscales, may be contaminated by response bias between modes of administration