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Government investment in preparing for pandemics has never been more relevant. The COVID-19 pandemic has stimulated debate regarding the trade-offs societies are prepared to make between health and economic activity. What is not known is: (1) how much the public in different countries are prepared to pay in forgone GDP to avoid mortality from future pandemics; and (2) which health and economic policies the public in different countries want their government to invest in to prepare for and respond to the next pandemic. Using a future-focused, multi-national discrete choice experiment, we quantify these trade-offs and find that the tax-paying public is prepared to pay $3.92 million USD (Canada), $4.39 million USD (UK), $5.57 million USD (US) and $7.19 million USD (Australia) in forgone GDP per death avoided in the next pandemic. We find the health policies that taxpayers want to invest in before the next pandemic and the economic policies they want activated once the next pandemic hits are relatively consistent across the countries, with some exceptions. Such results can inform economic policy responses and government investment in health policies to reduce the adverse impacts of the next pandemic.

In this multi-center longitudinal cohort study conducted in Australia and New Zealand, we assessed the trajectories of health-related quality of life (HRQoL) in children with chronic kidney disease (CKD) over time. A total of 377 children (aged 6-18 years) with CKD stages 1-5 (pre-dialysis), dialysis, or transplant, were followed biennially for four years. Multi Attribute Utility (MAU) scores of HRQoL were measured at baseline and at two and four years using the McMaster Health Utilities Index Mark 3 tool, a generic multi-attribute, preference-based system. A multivariable linear mixed model was used to assess the trajectories of HRQoL over time in 199 children with CKD stage 1-5, 43 children receiving dialysis and 135 kidney transplant recipients. An interaction between CKD stage at baseline and follow-up time indicated that the slopes of the HRQoL scores differed between children by CKD stage at inception. Over half of the cohort on dialysis at baseline had received a kidney transplant by the end of year four and the MAU scores of these children increased by a meaningful amount averaging 0.05 (95% confidence interval 0.01 to 0.09) per year in comparison to those who were transplant recipients at baseline. The mean difference between baseline and year two MAU scores was 0.09 (95% confidence interval -0.05, 0.23), (Cohen's d effect size 0.31). Thus, improvement in HRQoL over time of children on dialysis at baseline was likely to have been driven by their transition from dialysis to transplantation. Additionally, children with CKD stage 1-5 and transplant recipients at baseline had no changes in their disease stage or treatment modality and experienced stable HRQoL over time.

This study undertook a head-to-head comparison of best-worst, best-best and ranking discrete choice experiments (DCEs) to help decide which method to use if moving beyond traditional single-best DCEs. Respondents were randomized to one of three preference elicitation methods. Rank-ordered (exploded) mixed logit models and respondent-reported data were used to compare methods and first and second choices. First choices differed from second choices and preferences differed between elicitation methods, even beyond scale and scale dynamics. First choices of best-worst had good choice consistency, scale dynamics and statistical efficiency, but this method's second choices performed worst. Ranking performed best on respondent-reported difficulty and preference; best-best's second choices on statistical efficiency. All three preference elicitation methods improve efficiency of data collection relative to using first choices only. However, differences in preferences between first and second choices challenge moving beyond single-best DCE. If nevertheless doing so, best-best and ranking are preferred over best-worst DCE.

Background The Paediatric Quality of life Inventory (PedsQLTM) Generic Core Scales and the Child Health Utilities 9 Dimensions (CHU9D) are two paediatric health-related quality of life (HRQoL) measures commonly used in overweight and obesity research. However, no studies have comprehensively established the psychometric properties of these instruments in the context of paediatric overweight and obesity. The aim of this study was to assess the reliability, acceptability, validity and responsiveness of the PedsQL and the CHU9D in the measurement of HRQoL among children and adolescents living with overweight and obesity. Subjects/Methods Subjects were 6544 child participants of the Longitudinal Study of Australian Children, with up to 3 repeated measures of PedsQL and CHU9D and aged between 10 and 17 years. Weight and height were measured objectively by trained operators, and weight status determined using World Health Organisation growth standards. We examined reliability, acceptability, known group and convergent validity and responsiveness, using recognised methods. Results Both PedsQL and CHU9D demonstrated good internal consistency reliability, and high acceptability. Neither instrument showed strong convergent validity, but PedsQL appears to be superior to the CHU9D in known groups validity and responsiveness. Compared with healthy weight, mean (95%CI) differences in PedsQL scores for children with obesity were: boys −5.6 (−6.2, −4.4); girls −6.7 (−8.1, −5.4) and differences in CHU9D utility were: boys −0.02 (−0.034, −0.006); girls −0.035 (−0.054, −0.015). Differences in scores for overweight compared with healthy weight were: PedsQL boys −2.2 (−3.0, −1.4) and girls −1.3 (−2.0, −0.6) and CHU9D boys: no significant difference; girls −0.014 (−0.026, −0.003). Conclusion PedsQL and CHU9D overall demonstrated good psychometric properties, supporting their use in measuring HRQoL in paediatric overweight and obesity. CHU9D had poorer responsiveness and did not discriminate between overweight and healthy weight in boys, which may limit its use in economic evaluation.

BACKGROUND/AIMS: Discrete choice experiments (DCEs) with either duration included an attribute or with dead included as an option can be used as a stand-alone approach to value health states. This paper reports on a DCE with both of these features to develop an EQ-5D-5L value set for Australia. METHODS: A DCE was undertaken using a large Australian panel of internet respondents, from which a sample of more than 4000 Australian adults was chosen, stratified to be population representative on age and gender. The DCE contained 500 choice triplets, with two EQ-5D-5L health states with duration, and dead as the third option. Each respondent answered 12 choice sets from the 500, stating both the best and worst options from the three available. The design was constructed to estimate a utility algorithm with main effects plus some key interaction terms. A variety of approaches to parameterising interactions, and to anchoring the value set on the required 0-1 scale, were tested. A preferred Australian adult utility algorithm for use in cost-utility analysis was then generated. RESULTS: In total, 4477 people completed at least one choice set and were included in the analysis. The results reflected the monotonic structure of the EQ-5D-5L, in that moving from no problems to extreme problems led to worsening utility in each dimension. Inclusion of interaction terms demonstrates that the disutility of the first dimension moving to a poor level (defined as either level 5, or level 4 or 5) had a large impact, but subsequent dimensions moving to a poor level had a relatively smaller disutility. DISCUSSION: This work develops a value set for the EQ-5D-5L in Australia, and also provides a range of methodological insights which can inform future work using a stand-alone DCE to value health in other countries.

The obesity epidemic is a significant public policy issue facing the international community, resulting in substantial costs to individuals and society. Various policies have been suggested to reduce and prevent obesity, including those informed by standard economics (a key feature of which is the assumption that individuals are rational) and behavioral economics (which identifies and harness deviations from rationality). It is not known which policy interventions taxpayers find acceptable and would prefer to fund via taxation. We provide evidence from a discrete choice experiment on an Australian sample of 996 individuals to investigate social acceptability of eight policies: mass media campaign; traffic light nutritional labeling; taxing sugar sweetened beverages; prepaid cards to purchase healthy food; financial incentives to exercise; improved built environment for physical activity; bans on advertising unhealthy food and drink to children; and improved nutritional quality of food sold in public institutions. Latent class analysis revealed three classes differing in preferences and key respondent characteristics including capacity to benefit. Social acceptability of the eight policies at realistic levels of tax increases was explored using post-estimation analysis. Overall, 78% of the sample were predicted to choose a new policy, varying from 99% in those most likely to benefit from obesity interventions to 19% of those least likely to benefit. A policy informed by standard economics, traffic light labeling was the most popular policy, followed by policies involving regulation: bans on junk food advertising to children and improvement of food quality in public institutions. The least popular policies were behaviorally informed: prepaid cards for the purchase of only healthy foods, and financial incentives to exercise.

BackgroundIn line with affordability and equity principles, Medicare—Australia’s universal health care program—has measures to contain out-of-pocket costs (OOPC), particularly for lower income households. This study examined the distribution of OOPC for Medicare-subsidised out-of-hospital services and prescription medicines in Australian households, according to their ability to pay.MethodsOOPC for out-of-hospital services and medicines in 2017-18 were estimated for each household, using 2016 Australian Census data linked to Medicare Benefits Schedule (MBS) and Pharmaceutical Benefit Scheme (PBS) claims. We derived household disposable income by combining income information from the Census linked to income tax and social security data. We quantified OOPC as a proportion of equivalised household disposable income and calculated Kakwani progressivity indices (K).ResultsUsing data from 85% (n=6,830,365) of all Census private households, OOPC as a percentage of equivalised household disposable income decreased from 1.16% in the poorest decile to 0.63% in the richest decile for MBS services, and from 1.35% to 0.35% for PBS medicines. The regressive trend was less pronounced for MBS services (K = −0.06), with percentage OOPC relatively stable between the 2nd and 9th income deciles; while percentage OOPC decreased substantially with increasing income for PBS medicines (K = −0.24).ConclusionOOPC for out-of-hospital Medicare services were mildly regressive while those for prescription medicines were distinctly regressive. Actions to reduce inequity in OOPC, particularly for medicines should be considered.

This paper reports on the valuation of the classification system for the Quality-of-Life Aged Care Consumers (QOL-ACC) instrument using a discrete choice experiment (DCE) with duration with a large sample of older people receiving aged care services.A DCE with 160 choice sets of two quality-of-life state-survival duration combinations blocked into 20 survey versions, with eight choice sets in each version, was designed and administered through an on-line survey to older Australians receiving aged care services in home and via interviewer facilitation with older people in residential aged care settings. Model specifications investigating preferences with respect to survival duration and interactions between QOL-ACC dimension levels were estimated. Utility weights were developed, with estimated coefficients transformed to the 0 (being dead) to 1 (full health) scale to generate a value set suitable for application in quality assessment and for the calculation of quality-adjusted life-years for use in economic evaluation.In total, 953 older people completed the choice experiment with valid responses. The estimation results from econometric model specifications indicated that utility increased with survival duration and decreased according to quality-of-life impairment levels. An Australian value set (range - 0.56 to 1.00) was generated for the calculation of utilities for all QOL-ACC states.The QOL-ACC is unique in its focus on measuring and valuing quality of life from the perspective of older people themselves, thereby ensuring that the preferences of aged care service users are the primary focus for quality assessment and economic evaluation.

Previous economics literature has explored the role of visual attention on choice in isolation without accounting for other influences such as habits and goals or learning effects, nor their interrelationship. In this paper, we: (i) develop a novel joint framework to explore the relationship between visual attention, observed heterogeneity from stated habits and goals, and choice outcomes while accounting for shorter- and longer-term learning effects; and (ii) investigate whether accounting for these relationships improves model predictive power and behavioral insights. The empirical analysis used an eye-tracked discrete choice experiment on sugar-sweetened beverage purchasing (n = 152 adults with 20 choice tasks). Results suggest that habits, goals, and shorter-term learning are key drivers of information acquisition whereas cumulative choices (longer-term learning) affect subsequent choice outcome. Importantly, ignoring the joint relationship between habits, visual attention and choice may exaggerate the role of visual attention, leading to incorrect behavioral insights and reduced prediction accuracy.

The objective of this study was to investigate the degree of inconsistency in quality-of-life attribute preference orderings generated via successive best–worst scaling (a form of ranking whereby the respondent chooses the best and worst attributes from a choice set, these attributes are then eliminated and the best and worst attributes from the reduced choice set are then chosen and this process is continued until all presented attributes are eliminated) and conventional ranking methods (whereby the respondent chooses the best, second best and third best from a choice set until all presented attributes are eliminated). An on-line survey was developed for administration to two general population samples comprising younger people (aged 18–64 years) and older people (aged 65 years and above). Data were analysed in STATA through an empirical examination of the relative level of choice inconsistency (randomness in responses or the variability in choice outcomes not explained by attributes and their associated preference weights) for successive best–worst in comparison with the conventional ranking method for the younger and older person samples. For the younger person sample, both methods were found to be similarly consistent. In contrast, for the older person sample, ranking performed relatively worse than best–worst scaling with more inconsistent responses (tau = 0.515, p

Despite unprecedented progress in developing COVID-19 vaccines, global vaccination levels needed to reach herd immunity remain a distant target, while new variants keep emerging. Obtaining near universal vaccine uptake relies on understanding and addressing vaccine resistance. Simple questions about vaccine acceptance however ignore that the vaccines being offered vary across countries and even population subgroups, and differ in terms of efficacy and side effects. By using advanced discrete choice models estimated on stated choice data collected in 18 countries/territories across six continents, we show a substantial influence of vaccine characteristics. Uptake increases if more efficacious vaccines (95% vs 60%) are offered (mean across study areas=3.9%, range of 0.6%-8.1%) or if vaccines offer at least 12 months of protection (mean across study areas=2.4%, range of 0.2%-5.8%), while an increase in severe side effects (from 0.001% to 0.01%) leads to reduced uptake (mean=-1.3%, range of -0.2% to -3.9%). Additionally, a large share of individuals (mean=55.2%, range of 28%-75.8%) would delay vaccination by 3 months to obtain a more efficacious (95% vs 60%) vaccine, where this increases further if the low efficacy vaccine has a higher risk (0.01% instead of 0.001%) of severe side effects (mean=65.9%, range of 41.4%-86.5%). Our work highlights that careful consideration of which vaccines to offer can be beneficial. In support of this, we provide an interactive tool to predict uptake in a country as a function of the vaccines being deployed, and also depending on the levels of infectiousness and severity of circulating variants of COVID-19. We acknowledge financial support as follows: CN Chinese National Natural Science Foundation (72071017), the joint project of the National Natural Science Foundation of China and the Joint Programming Initiative Urban Europe (NSFC – JPI UE) (‘U- PASS’, 71961137005). CL Instituto Sistemas Complejos de Ingeniería (ISCI), through grant ANID PIA/BASAL AFB180003. ES FEDER/Ministry of Science, Innovation and Universities through grant PID2020-113650RB-I00; Basque Government through grant IT1359-19 (UPV/EHU Econometrics Research Group); BERC 2018–2021 programme; MICINN María de Maeztu excellence accreditation (MDM- 2017-0714). FR FR French National Research Agency Grants ANR-17-EURE-0020 and the Excellence Initiative of Aix-Marseille University - A*MIDEX. KR Creative-Pioneering Researchers Program through Seoul Na- tional University. NA Ndatara Surveys. NZ Waikato Management School. UK European Research Council through the consolidator grant 615596-DECISIONS; internal funding through the Choice Modelling Centre (CMC). We would also like to express our thanks to technical support from Aix-Marseille University, and thank Sofia Hern ́andez Benavides (CL), Simon Dec Pedersen (DK) and Robbie Maris (NZ) for help in data preparation and analysis.

The notion of hypothetical bias (HB) constitutes, arguably, the most fundamental issue in relation to the use of hypothetical survey methods. Whether or to what extent choices of survey participants and subsequent inferred estimates translate to real-world settings continues to be debated. While HB has been extensively studied in the broader context of contingent valuation, it is much less understood in relation to choice experiments (CE). While the number of CE studies has rapidly increased, the critical issue of HB has been studied in only a small fraction of CE studies. This paper provides macro-scale insights into the literature of CE and reviews the empirical evidence for HB in CE in various fields of applied economics as well as experimental psychology and behavioural neuroscience. Results suggest mixed evidence on the prevalence, extent and direction of HB as well as considerable context and measurement dependency. While HB is found to be an undeniable issue when conducting CEs, the empirical evidence on HB does not render CEs unable to represent real-world preferences. While health-related choice experiments often find negligible degrees of HB, experiments in consumer behaviour and transport domains suggest significant degrees of HB. Environmental valuation studies provide mixed evidence. Also, across these disciplines many studies display HB in their total willingness to pay estimates and opt-in rates but not in their hypothetical marginal rates of substitution (subject to scale correction). Further, recent findings in psychology and brain imaging studies identify neurocognitive mechanisms underlying HB that may explain some of the discrepancies and unexpected findings in the mainstream CE literature.

Workforce participation decisions involve multiple stages: search, screening and offer evaluation. Standard econometric practice focusses on these stages in isolation. We conceptualize the focal behaviours as separate sequential decision stages, and provide a stated preference measurement framework for online job search and choice with a behaviourally consistent modelling approach. We demonstrate this approach in an empirical application of 275 dentists who completed an online survey including two Discrete Choice Experiments: the first mimicked an online job search site in which dentists decided which jobs they would apply to and the second presented dentists with a job offer which they accepted or rejected. Modelling these tasks requires a two-stage econometric model that incorporates the likelihood of application (first stage) into the job offer choice (second stage). The model detects differences in preferences (hence behaviours) across stages, facilitating the differentiation of policy aimed at search and job choice behaviours. Job screening occurs during search and the marginal propensity to apply for a job-type differs from the offer stage. We suggest that the approach presented provides a valuable way to investigate how dentists particularly, and perhaps the health workforce more generally, respond at different stages of workforce participation decisions and discuss practical implications.

BackgroundMedication management in residential aged care facilities is an ongoing concern. Numerous studies have reported high rates of inappropriate prescribing and medication use in aged care facilities, which contribute to residents’ adverse health outcomes. There is a need for new models of care that enhance inter-disciplinary collaboration between residential aged care facility staff and healthcare professionals, to improve medication management. Pilot research has demonstrated the feasibility and benefits of integrating a pharmacist into the aged care facility team to improve the quality use of medicines. This protocol describes the design and methods for a cluster randomised controlled trial to evaluate the outcomes and conduct economic evaluation of a service model where on-site pharmacists are integrated into residential aged care facility healthcare teams to improve medication management.MethodsIntervention aged care facilities will employ on-site pharmacists to work as part of their healthcare teams. Pharmacists will assume responsibility for medication management, and collaborate with facility nurses, prescribers, community pharmacists, residents and families to improve the quality use of medicines. The intervention will last for 12 months. Aged care facilities in the control group will continue usual care. The target sample size is 1,188 residents from a minimum of 13 aged care facilities. The primary outcome is the appropriateness of prescribing, measured by the proportion of residents who are prescribed at least one potentially inappropriate medicine according to the 2019 Beers Criteria. Secondary outcomes include hospital and Emergency Department presentations, fall rates, prevalence and dose of antipsychotics and benzodiazepines, Anticholinergic Cognitive Burden Score, staff influenza vaccination rate, time spent on medication rounds, appropriateness of dose form modification and completeness of resident’s allergy and adverse drug reaction documentation. A cost-consequence and cost-effectiveness analysis will be embedded in the trial.DiscussionThe results of this study will provide information on clinical and economic outcomes of a model that integrates on-site pharmacists into Australian residential aged care facilities. The results will provide policymakers with recommendations relevant to further implementation of this model.Trial registrationACTRN: ACTRN12620000430932, retrospectively registered with ANZCTR on 1 April 2020. Available from https://www.anzctr.org.au/TrialSearch.aspx#&&conditionCode=&dateOfRegistrationFrom=&interventionDescription=&interventionCodeOperator=OR&primarySponsorType=&gender=&distance=&postcode=&pageSize=20&ageGroup=&recruitmentCountryOperator=OR&recruitmentRegion=&ethicsReview=&countryOfRecruitment=&registry=&searchTxt=ACTRN12620000430932&studyType=&allocationToIntervention=&dateOfRegistrationTo=&recruitmentStatus=&interventionCode=&healthCondition=&healthyVolunteers=&page=1&conditionCategory=&fundingSource=&trialStartDateTo=&trialStartDateFrom=&phase=

In the original version of this article, the author’s name Emily Lancsar was incorrectly written as Emily Lanscar. The original article has been corrected.

Large changes to food retail settings are required to improve population diet. However, limited research has comprehensively considered the business implications of healthy food retail strategies for food retailers. We performed a systematic scoping review to identify types of business outcomes that have been reported in healthy food retail strategy evaluations. Peer-reviewed and grey literature were searched. We identified qualitative or quantitative real-world food or beverage retail strategies designed to improve the healthiness of the consumer nutrition environment (eg, changes to the "marketing mix" of product, price, promotion, and/or placement). Eligible studies reported store- or chain-level outcomes for measures of commercial viability, retailer perspectives, customer perspectives, and/or community outcomes. 11 682 titles and abstracts were screened with 107 studies included for review from 15 countries. Overall item sales, revenue, store patronage, and customer level of satisfaction with strategy were the most frequently examined outcomes. There was a large heterogeneity in outcome measures reported and in favourability for retailers of outcomes across studies. We recommend more consistent reporting of business outcomes and increased development and use of validated and reliable measurement tools. This may help generate more robust research evidence to aid retailers and policymakers to select feasible and sustainable healthy food retail strategies to benefit population health within and across countries.

Governments and health insurers often make funding decisions based on health gains from randomised controlled trials. These decisions are inherently uncertain because health gains in trials may not translate to practice owing to differences in the population, treatment use and setting. Post-market analysis of real-world data can provide additional evidence but estimates from standard matching methods may be biased when unobserved characteristics explain whether a patient is treated and their outcomes. We propose a new untreated matching approach that can reduce this bias. Our approach utilises the outcomes of contemporaneous untreated patients to improve the matching of treated and historical control patients. We assess the performance of this new approach compared to standard matching using a simulation study and demonstrate the steps required using a funding decision for prostate cancer treatments in Australia. Our simulation study shows that our new matching approach eliminates nearly all bias when unobserved treatment selection is related to outcomes, and outperforms standard matching in most scenarios. In our empirical example, standard matching overestimated survival by 15% (95% confidence interval 2–34) compared to our untreated matching approach. The health gains estimated using our approach were slightly lower than expected based on the trial evidence, but we also found evidence that in practice prescribers ceased prior therapies earlier, treated a more vulnerable population and continued treatment for longer. Our untreated matching approach offers researchers a new tool for reducing uncertainty in healthcare funding decisions using real-world data.

OBJECTIVES To assess the impact of a Consumer Directed Care (CDC) model of service delivery on the quality of life of older people receiving home care packages. METHODS Quality of life was assessed using validated instruments. The relationship between quality of life and length of time exposed to CDC was examined using descriptive statistical and multivariate regression analyses. RESULTS Consenting older adults (n = 150) in receipt of home care packages participated. Quality of life and capability scores were higher for older people in receipt of a CDC model of service delivery for

The notion of hypothetical bias (HB) constitutes, arguably, the most fundamental issue in relation to the use of hypothetical survey methods. Whether or to what extent choices of survey participants and subsequent inferred estimates translate to real-world settings continues to be debated. While HB has been extensively studied in the broader context of contingent valuation, it is much less understood in relation to choice experiments (CE). This paper reviews the empirical evidence for HB in CE in various fields of applied economics and presents an integrative framework for how HB relates to external validity. Results suggest mixed evidence on the prevalence, extent and direction of HB as well as considerable context and measurement dependency. While HB is found to be an undeniable issue when conducting CEs, the empirical evidence on HB does not render CEs unable to represent real-world preferences. While health-related choice experiments often find negligible degrees of HB, experiments in consumer behaviour and transport domains suggest that significant degrees of HB are ubiquitous. Assessments of bias in environmental valuation studies provide mixed evidence. Also, across these disciplines many studies display HB in their total willingness to pay estimates and opt-in rates but not in their hypothetical marginal rates of substitution (subject to scale correction). Further, recent findings in psychology and brain imaging studies suggest neurocognitive mechanisms underlying HB that may explain some of the discrepancies and unexpected findings in the mainstream CE literature. The review also observes how the variety of operational definitions of HB prohibits consistent measurement of HB in CE. The paper further identifies major sources of HB and possible moderating factors. Finally, it explains how HB represents one component of the wider concept of external validity.

IntroductionDescribing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to administrative income and medical claims data, we aimed to quantify, for the first time, the progressivity of OOP costs for government-subsidised out-of-hospital healthcare in Australia. Objectives and ApproachWe used Australian Census 2011 linked to Personal Income Tax (PIT), Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) data compiled through the Multi-Agency Data Integration Project (MADIP). Personal disposable income was estimated using a combination of PIT data and Census self-reported income, and aggregated across the household to estimate equivalised household income. We estimated annual MBS (out-of-hospital only) and PBS OOP costs as a proportion of equivalised household income, and assessed progressivity by reporting this for each income decile and computing a Kakwani Index. ResultsWe will present findings on progressivity overall, and separately by age, sex and location (incomplete at time of abstract submission). Conclusion / ImplicationsOur study will present one measure regarding the equity of healthcare costs, and help to identify vulnerable or at-risk groups. These findings may inform policy changes on equity in the financing of healthcare. Newly linked data from the MADIP can be used to relate healthcare costs to ability to pay.

Background A discrete choice experiment (DCE) is a method used to elicit participants’ preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influencing a decision of interest and to selection methods for their inclusion in a DCE are under-reported. Our objectives were: to explore the development process used to select/present attributes/levels from the identified range that may be influential; to describe a systematic and rigorous development process for design of a DCE in the context of thrombolytic therapy for acute stroke; and, to discuss the advantages of our five-stage approach to enhance current guidance for developing DCEs. Methods A five-stage DCE development process was undertaken. Methods employed included literature review, qualitative analysis of interview and ethnographic data, expert panel discussions, a quantitative structured prioritisation (ranking) exercise and pilot testing of the DCE using a ‘think aloud’ approach. Results The five-stage process reported helped to reduce the list of 22 initial patient-related factors to a final set of nine variable factors and six fixed factors for inclusion in a testable DCE using a vignette model of presentation. Conclusions In order for the data and conclusions generated by DCEs to be deemed valid, it is crucial that the methods of design and development are documented and reported. This paper has detailed a rigorous and systematic approach to DCE development which may be useful to researchers seeking to establish methods for reducing and prioritising attributes for inclusion in future DCEs. Electronic supplementary material The online version of this article (10.1186/s12913-018-3305-5) contains supplementary material, which is available to authorized users.

Since the introduction of Discrete Choice Analysis, countless efforts have been made to enhance the efficiency of data collection through choice experiments and to improve the behavioural realism of choice models. One example development in data collection are best-worst discrete choice experiments (BWDCE), which have the benefit of obtaining a larger number of observations per respondent, allowing for reliably estimating choice models even with smaller samples. In SWDCE, respondents are asked to alternatingly select the ‘best’/‘worst’ alternatives, until the choice set is exhausted. The use of BWDCE raises the question of decision-rule consistency through the stages of the experiment. We challenge the notion that the same fully compensatory decision rule is utilised throughout the experiment. We hypothesize that respondents may utilise one decision rule for selecting the ‘best’ and another for selecting the ‘worst’ alternatives. To test our hypothesis, we developed a model that combines the SBWMNL model for modelling best-worst data and the μRRM model that can account for variations in decision rules. Our results show that decision-rule heterogeneity does seem to be present in BWDCE: it is more likely that ‘best’ choices are made using a fully compensatory decision rule (maximising utility), whereas ‘worst’ choices are more likely made using a non-compensatory decision rule (minimising regret). Such behaviour is largely similar to how image theory describes the decision-making process in complex situations. Our findings give choice modellers new insight into the behaviour of respondents in best-worst experiments and allows them to represent their behaviour more accurately.

This paper follows the review of empirical evidence on the existence of hypothetical bias (HB) in choice experiments (CEs) presented in Part I of this study. It observes how the variation in operational definitions of HB has prohibited consistent measurement of HB in CE. It offers a unifying definition of HB and presents an integrative framework of how HB relates to but is also distinct from external validity (EV), with HB representing one component of the wider concept of EV. The paper further identifies major sources of HB and discusses explanations as well as possible moderating factors of HB. The paper reviews methods of HB mitigation identified in the literature and the empirical evidence of their effectiveness. The review includes both ex-ante and ex-post bias mitigation methods. Ex-ante bias mitigation methods include cheap talk, real talk, consequentiality scripts, solemn oath scripts, opt-out reminders, budget reminders, honesty priming, induced truth telling, indirect questioning, time to think and pivot designs. Ex-post methods include follow-up certainty calibration scales, respondent perceived consequentiality scales, and revealed-preference-assisted estimation. It is observed that the mitigation methods and their preferred use vary markedly across different sectors of applied economics. The existing empirical evidence points to the overall effectiveness of mitigation strategies in reducing HB, although there is some variation. The paper further discusses how each mitigation method can counter a certain subset of HB sources. Considering the prevalence of HB in CEs and the effectiveness of bias mitigation methods, it is recommended that implementation of at least one bias mitigation method (or a suitable combination where possible) becomes standard practice in conducting CEs to ensure that inferences and subsequent policy decisions are as much as possible free of HB.

Gastroenteritis caused from infections with

IntroductionThe ageing of the population represents a significant challenge for aged care in Australia and in many other countries internationally. In an environment of increasing resource constraints, new methods, techniques and evaluative frameworks are needed to support resource allocation decisions that maximise the quality of life and well-being of older people. Economic evaluation offers a rigorous, systematical and transparent framework for measuring quality and efficiency, but there is currently no composite mechanism for incorporating older people’s values into the measurement and valuation of quality of life for quality assessment and economic evaluation. In addition, to date relatively few economic evaluations have been conducted in aged care despite the large potential benefits associated with their application in this sector. This study will generate a new preference based older person-specific quality of life instrument designed for application in economic evaluation and co-created from its inception with older people.Methods and analysisA candidate descriptive system for the new instrument will be developed by synthesising the findings from a series of in-depth qualitative interviews with 40 older people currently in receipt of aged care services about the salient factors which make up their quality of life. The candidate descriptive system will be tested for construct validity, practicality and reliability with a new independent sample of older people (n=100). Quality of life state valuation tasks using best worst scaling (a form of discrete choice experiment) will then be undertaken with a representative sample of older people currently receiving aged care services across five Australian states (n=500). A multinomial (conditional) logistical framework will be used to analyse responses and generate a scoring algorithm for the new preference-based instrument.Ethics and disseminationThe new quality of life instrument will have wide potential applicability in assessing the cost effectiveness of new service innovations and for quality assessment across the spectrum of ageing and aged care. Results will be disseminated in ageing, quality of life research and health economics journals and through professional conferences and policy forums. This study has been reviewed by the Human Research Ethics Committee of the University of South Australia and has ethics approval (Application ID: 201644).

Copyright Ó, International Association for Food Protection Gastroenteritis caused from infections with Salmonella enterica (salmonellosis) causes significant morbidity in Australia. In addition to acute gastroenteritis, approximately 8.8% of people develop irritable bowel syndrome (IBS) and 8.5% of people develop reactive arthritis (ReA). We estimated the economic cost of salmonellosis and associated sequel illnesses in Australia in a typical year circa 2015. We estimated incidence, hospitalizations, other health care usage, absenteeism, and premature mortality for four age groups using a variety of complementary data sets. We calculated direct costs (health care) and indirect costs (lost productivity and premature mortality) by using Monte Carlo simulation to estimate 90% credible intervals (CrI) around our point estimates. We estimated that 90,833 cases, 4,312 hospitalizations, and 19 deaths occurred from salmonellosis in Australia circa 2015 at a direct cost of AUD 23.8 million (90% CrI, 19.3 to 28.9 million) and a total cost of AUD 124.4 million (90% CrI, 107.4 to 143.1 million). When IBS and ReA were included, the estimated direct cost was 35.7 million (90% CrI, 29.9 to 42.7 million) and the total cost was AUD 146.8 million (90% CrI, 127.8 to 167.9 million). Foodborne infections were responsible for AUD 88.9 million (90% CrI, 63.9 to 112.4 million) from acute salmonellosis and AUD 104.8 million (90% CrI, 75.5 to 132.3 million) when IBS and ReA were included. Targeted interventions to prevent illness could considerably reduce costs and societal impact from Salmonella infections and sequel illnesses in Australia.

In most societies resources are insufficient to provide everyone with all the health care they want. In practice, this means that some people are given priority over others. On what basis should priority be given? In this paper we are interested in the general public's views on this question. We set out to synthesis what the literature has found as a whole regarding which attributes or factors the general public think should count in priority setting and what weight they should receive. A systematic review was undertaken (in August 2014) to address these questions based on empirical studies that elicited stated preferences from the general public. Sixty four studies, applying eight methods, spanning five continents met the inclusion criteria. Discrete Choice Experiment (DCE) and Person Trade-off (PTO) were the most popular standard methods for preference elicitation, but only 34% of all studies calculated distributional weights, mainly using PTO. While there is heterogeneity, results suggest the young are favoured over the old, the more severely ill are favoured over the less severely ill, and people with self-induced illness or high socioeconomic status tend to receive lower priority. In those studies that considered health gain, larger gain is universally preferred, but at a diminishing rate. Evidence from the small number of studies that explored preferences over different components of health gain suggests life extension is favoured over quality of life enhancement; however this may be reversed at the end of life. The majority of studies that investigated end of life care found weak/no support for providing a premium for such care. The review highlights considerable heterogeneity in both methods and results. Further methodological work is needed to achieve the goal of deriving robust distributional weights for use in health care priority setting.

The oft-applied assumption in the use of Quality Adjusted Life Years (QALYs) in economic evaluation, that all QALYs are valued equally, has been questioned from the outset. The literature has focused on differential values of a QALY based on equity considerations such as the characteristics of the beneficiaries of the QALYs. However, a key characteristic which may affect the value of a QALY is the type of QALY itself. QALY gains can be generated purely by gains in survival, purely by improvements in quality of life, or by changes in both. Using a discrete choice experiment and a new methodological approach to the derivation of relative weights, we undertake the first direct and systematic exploration of the relative weight accorded different QALY types and do so in the presence of equity considerations; age and severity. Results provide new evidence against the normative starting point that all QALYs are valued equally.

An increase in sugar-sweetened beverage (SSB) prices has been suggested to reduce SSB intake to improve population health. Using a discrete choice experiment, we tested the effect of price changes on beverage choices in an online hypothetical convenience store setting amongst 1,008 Australian adults in May to June 2016. From this we calculated pre-packaged beverage price elasticities overall and for health policy-target consumer subgroups; and identified consumer subgroups likely to be most reactive to beverage price changes. Using mixed logit analysis, we found similar price elasticities for age, gender and income groups. More frequent SSB consumers tended to be less sensitive to SSB price changes. Latent class analysis revealed five consumer groups, none of which fit the desirable policy-target of highly price sensitive, frequent SSB consumers. An improved understanding of responsiveness to beverage price changes and consumer preferences could improve predictions of whose health is likely to benefit most from pricing interventions.

There is much interest from stakeholders in understanding how health technology assessment (HTA) committees make national funding decisions for health technologies. A growing literature has analysed past decisions by committees (revealed preference, RP studies) and hypothetical decisions by committee members (stated preference, SP studies) to identify factors influencing decisions and assess their importance. A systematic review of the literature was undertaken to provide insight into committee preferences for these factors (after controlling for other factors) and the methods used to elicit them. Ovid Medline, Embase, Econlit and Web of Science were searched from inception to 11 May 2017. Included studies had to have investigated factors considered by HTA committees and to have conducted multivariate analysis to identify the effect of each factor on funding decisions. Factors were classified as being important based on statistical significance, and their impact on decisions was compared using marginal effects. Twenty-three RP and four SP studies (containing 42 analyses) of 14 HTA committees met the inclusion criteria. Although factors were defined differently, the SP literature generally found clinical efficacy, cost-effectiveness and equity factors (such as disease severity) were each important to the Pharmaceutical Benefits Advisory Committee (PBAC), the National Institute for Health and Care Excellence (NICE) and the All Wales Medicines Strategy Group. These findings were supported by the RP studies of the PBAC, but not the other committees, which found funding decisions by these and other committees were mostly influenced by the acceptance of the clinical evidence and, where applicable, cost-effectiveness. Trust in the evidence was very important for decision makers, equivalent to reducing the incremental cost-effectiveness ratio (cost per quality-adjusted life-year) by A$38,000 (Australian dollars) for the PBAC and £15,000 for NICE. This review found trust in the clinical evidence and, where applicable, cost-effectiveness were important for decision makers. Many methodological differences likely contributed to the diversity in some of the other findings across studies of the same committee. Further work is needed to better understand how competing factors are valued by different HTA committees.

There is a paucity of evidence regarding the impact of sugar sweetened beverage (SSB) price increases on beverage consumption, using individual-level data, for the population overall and for different socioeconomic groups. This study aimed to predict the impact of altered beverage prices and educational messages on consumer purchasing behavior. 2020 adults representative of the Australian population by age, gender and income completed a discrete choice experiment online in 2016. Each subject completed 20 choice scenarios in a hypothetical convenience store setting where subjects chose between seven SSB and non-SSB beverage options or a no beverage option. Beverage prices and volumes varied between scenarios. Half of participants (n = 1012) were randomly exposed to an educational poster discouraging SSB consumption prior to completing choice scenarios. We used discrete choice models to predict purchases under several policy proposals, overall and for income and SSB consumption frequency sub-groups. Compared to baseline prices, a 10% SSB price increase was predicted to reduce SSB purchases by 15.0% [95%CI -15.2, −14.7], and increase purchases of non-SSBs by +11.0% [95%CI 10.8, 11.2] and no beverage by +15.5% [95%CI 15.1, 15.9]. Effects were greater with a 20% SSB price increase. Across all policy scenarios, the highest income quintile had a similar absolute and slightly greater relative decrease in SSB purchases compared to the lowest quintile. Educational poster exposure reduced SSB choice for all groups, with a greater reduction in the lower compared to higher income group, and additively increased response to price changes. Our results support the use of population-wide SSB pricing and educational interventions to reduce demand across all income groups.

We provide a user guide on the analysis of data (including best–worst and best–best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a ‘way in’ for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

Background Limited evidence has been gathered on the real-world impact of sugar-sweetened beverage price changes on purchasing behavior over time or in community-retail settings. Objective Our aim was to determine changes in beverage purchases, business outcomes, and customer and retailer satisfaction associated with a retailer-led sugar-sweetened beverage price increase in a convenience store. We hypothesized that purchases of less-healthy beverages would decrease compared to predicted sales. Design A convergent parallel mixed methods design complemented sales data (122 weeks pre-intervention, 17 weeks during intervention) with stakeholder interviews and customer surveys. Participants/setting Electronic beverage sales data were collected from a convenience store in Melbourne, Australia (August through November 2015). Convenience store staff completed semi-structured interviews (n=4) and adult customers exiting the store completed surveys (n=352). Intervention Beverages were classified using a state government framework. Prices of "red" beverages (eg, nondiet soft drinks, energy drinks) increased by 20%. Prices of "amber" (eg, diet soft drinks, small pure fruit juices) and "green" beverages (eg, water) were unchanged. Main outcome measures Changes in beverage volume, item sales, and revenue during the intervention were compared with predicted sales. Statistical analyses Sales data were analyzed using time series segmented regression while controlling for pre-intervention trends, autocorrelation in sales data, and seasonal fluctuations. Results Beverage volume sales of red (−27.6%; 95% CI −32.2 to −23.0) and amber (−26.7%; 95% CI −39.3 to −16.0) decreased, and volume of green beverages increased (+26.9%; 95% CI +14.1 to +39.7) in the 17th intervention week compared with predicted sales. Store manager and staff considered the intervention business-neutral, despite a small reduction in beverage revenue. Fifteen percent of customers noticed the price difference and 61% supported the intervention. Conclusions A 20% sugar-sweetened beverage price increase was associated with a reduction in their purchases and an increase in purchases of healthier alternatives. Community retail settings present a bottom-up approach to improving consumer beverage choices.