Discrete choice experiments in health economics

Bryan and Dolan have offered a critique of the use of discrete choice experiments in health economics. Their call for more open debate on the relative strengths and limitations of the DCE method, particularly when applied in health settings is warranted. However, their paper has only added to part of this debate in that it focuses on the application of choice experiments in the health sector but says little on the strengths and limitations of the DCE method in general. We argue that while the criticisms posed by Bryan and Dolan rightly challenge the manner in which DCEs have been applied in health economics, such criticism does not challenge the theoretical/methodological basis of DCEs per se.     

Discrete choice experiments in health economics: a review of the literature

Discrete choice experiments (DCEs) have become a commonly used instrument in health economics. This paper updates a review of published papers between 1990 and 2000 for the years 2001-2008. Based on this previous review, and a number of other key review papers, focus is given to three issues: experimental design; estimation procedures; and validity of responses. Consideration is also given to how DCEs are applied and reported. We identified 114 DCEs, covering a wide range of policy questions. Applications took place in a broader range of health-care systems, and there has been a move to incorporating fewer attributes, more choices and interview-based surveys. There has also been a shift towards statistically more efficient designs and flexible econometric models. The reporting of monetary values continues to be popular, the use of utility scores has not gained popularity, and there has been an increasing use of odds ratios and probabilities. The latter are likely to be useful at the policy level to investigate take-up and acceptability of new interventions. Incorporation of interactions terms in the design and analysis of DCEs, explanations of risk, tests of external validity and incorporation of DCE results into a decision-making framework remain important areas for future research.     

Elimination and selection by aspects in health choice experiments: Prioritising health service innovations

Priorities for public health innovations are typically not considered equally by all members of the public. When faced with a choice between various innovation options, it is, therefore, possible that some respondents eliminate and/or select innovations based on certain characteristics. This paper proposes a flexible method for exploring and accommodating situations where respondents exhibit such behaviours, whilst addressing preference heterogeneity. We present an empirical case study on the public's preferences for health service innovations. We show that allowing for elimination-by-aspects and/or selection-by-aspects behavioural rules leads to substantial improvements in model fit and, importantly, has implications for willingness to pay estimates and scenario analysis.     

开发离散选择实验属性和水平的研究进展

目的 综述开发离散选择实验属性和水平的研究进展，为实证研究提供理论基础。方法 以“离散选择实验”作为CNKI数据库和万方数据库的检索词，以“patient preference”、“discrete choice*”、“discrete-choice*”、“attribute*”作为PubMed数据库的检索词，检索关于医疗卫生健康领域离散选择实验属性和水平开发的相关文献，总结开发离散选择实验属性和水平的研究现状、研究方法。结果 离散选择实验属性和水平的设计流程、研究方法等没有统一的标准，且大多数研究没有详细报告开发过程。 结论 详细报告开发离散选择实验属性和水平的过程，可以提高实验质量、促进学科发展。     

Design techniques for stated preference methods in health economics

This paper discusses different design techniques for stated preference surveys in health economic applications. In particular, we focus on different design techniques, i.e. how to combine the attribute levels into alternatives and choice sets, for choice experiments. Design is a vital issue in choice experiments since the combination of alternatives in the choice sets will determine the degree of precision obtainable from the estimates and welfare measures. In this paper we compare orthogonal, cyclical and D-optimal designs, where the latter allows expectations about the true parameters to be included when creating the design. Moreover, we discuss how to obtain prior information on the parameters and how to conduct a sequential design procedure during the actual experiment in order to improve the precision in the estimates. The designs are evaluated according to their ability to predict the true marginal willingness to pay under different specifications of the utility function in Monte Carlo simulations. Our results suggest that the designs produce unbiased estimations, but orthogonal designs result in larger mean square error in comparison to D-optimal designs. This result is expected when using correct priors on the parameters in D-optimal designs. However, the simulations show that welfare measures are not very sensitive if the choice sets are generated from a D-optimal design with biased priors.     

Empirical investigation of experimental design properties of discrete choice experiments in health care

Experimental design is critical to valid inference from the results of discrete choice experiments (DCEs). In health economics, DCEs have placed limited emphasis on experimental design, typically employing relatively small fractional factorial designs, which allow only strictly linear additive utility functions to be estimated. The extensive literature on optimal experimental design outside health economics has proposed potentially desirable design properties, such as orthogonality, utility balance and level balance. However, there are trade-offs between these properties and emphasis on some properties may increase the random variability in responses, potentially biasing parameter estimates.This study investigates empirically the design properties of DCEs, in particular, the optimal method of combining alternatives in the choice set. The study involves a forced choice between two alternatives (treatment and non-treatment for a hypothetical health care condition), each with three, four-level, alternative-specific attributes. Three experimental design approaches are investigated: a standard six-attribute, orthogonal main effects design; a design that combines alternatives to achieve utility balance, ensuring no alternatives are dominated; and a design that combines alternatives randomly. The different experimental designs did not impact on the underlying parameter estimates, but imposing utility balance increases the random variability of responses.     

Modelling non-demanders in choice experiments

Discrete choice experiments have the advantage that they can study preferences in health care where revealed preference data is not readily available. However, as a substitute for actual observed market led data, the experimental set-up for hypothetical situations must mimic the circumstances under which actual choices are made. One situation that a consumer/patient might face is an opt-out option. They might not choose to accept any of the positive actions available and as such will be a non-demander of the health care on offer. This paper explores issues raised in the modelling of such data within an experiment looking at women's preferences for cervical screening services.     

Best-worst scaling vs. discrete choice experiments: an empirical comparison using social care data

This paper presents empirical findings from the comparison between two principal preference elicitation techniques: discrete choice experiments and profile-based best-worst scaling. Best-worst scaling involves less cognitive burden for respondents and provides more information than traditional "pick-one" tasks asked in discrete choice experiments. However, there is lack of empirical evidence on how best-worst scaling compares to discrete choice experiments. This empirical comparison between discrete choice experiments and best-worst scaling was undertaken as part of the Outcomes of Social Care for Adults project, England, which aims to develop a weighted measure of social care outcomes. The findings show that preference weights from best-worst scaling and discrete choice experiments do reveal similar patterns in preferences and in the majority of cases preference weights--when normalised/rescaled--are not significantly different.     

21世纪卫生系统改革对卫生经济学发展的影响

该文介绍了发达国家和发展中国家在卫生改革中遇到的问题。前者有：组建医院间“战略联盟”,管理保健市场发展,卫生服务效率、公平性和可及性等。后者有：减少政府的作用,改变公共部门的组织及管理,增加卫生资金的来源及数量。这些问题引起卫生经济学界关注。第二次国际卫生经济学会会议将讨论以下专题：信息不对称及卫生保健组织间关系、卫生保健的选择,卫生及卫生服务的需求,健康及卫生服务的分布,卫生保健的经济学评价,卫生保健市场分析,健康保险,管理保健,卫生服务的产出等18个主题。     

Effects coding in discrete choice experiments

This paper discusses the inherent problems associated with applying dummy coding when including a fixed comparator in a discrete choice experiment, and seeks to illustrate the misinterpretations that may arise if the analyst is not aware of the problem. This note provides two examples of possible misinterpretations with dummy coding and how it is solved with the use of effects coding.     

Theory verses empiricism in health economics

We report the results of a study analyzing the proportion of theoretical and empirical articles in two core health economics journals. The Journal of Health Economics published 30% theory during the period 1982–1986, but by 1997–2001 the proportion had risen to 40% theory. Health Economics published 38% theory during 1992–1996, but the proportion fell to 32% theory during 1997–2001. In both journals articles were more likely to be published by men (78%), and published women were 50% less likely to publish theory than were men. Articles were more likely to be published by United States authors (54%), but United States authors were less likely to publish theory than authors from other countries. Compared to other disciplines, health economics published a higher proportion of theory than sociology, chemistry, and physics but less than economics and political science. John F. P. Bridges Department of Epidemiology and Biostatistics, Health Services. Research Division, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-4945 USA, e-mail: healtheconomics@hotmail.com     

运用卫生经济学原理 强化医院经济管理

卫生经济学原理对医院经济管理有着重要作用和影响，卫生事业的性质影响医院的经济体制和运行模式，付费方式影响医院供需双方的行为；筹资方式和资源配置影响医院的经济运行模式，医疗价格政策影响的经营效益，信息技术影响医院经济管理的决策方式，成本核算提高医院工作的效率和效益，分配方式影响医院员工的激励效果，结合医院经济管理工作中的理论认识和实践体会，提出医院应当更新观念，主动改变医院的经济管理体制和运行模式，     

Deriving distributional weights for QALYs through discrete choice experiments

This paper presents the first attempt to use a discrete choice experiment to derive distributional weights for quality adjusted life years (QALYs), based on characteristics (age and severity) of the beneficiaries. A novel approach using the Hicksian compensating variation is applied. Advantages include derivation of weights for QALYs, not just for life or life years saved, and investigation of the impact of the size of the health gain by allowing the gain to be traded against other characteristics. Results suggest one would generally not weight QALYs, except in a small number of specific cases and in those cases the weights are relatively small. Methodological challenges are highlighted as is a future research agenda.     

For better or worse? Investigating the validity of best–worst discrete choice experiments in health

Discrete choice experiments (DCEs) are frequently used in health economics to measure preferences for nonmarket goods. Best–worst discrete choice experiment (BWDCE) has been proposed as a variant of the traditional “pick the best” approach. BWDCE, where participants choose the best and worst options, is argued to generate more precise preference estimates because of the additional information collected. However, the validity of the approach relies on two necessary conditions: (a) best and worst decisions provide similar information about preferences and (b) asking individuals to answer more than one choice question per task does not reduce data quality. Whether these conditions hold in empirical applications remains under researched. This is the first study to compare participants' choices across three experimental conditions: (a) BEST choices only, (b) WORST choices only, and (c) BEST and WORST choices (BWDCE). We find responses to worst choices are noisier. Implied preferences from the best only and worst only choices are qualitatively different, leading to different WTP values. Responses to BWDCE tasks have lower consistency, and respondents are more likely to use simplifying decision heuristics. We urge caution in using BWDCE as an alternative to the traditional “pick the best” DCE.     

Determinants of the choice of GP practice registration in England: Evidence from a discrete choice experiment

There have been growing concerns that general practitioner (GP) services in England, which are based on registration with a single practice located near the patient's home, are not sufficiently convenient for patients. To inform the decision as to whether to change registration rules allowing patients to register ‘out-of-area’ and to estimate the demand for this wider choice, we undertook a discrete choice experiment with 1706 respondents. Latent class models were used to analyse preferences for GP practice registration comparing preferences for neighbourhood and non-neighbourhood practices. We find that there is some appetite for registering outside the neighbourhood, but this preference is not uniformly shared across the population. Specifically individuals who are less mobile (e.g. older people and those with caring responsibilities), or satisfied with their local practice are less likely to be interested in registering at a practice outside their neighbourhood. Overall, people feel most strongly about obtaining an appointment with a GP as quickly as possible. Respondents regarded weekend opening as less important than other factors, and particularly less important than extended practice opening hours from Monday to Friday. Assuming a constant demand for GP services, a policy encouraging GP practices to extend their opening hours during the week is likely to decrease the average patient waiting time for an appointment and is likely to be preferred by patients.     

Comparing welfare estimates from payment card contingent valuation and discrete choice experiments

This study presents the first comparison of willingness to pay estimates derived from the payment card (PC) contingent valuation and discrete choice experiment (DCE) methods. A within-sample experiment was used to elicit women's preferences for Chlamydia screening. The willingness to pay estimate derived from the DCE was larger than that derived from the PC. To investigate why the willingness to pay estimates were different, a range of validity tests were conducted. Both methods produced theoretically valid results, and there was no difference in the reported difficulty of completing the tasks. Evidence of a prominence effect was found in the PC responses. Responses to the DCE satisfied tests of non-satiation. Responses to both methods were compared with revealed preference data. There were significant differences between stated screening intention in both methods and actual screening uptake. Future work should address the external validity of stated preference methods.     

中国居民对家庭医生签约服务内容的偏好研究——基于离散选择实验

目的:通过测量中国居民对家庭医生签约服务内容的偏好,为优化家庭医生签约服务内容提供参考依据。方法:基于离散选择实验,通过对北京、上海、杭州、厦门四市共400名社区卫生服务中心就诊居民进行问卷调查,利用条件logistic模型进行分析。结果:纳入分析的8项家庭医生服务内容都具有统计学意义(P<0.05)。其中,慢性病8周长处方相较于2周处方,居民选择签约的OR(Odds Ratio)为3.46;面对面健康咨询与通过电话、网络进行咨询相比较,OR为2.44;疾病治疗免挂号费、诊查费与自费相比,OR为2.24。"8周长处方+免挂号费、诊查费"、"8周长处方+面对面健康咨询"、"8周长处方+4次/年免费上门服务"、"面对面健康咨询+免挂号费、诊查费"这四种服务组合包能使90%以上居民愿意签约家庭医生服务。结论:对于社区就诊居民来说,最吸引其签约家庭医生的服务内容是获得慢性病长处方、面对面健康咨询、疾病治疗减免挂号费和诊查费、一年4次免费上门服务。根据离散选择实验结果可以优化家庭医生服务内容,吸引居民签约家庭医生并增加签约居民的获得感。     

Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters

Health services researchers are increasingly using discrete choice experiments (DCEs) to model a latent variable, be it health, health-related quality of life or utility. Unfortunately it is not widely recognised that failure to model variance heterogeneity correctly leads to bias in the point estimates. This paper compares variance heterogeneity latent class models with traditional multinomial logistic (MNL) regression models. Using the ICECAP-O quality of life instrument which was designed to provide a set of preference-based general quality of life tariffs for the UK population aged 65+, it demonstrates that there is both mean and variance heterogeneity in preferences for quality of life, which covariate-adjusted MNL is incapable of separating. Two policy-relevant mean groups were found: one group that particularly disliked impairments to independence was dominated by females living alone (typically widows). Males who live alone (often widowers) did not display a preference for independence, but instead showed a strong aversion to social isolation, as did older people (of either sex) who lived with a spouse. Approximately 6–10% of respondents can be classified into a third group that often misunderstood the task. Having a qualification of any type and higher quality of life was associated with smaller random component variances. This illustrates how better understanding of random utility theory enables richer inferences to be drawn from discrete choice experiments. The methods have relevance for all health studies using discrete choice tasks to make inferences about a latent scale, particular QALY valuation exercises that use DCEs, best-worst scaling and ranking tasks.     

Parental preferences for rotavirus vaccination in young children: A discrete choice experiment

Objective

This study aimed to identify characteristics that affect parental decisions about rotavirus vaccination, to determine the relative importance of those characteristics and subsequently to estimate vaccination coverage for different implementation strategies.

Methods

A Discrete choice experiment (DCE) questionnaire was sent to the parents of 1250 newborns aged 6 weeks (response rate 37.3%). Mixed-logit models were used to estimate the relative importance of the five included rotavirus vaccine and implementation characteristics; vaccine effectiveness, frequency of severe side effects, protection duration, the healthcare facility that administrates vaccination and out-of-pocket costs. Based on the utility functions of the mixed-logit model, the potential vaccination coverage was estimated for different vaccine scenarios and implementation strategies.

Results

All characteristics, except for healthcare facility that administrates vaccination, influenced parental willingness to vaccinate their newborn against rotavirus. Parents were willing to trade 20.2 percentage points vaccine effectiveness for the lowest frequency of severe side effects (i.e., 1 in 1,000,000) or 20.8 percentage points for a higher protection duration. Potential vaccination coverage ranged between 22.7 and 86.2%, depending on vaccine scenario (i.e., vaccine effectiveness and protection duration) and implementation strategy (i.e., out-of-pocket costs and healthcare facility that administrates vaccination).

Conclusions

When deciding about vaccination against rotavirus, parents are mostly driven by the out-of-pocket costs, vaccine effectiveness, protection duration, and frequency of severe side effects. The highest vaccination coverage is expected for a vaccine with high effectiveness and protection duration that is implemented within the current National Immunization Program context. Implementation of the same rotavirus vaccine in the free market will result in lowest coverage.     

辽宁省庄河市胃癌高发区胃癌筛检的卫生经济学评价

目的采用卫生经济学方法评价2001—2003年在辽宁省庄河市胃癌高发区开展的胃癌筛检项目，评估其经济上的可行性，为在胃癌高发区推广两轮筛检法提供依据。方法采用了三种基本的卫生经济学评价方法：成本一效果分析（CEA）、成本一效益分析（CBA）和成本一效用分析（CUA）。CEA以“减少死亡”作为效果进行评估，计算了每减少一例死亡所需投人的直接成本；CBA计算了直接成本、间接成本和直接效益、间接效益，并计算了成本一效益比；CUA评估了筛检措施挽回的质量调整生命年，并计算了每挽回一个质量调整生命年所耗费的直接成本。结果CEA显示，在庄河地区高危人群中每多投人8448元人民币进行筛检治疗就可以减少一例胃癌的死亡；CBA显示，成本为1300621元，产生效益2555979元，成本效益比为1：1，97；CUA显示，筛检共挽回331．44个质量调整寿命年（QALY），每避免一例胃癌死亡增加11．43个QALY。在庄河地区高危人群中每挽回一个QALY花费3802元。结论在胃癌高发区开展两轮胃癌筛检可以挽回更多胃癌患者的生命，是一项经济、社会效益较好，值得推广的一级预防措施。