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What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review.

ABSTRACT: Discrete choice experiments (DCEs) are a way to assess priority-setting in health care provision. This approach allows for the evaluation of individuals' preferences as a means of adding criteria to traditional quality-adjusted life year analysis. The aim of this systematic literature review was to identify attributes for designing a DCE in order to then develop and validate a framework that supports decision-making on health technologies. Our systematic literature review replicated the methods and search terms used by de Bekker-Grob et al. 2012 and Clark et al. 2014. The Medline database was searched for articles dated between 2008 and 2015. The search was limited to studies in English that reflected general preferences and were choice-based, published as full-text articles and related to health technologies. This study included 72 papers, 52% of which focused on DCEs on drug treatments. The average number of attributes used in all included DCE studies was 5.74 (SD 1.98). The most frequently used attributes in these DCEs were improvements in health (78%), side effects (57%) and cost of treatment (53%). Other, less frequently used attributes included waiting time for treatment or duration of treatment (25%), severity of disease (7%) and value for money (4%). The attributes identified might inform future DCE surveys designed to study societal preferences regarding health technologies in order to better inform decisions in health technology assessment.

SUBMITTER: Trapero-Bertran M

PROVIDER: S-EPMC6639002 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review.

Trapero-Bertran Marta M Rodríguez-Martín Beatriz B López-Bastida Julio J

PloS one 20190718 7

Discrete choice experiments (DCEs) are a way to assess priority-setting in health care provision. This approach allows for the evaluation of individuals' preferences as a means of adding criteria to traditional quality-adjusted life year analysis. The aim of this systematic literature review was to identify attributes for designing a DCE in order to then develop and validate a framework that supports decision-making on health technologies. Our systematic literature review replicated the methods ...[more]

PMID: 31318926

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Project description:BACKGROUND: Discrete choice experiments (DCEs) are attribute-driven experimental techniques used to elicit stakeholders' preferences to support the design and implementation of policy interventions. The validity of a DCE, therefore, depends on the appropriate specification of the attributes and their levels. There have been recent calls for greater rigor in implementing and reporting on the processes of developing attributes and attribute-levels for discrete choice experiments (DCEs). This paper responds to such calls by carefully reporting a systematic process of developing micro health insurance attributes and attribute-levels for the design of a DCE in rural Malawi. METHODS: Conceptual attributes and attribute-levels were initially derived from a literature review which informed the design of qualitative data collection tools to identify context specific attributes and attribute-levels. Qualitative data was collected in August-September 2012 from 12 focus group discussions with community residents and 8 in-depth interviews with health workers. All participants were selected according to stratified purposive sampling. The material was tape-recorded, fully transcribed, and coded by three researchers to identify context-specific attributes and attribute-levels. Expert opinion was used to scale down the attributes and levels. A pilot study confirmed the appropriateness of the selected attributes and levels for a DCE. RESULTS: First, a consensus, emerging from an individual level analysis of the qualitative transcripts, identified 10 candidate attributes. Levels were assigned to all attributes based on data from transcripts and knowledge of the Malawian context, derived from literature. Second, through further discussions with experts, four attributes were discarded based on multiple criteria. The 6 remaining attributes were: premium level, unit of enrollment, management structure, health service benefit package, transportation coverage and copayment levels. A final step of revision and piloting confirmed that the retained attributes satisfied the credibility criteria of DCE attributes. CONCLUSION: This detailed description makes our attribute development process transparent, and provides the reader with a basis to assess the rigor of this stage of constructing the DCE. This paper contributes empirical evidence to the limited methodological literature on attributes and levels development for DCE, thereby providing further empirical guidance on the matter, specifically within rural communities of low- and middle-income countries.

Project description:BackgroundAtypical hemolytic uremic syndrome is a rare disease caused by complement dysregulation that can lead to progressive kidney damage or death if untreated. Owing to its rarity, the impact of atypical hemolytic uremic syndrome and available therapies (eculizumab and ravulizumab) on patients' health-related quality of life is difficult to describe, but such data are required for an economic evaluation.ObjectiveThe objective of this study was to estimate utility values for atypical hemolytic uremic syndrome-related attributes in five countries for an economic evaluation.MethodsUsing discrete choice experiment surveys, key atypical hemolytic uremic syndrome-related attributes (life expectancy, administration frequency, risk of meningitis, need for hospitalization, and risk of kidney impairment) were evaluated in adult general population samples from Australia, Canada, the Netherlands, Sweden, and the UK. Survey choice sets were constructed using a published orthogonal array. A mixed-effects logit model estimated preference strength for each attribute. Utilities were estimated using marginal substitution rates between overall survival and other attributes, weighted against average life expectancy.ResultsAcross all countries (N = 2382), utility weights revealed a consistent pattern: participants were averse to the risk of kidney impairment (disutility/utility weight range: -0.185 to -0.158), risk of meningitis (-0.041 to -0.032), and the need for hospitalization (-0.063 to -0.048), but preferred 8-weekly vs 2-weekly infusions over 1 h (0.013-0.039).ConclusionsAlthough all attributes played a role in determining treatment preferences, the largest drivers were life expectancy and risk of kidney impairment. Participants favored 8-weekly dosing (corresponding to ravulizumab administration frequency) vs 2-weekly dosing. The discrete choice experiment was designed such that estimated (dis)utility weights can be used in future cost-effectiveness models in atypical hemolytic uremic syndrome.

Project description:BackgroundPrimary care is a key element of health care systems and addresses the main health problems of the population. Due to the demographic change, primary care even gains in importance. The knowledge of the patients' preferences can help policy makers as well as physicians to set priorities in their effort to make health care delivery more responsive to patients' needs. Our objective was to describe which aspects of primary care were included in preference studies and which of them were the most preferred aspects.MethodsIn order to elicit the preferences for primary care, a systematic literature search was conducted. Two researchers searched three electronic databases (PubMed, Scopus, and PsycINFO) and conducted a narrative synthesis. Inclusion criteria were: focus on primary health care delivery, discrete choice experiment as elicitation method, and studies published between 2006 and 2015 in English language.ResultsWe identified 18 studies that elicited either the patients' or the population's preferences for primary care based on a discrete choice experiment. Altogether the studies used 16 structure attributes, ten process attributes and four outcome attributes. The most commonly applied structure attribute was "Waiting time till appointment", the most frequently used process attribute was "Shared decision making / professional's attention paid to your views". "Receiving the 'best' treatment" was the most commonly applied outcome attribute. Process attributes were most often the ones of highest importance for patients or the population. The attributes and attribute levels used in the discrete choice experiments were identified by literature research, qualitative research, expert interviews, or the analysis of policy documents.ConclusionsThe results of the DCE studies show different preferences for primary health care. The diversity of the results may have several reasons, such as the method of analysis, the selection procedure of the attributes and their levels or the specific research question of the study. As the results of discrete choice experiments depend on many different factors, it is important for a better comprehensibility of the studies to transparently report the steps undertaken in a study as well as the interim results regarding the identification of attributes and levels.

Project description:BackgroundWomen can choose from a range of contraceptive methods that differ in important ways. Inadequate decision support may lead them to select a method that poorly fits their circumstances, leading to dissatisfaction, misuse, or nonuse. Decision support interventions, such as decision aids, may help women choose a method of contraception that best fits their personal circumstances. To guide future decision aid development, we aim to summarize the attributes of contraceptive methods included in available decision aids as well as surveys and interviews of women actively choosing a contraceptive method.MethodsWe conducted a systematic review to identify attributes of contraceptive methods that may be important to women when engaging in this decision making process. We performed a database search of MEDLINE/PubMed, Ovid EMBASE, OVID CENTRAL, Ovid PsycInfo, EBSCO CINAHL, Popline, and Scopus from 1985 until 2013 to identify decision aids, structured interviews and questionnaires reporting attributes of contraceptive options that are of importance to women. A free-text internet search was also performed to identify additional decision support tools. All articles and tools were reviewed in duplicate for inclusion, and a summary list of attributes was compiled.ResultsWe included 20 surveys, 1 semistructured interview report and 19 decision aids, reporting 32 unique attributes. While some attributes were consistently included in surveys/interviews and decision aids, several were included more often in decision aids as opposed to surveys/interviews (e.g., STI prevention, noncontraceptive benefits, how the method is used, requirement of a healthcare provider), and vice versa (e.g., a woman's vicarious experience with contraceptive methods). Key attributes mentioned in both surveys/interviews and decision aids include efficacy (29 total mentioned) and side effects/health risks (28 total mentioned). While a limited number of decision support tools were formally evaluated, many were not rigorously studied.ConclusionsMany attributes were identified as potentially important to women choosing a method of contraception, but these were inconsistently included in the reviewed resources. Formal evaluation of decision support tools for contraceptive choice and involvement of users in the development process may lead to more user-centered design and implementation.

Project description:BackgroundDigital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people's preferences for sharing digital health data.ObjectiveThe aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts.MethodsRespondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates.ResultsIn the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents' willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels.ConclusionsRespondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism.

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What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review.

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What attributes should be included in a discrete choice experiment related to health technologies? A systematic literature review.

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