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Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments.

ABSTRACT: Given the increasing number of genetic tests available, decisions have to be made on how to allocate limited health-care resources to them. Different criteria have been proposed to guide priority setting. However, their relative importance is unclear. Discrete-choice experiments (DCEs) and best-worst scaling experiments (BWSs) are methods used to identify and weight various criteria that influence orders of priority. This study tests whether these preference eliciting techniques can be used for prioritising genetic tests and compares the empirical findings resulting from these two approaches. Pilot DCE and BWS questionnaires were developed for the same criteria: prevalence, severity, clinical utility, alternatives to genetic testing available, infrastructure for testing and care established, and urgency of care. Interview-style experiments were carried out among different genetics professionals (mainly clinical geneticists, researchers and biologists). A total of 31 respondents completed the DCE and 26 completed the BWS experiment. Weights for the levels of the six attributes were estimated by conditional logit models. Although the results derived from the DCE and BWS experiments differed in detail, we found similar valuation patterns in the DCE and BWS experiments. The respondents attached greatest value to tests with high clinical utility (defined by the availability of treatments that reduce mortality and morbidity) and to testing for highly prevalent conditions. The findings from this study exemplify how decision makers can use quantitative preference eliciting methods to measure aggregated preferences in order to prioritise alternative clinical interventions. Further research is necessary to confirm the survey results.

SUBMITTER: Severin F

PROVIDER: S-EPMC3798841 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

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Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments.

Severin Franziska F Schmidtke Jörg J Mühlbacher Axel A Rogowski Wolf H WH

European journal of human genetics : EJHG 20130313 11

Given the increasing number of genetic tests available, decisions have to be made on how to allocate limited health-care resources to them. Different criteria have been proposed to guide priority setting. However, their relative importance is unclear. Discrete-choice experiments (DCEs) and best-worst scaling experiments (BWSs) are methods used to identify and weight various criteria that influence orders of priority. This study tests whether these preference eliciting techniques can be used for ...[more]

PMID: 23486538

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Project description:IntroductionFollow-up care is important for gastric cancer survivors, but follow-up strategies for gastric cancer survivors remain inconsistent, and compliance of gastric cancer survivors with follow-up care is very low. Understanding the needs and preferences of gastric cancer survivors is conducive to developing appropriate and acceptable follow-up strategies, thereby improving patient compliance. Discrete choice experiments can quantify individual needs and preferences. However, to date, there is no discrete choice experiment on the preferences of gastric cancer survivors, and no studies have examined how gastric cancer survivors make choices based on different characteristics of follow-up. This paper outlines an ongoing discrete choice experiment that aims to (1) explore follow-up service-related characteristics that may affect gastric cancer survivors' choices about their follow-up, (2) elicit how gastric cancer survivors consider the trade-offs among different follow-up service options using discrete choice experiment, (3) determine whether gastric cancer survivors' needs and preferences for follow-up vary due to the economy, politics, technology and culture in different regions.Methods and analysisSix attributes were developed through a literature review, semistructured interviews and experts and focus group discussions. A fractional factorial design was used to evaluate the interaction between attributes. A multiple logit model will be used to understand the trade-off between the follow-up characteristics of gastric cancer survivors. A mixed logit model will be used to explore the willingness to pay and uptake rate of gastric cancer survivors for follow-up attributes and further explore the preferences of different groups.Ethics and disseminationThis study was approved by the ethics committee of the School of Nursing, Jilin University. The results of this study will be shared through online blogs, policy briefs, seminars and peer-reviewed journal articles and will be used to modify the current strategy of gastric cancer survivors' follow-up services according to economic development and regional culture.

Project description:BackgroundDeciding on pharmaceutical subsidy is regarded as a challenging issue for healthcare policymakers in Iran in most times. Public preferences, rarely attended in Iran, could be invaluable for including a particular drug in the list of subsidized medications.ObjectivesThe current study aims to elicit the public preferences to develop an evidence-based decision-making framework for entering a drug into the list of subsidies in Iran.MethodsDiscrete Choice Experiment (DCE) was employed to elicit the public preferences. Around 34 attributes were identified based on the systematic review and interview with 51 experts. By holding an expert panel, 7 attributes were finalized, namely: the survival after treatment, quality of life after treatment (QoL), alternative treatment, age group of the target population, cost burden for the government, disease severity, and drug manufacturer country. Next, 1224 households were selected for the survey in the city of Tehran, using random cluster sampling. Data were analyzed using conditional logit model.ResultsThe survival after treatment (β = 1.245; SE = 0.053) and disease severity (β =- 0.143; SE = 0.043) had the highest and lowest priority, respectively, in the preferences for allocating subsidy to a drug. In developed region, unlike the other two regions, the level of domestic drug production (β =- 0.302; SE = 0.073) was inversely associated with preferences toward allocating subsidy to a drug. In contrast to other districts, those living in district number one (β = 2.053; SE = 0.138) gave the highest value to promoting the QoL after treatment.ConclusionsIt is suggested that policymakers pay more attention to attributes such as effectiveness and alternative treatment when developing an evidence-based framework for entering a drug into the list of subsidies. This study highlighted the public belief in the government's subsidy for medicines, provided that, this results in an increased survival and QoL.

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.

Dataset Information

Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments.

Publications

Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments.

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