Stated Preference Discrete Choice Experiment Research Articles

Front row or backstage? Evidence on concert ticket preferences from a discrete choice experiment

AbstractSophisticated ticketing practices have become widespread in the concert industry in recent years, with a wider range of musicians now experimenting with different ticket pricing schemes. The aim of these practices is to help musicians manage ticket capacity and maximize their concert income. However, there is limited evidence on how musicians can optimally allocate and price tickets with respect to how consumers value different ticket attributes. This study uses a stated preference discrete choice experiment and choice modeling methods to analyze consumer preferences for different attributes of concert tickets. The results of the modeling exercise highlight patterns in consumer preferences across different seating areas within a hypothetical venue, as well as average preferences for other common attributes of concert tickets. Finally, this study provides evidence of the significant welfare consumers derive from the availability of new ticketing innovations in the form of VIP packages.

Developing an alternative care pathway for emergency ambulance responses for adults with epilepsy: A Discrete Choice Experiment to understand which configuration service users prefer. Part of the COLLABORATE project

IntroductionTo identify service users’ preferences for an alternative care pathway for adults with epilepsy presenting to the ambulance service. MethodsExtensive formative work (qualitative, survey and knowledge exchange) informed the design of a stated preference discrete choice experiment (DCE). This hypothetical survey was hosted online and consisted of 12 binary choices of alternative care pathways described in terms of: the paramedic's access to medical records/ ‘care plan’, what happens next (described in terms of conveyance), time, availability of epilepsy specialists today, general practitioner (GP) notification and future contact with epilepsy specialists. DCE scenarios were described as: (i) typical seizure at home. (ii) typical seizure in public, (iii) atypical seizure. Respondents were recruited by a regional English ambulance service and by national public adverts. Participants were randomised to complete 2 of the 3 DCEs. ResultsPeople with epilepsy (PWE; n = 427) and friends/family (n = 167) who completed the survey were representative of the target population. PWE preferred paramedics to have access to medical records, non-conveyance, to avoid lengthy episodes of care, availability of epilepsy specialists today, GP notification, and contact with epilepsy specialists within 2–3 weeks. Significant others (close family members or friends) preferred PWE experiencing an atypical seizure to be conveyed to an Urgent Treatment Centre and preferred shorter times. Optimal configuration of services from service users’ perspective far out ranked current practice (rank 230/288 possible configurations). DiscussionPreferences differ to current practice but have minimal variation by seizure type or stakeholder. Further work on feasibility of these pathways in England, and potentially beyond, is required.

Aggregating social benefits of endangered species protection: the case of the Cook Inlet beluga whale

ABSTRACT The Cook Inlet beluga whale (CIBW) is an endangered whale found in waters off the state of Alaska that is protected under the U.S. Endangered Species Act. The federal recovery plan estimates recovery costs will total $73 million (in 2013 dollars). In this study, we use data from a stated preference discrete choice experiment (CE) study to estimate the aggregate benefits of recovering the CIBW and generally for improving its conservation status and reducing extinction risk. Estimated CE models account and test for utility scale heterogeneity, attribute non-attendance, self-selection bias, and demographic effects. Aggregation methods that differ in adjustments made to the mean household welfare and/or to the number of population units are compared by assessing their impact on the resulting aggregate (population-level) welfare estimates. Alaska households are willing to pay between $34 million (95% CI of [$25 million, $44 million]) and $103 million ([$74 million, $131 million]) for full recovery of the CIBW, depending upon the model and aggregation assumptions. While some of the state-level recovery value estimates are below the total cost of combined federal and state recovery actions, accounting for welfare benefits beyond the state of Alaska justifies recovery actions by the benefit–cost criterion.

What Features of Fertility Treatment do Patients Value? Price Elasticity and Willingness-to-Pay Values from a Discrete Choice Experiment.

Infertility is a medical condition affecting an estimated 186 million people worldwide. Medically assisted fertility treatments allow many of these individuals to have a baby. Insights about preferences of patients who have experienced fertility treatment should be used to inform funding policies and treatment configurations that best reflect the patients' voice and the value of fertility treatment to patients. To explore the preferences for fertility treatment attributes of infertile women who had previously undergone or were undergoing fertility treatments-ex post perspective. We used data from a stated-preference discrete choice experiment (DCE) among 376 Australian women who had undergone or were undergoing fertility treatment. Respondents chose their preferred treatment choices in 12 hypothetical treatment choice scenarios described by seven attributes (success rates, side effects, counselling/peer support, treatment journey, continuity of care, availability of experimental treatment and out-of-pocket cost). We estimated random parameter logit (RPL) and latent class (LC) models that accounted for preference heterogeneity. The results were used to derive price elasticities of demand and marginal willingness-to-pay (WTP) values for the treatment attributes explored within the DCE survey. Income level did not have a significant effect on marginal WTP for fertility treatment attributes. The demand for fertility treatment from an ex post perspective was found to be highly inelastic (treatment cost changes had almost no impact on demand). Success rates and out-of-pocket costs were significant and important predictors of individuals' treatment choices conditional on the attributes and levels included in the study. These were followed by counselling/peer support, side effects, treatment journey, continuity of care, and availability of experimental treatment, in that order. Respondents were willing to pay $383-$524 per one percentage point increase in the treatment success rate and over $2000 and over $3500 to avoid moderate and significant side effects, respectively (values are reportedin AU$). Latent class models revealed that the majority of respondents (51%) were risk-averse success-rate seekers. Infertile women who had previously undergone or were undergoing fertility treatment valued fertility treatment highly as reflected by highly price-inelastic demand. Success rate of treatment and out-of-pocket costs were the most important attributes and largely determined patients' WTP for fertility treatment relative to the attributes and levels used in the study. While further research should investigate the price sensitivity of women who have not experienced fertility treatment, these results might explain why women continue fertility treatment once they have commenced despite their financial capacity to pay. Future research should also determine patients' price elasticities for a fertility treatment program with multiple treatment cycles.

Information sharing preferences within buildings: Benefits of cognitive interviewing for enhancing a discrete choice experiment

To design and operate energy efficient and comfortable buildings it is important to know what the occupants’ preferences for indoor environmental quality would be. These preferences are related to a range of personal characteristics that occupants may or may not be willing to share. Preparing materials for a forthcoming stated preference discrete choice experiment (SPDCE) aimed at investigating willingness of building occupants to share information, we conducted cognitive-interview pretesting with 12 participants to find out whether these materials were interpretable and meaningful. Qualitative analysis identified seven important limitations, including misinterpretations and uncertainties arising from language and difficulties imagining the situation and options being described. Most participants expressed some desire for a deeper understanding and were not satisfied with the choices they were asked to make. We discuss how identifying these limitations assisted in refining these SPDCE materials, the potential cognitive interviewing has for enhancing the validity of study materials and the importance of better understanding when researching occupant behaviours.

Analyzing Prospective Owners’ Choice Decision towards Plug-in Hybrid Electric Vehicles in Urban India: A Stated Preference Discrete Choice Experiment

Plug-in Hybrid Electric Vehicles (PHEVs) can help decarbonize road transport in urban India. To accelerate the diffusion of PHEVs, investigation of commuter preferences towards the attributes of PHEVs is necessary. Therefore, the present study analyzes prospective owners’ choice decisions towards PHEVs in a typical Indian context. A stated preference survey was designed to collect responses from the current owners of conventional vehicles (CVs) in Delhi, India, and Mixed Logit (ML) models were developed to estimate commuters’ Willingness To Pay (WTP) for a set of key PHEV-specific attributes. The decomposition effect of prospective owners’ sociodemographic characteristics and trip characteristics on the mean estimates of random parameters was investigated by developing ML models with heterogeneity. Subsequently, the influence of improvement of each PHEV-specific attribute on prospective owners’ choice probability was investigated by calculating marginal effects. Among the various PHEV-specific attributes considered in the present study, high WTPs are observed for decrease in battery recharging time, reduction in tailpipe emission and increase in electric range. Therefore, an added emphasis on these attributes by vehicle manufacturers is likely to enhance the attractiveness of PHEVs to Indian commuters. The results also highlight the importance of government subsidy for promoting PHEVs in the Indian market. Prospective owners’ income, availability of home-based parking space, and average daily trip length are found to significantly influence the choice decision of Indian commuters towards PHEVs.

Stay-at-home orders and the willingness to stay home during the COVID-19 pandemic: A stated-preference discrete choice experiment.

The spread of COVID-19 in the Spring of 2020 prompted state and local governments to implement a variety of policies, including stay-at-home (SAH) orders and mandatory mask requirements, aimed at reducing the infection rate and the severity of the pandemic’s impact. We implement a discrete choice experiment survey in three major U.S. States—California, Georgia, and Illinois—to empirically quantify individuals’ willingness to stay (WTS) home, measured as the number of weeks of a potential new SAH order, to prevent the spread of the COVID-19 disease and explore factors leading to their heterogeneous WTS. Our results demonstrate broad support for statewide mask mandates. In addition, the estimate of WTS to lower new positive cases is quite large, approximately five and half weeks, even though staying home lowers utility. We also find that individuals recognize the trade-offs between case reduction and economic slowdown stemming from SAH orders when they decide to stay home or not. Finally, pandemic related factors such as age, ability to work from home, and unemployment status are the main drivers of the heterogeneity in individuals’ WTS.

PREFERENCE MODELLING IN R: A TRIAL ON HOME BUYERS’ WILLINGNESS TO PAY

Modelling stated preferences is an almost mystical science and as there is no data explaining how the sustainable feature in homes would effectively encourage homebuyers to invest in sustainable housing, it is important to investigate the buyers’ willingness to pay (WTP) for sustainable housing. The study of stated preferences often requires the use of specialised software or proprietary programs, which can be difficult and/or expensive to use. This study proposes to re-purpose the ‘support.CEs’ package, a program written in the R programming language, from its agronomic roots to measure home buyer preferences for sustainable housing. These are demonstrated through a stated preference discrete choice experiment of choosing model houses with differing levels of energy savings, renewable energy generation, landscaping, soundproofing, ventilation, and price differences. A pilot study was performed using an online survey, constructed using the LMA design tool provided in the ‘support.CEs’ package. The survey was also separated into six blocks of six questions each to reduce the cognitive burden on respondents. The survey was distributed through social media channels. Preliminary results with a limited sample of 20 respondents with mixed income, age, and occupational demographics, analysed using the package’s clogit function, that performs conditional logit estimations, have shown that the results have a statistically reliable adjusted rho-squared value and that all coefficients show the expected signs. From this study, it can be concluded that the ‘support.CEs’ package can be used to model home buyer preferences and that adequate blocking allows for the measurement of a higher number of variables despite having smaller sample sizes.

Patient Preferences For Specialty Pharmacy Services: A Stated Preference Discrete-Choice Experiment in China.

Objectives: To survey, analyze, and ascertain the preferences for specialty pharmacy services among patients requiring complex care and to provide evidence to support specialty pharmacy service decision-making in China.Methods: To identify essential service attributes and levels, a review of the literature, discussions with specialty pharmacy managers and a pilot questionnaire were conducted. A D-efficient fractional factorial design was used to generate the discrete-choice experiment (DCE) questionnaire. A face-to-face survey of patients with chronic illness and their families or friends was conducted at three specialty pharmacies in Chengdu and Qingdao, China. A mixed logit model was used for estimation.Results: Six relevant attributes were identified and incorporated into the DCE questionnaire. A total of 417 participants completed the survey (mean age 43 years, 45.1% males), and 32.1% had lung cancer. The conditional relative importance showed that the most critical attribute was “frequency of telephone follow-up to monitor adverse drug reactions (ADRs), “followed by “mode of drug delivery,” “provider of medication guidance services,” and “availability of medical insurance consultation”; the least important attribute was “business hours.” A 1 min increase in time spent led to a 0.73% decrease in the probability that a service profile would be chosen. Negative preferences were noted for ADR monitoring by telephone follow-up once a year (β = −0.23, p < 0.001) and business hours [8:30–20:00 (Monday to Friday), 8:30–17:30 (weekend)] (β = −0.12, p < 0.001). Compared with women, men had a higher preference for service monitoring ADRs once every 3 months.Conclusions: Preference measurements showed that “frequency of telephone follow-up to monitor ADRs” had the most critical impact on decisions, followed by “mode of drug delivery.” Specialty pharmacies in China need to take these findings into account to improve their design to increase uptake and patient loyalty.

Consumer preferences for hydrogen fuel cell vehicles in Japan

After the successful adoption and deployment of electric vehicles in Norway with the support of generous government-led incentives, several other countries began introducing policy incentives for environmental-friendly vehicles. In light of Japan’s goal of becoming a hydrogen society, this paper examines the preferences of Japanese citizens for hydrogen fuel cell vehicles (HFCVs) through a stated preference discrete choice experiment involving carefully chosen vehicle attributes and incentives. To this end, it uses mixed logit model on the choice scenario data to elicit the behavioral responses. Governmental incentives such as free public parking and free public transport significantly impact the preferences for HFCVs. In terms of socio-demographic characteristics, education and apartment parking remarkably affect the adoption of HFCVs. Although the preference of Japanese consumers for HFCVs is significantly lower than that for conventional vehicles, a well-designed package of policy incentives involving free public parking and public transport can drive Japan’s push for HFCVs in the long run.

Preferences heterogeneity of health care utilization of community residents in China: a stated preference discrete choice experiment

BackgroundTo tackle the issue with the low usage of primary healthcare service in China, it is essential to align resource distribution with the preferences of the community residents. There are few academic researches for describing residents’ perceived characteristics of healthcare services in China. This study aims to investigate the preferences of healthcare services utilization in community residents and explore the heterogeneity. The findings will be useful for the policy makers to take targeted measures to tailor the provision of healthcare services.MethodsThe face-to-face interviews and surveys were conducted to elicit four key attributes (care provider; mode of services; cost; travel time) of the preference from community residents for healthcare utilization. A rational test was presented first to confirm the consistency, and then 16 pairs of choice tasks with 12 sociodemographic items were given to the respondents. Two hypothetical options for each set, without an opt-out option, were presented in each choice task. The latent class analysis (LCA) was used to analyse the data.ResultsTwo thousand one hundred sixty respondents from 36 communities in 6 cities were recruited for our study. 2019 (93.47%) respondents completed valid discrete choice experiment (DCE) questionnaires. The LCA results suggested that four groups of similar preferences were identified. The first group (27.29%) labelled as “Comprehensive consideration” had an even preference of all four attributes. The second group (37.79%) labelled as “Price-driven” preferred low-price healthcare services. The third group labelled as “Near distance” showed a clear preference for seeking healthcare services nearby. The fourth group (34.18%) labelled as “Quality seeker” preferred the healthcare service provided by experts. Willingness to pay (WTP) results showed that people were willing to accept CNY202.12($29.37) for Traditional Chinese Medicine (TCM) services and willing to pay CNY604.31($87.81) for the service provided by experts.ConclusionsOur study qualitatively measures the distinct preferences for healthcare utilization in community residents in China. The results suggest that the care provider, mode of services, travel time and cost should be considered in priority setting decisions. The study, however, reveals substantial disagreement in opinion of TCM between different population subgroups.

Payer Preferences and Willingness to Pay for Genomic Precision Medicine: A Discrete Choice Experiment.

Although precision medicine using genetic information offers significant promise, its uptake and eventual clinical and economic impacts are uncertain. Health care payers will play an important role in evaluating evidence and costs to develop coverage and reimbursement policies. To elicit U.S. health care payer preference for genomic precision medicine to better understand trade-offs among clinical benefits, uncertainty, and cost. Using key informant interviewer discussions (N = 6 payers), we identified 6 key attributes of genetic tests important to payers: type of information the test provides (screening vs. treatment prediction), probability that the member has an informative genetic marker, expert agreement on changing medical care based on the marker, quality-of-life gains, life expectancy gains (with statistical uncertainty), and cost to the plan. We designed a stated preference discrete choice experiment using these attributes and administered a web survey to a sample of U.S. health care payers. We used effects coding and analyzed the data using an error component mixed logit modeling approach. The survey response rate was 58% (150 participants completed the survey). Approximately 53% of respondents had previous experience evaluating genetic tests for reimbursement, and 85% had more than 5 years of health care decision-making experience. Payers valued improvements in quality of life the most (marginal willingness to pay [mWTP] of $1,513-$6,076), followed by medical expert agreement on the treatment change (mWTP of $2,881-$3,489). Payers placed a relatively lower value for genetic tests with lower marker probability (mWTP of $2,776 for highest marker probability to $423 for lowest marker probability). Payers mWTP was lowest for resolving uncertainty in quality of life (mWTP of $1,513-$2,031) and life expectancy gains ($536-$1,537). Payers exhibited a strong preference for genetic tests that improved quality of life, had high expert agreement on changing medical care, and increased life expectancy. These findings suggest that payers will need evidence of clinical utility to support coverage and reimbursement of genomic precision medicine. This study was supported by a grant from the NIH Common Fund and NIA (1U01AG047109-01) via the Personalized Medicine Economics Research (PriMER) project. Unrelated to this study, Veenstra reports consulting fees from Bayer and Halozyme; Basu reports consulting fees from Salutis Consulting; and Reiger reports consulting fees from Roche. Carlson reports grants from Institute for Clinical and Economic Review, during the conduct of this study, and consulting fees from Bayer, Adaptive Biotechnologies, Allergan, Galderma, and Vifor Pharma, unrelated to this study.

Stay-at-Home Orders and the Willingness to Stay Home During the COVID-19 Pandemic: A Stated-Preference Discrete Choice Experiment

The spread of COVID-19 in the Spring of 2020 prompted state and local governments to implement a variety of policies, including stay-at-home (SAH) orders and mandatory mask requirements, aimed at reducing infection rates and the severity of the pandemic’s impact. We implement a discrete choice experiment survey in three major U.S. States - California, Georgia, and Illinois - to empirically quantify individuals’ willingness to stay (WTS) home, measured as the number of weeks of a potential new SAH order, to prevent the spread of the COVID-19 disease and explore factors leading to their heterogeneous WTS. Our results demonstrate broad support for statewide mask mandates. In addition, the estimate of WTS to lower new positive cases is quite large, approximately five and half weeks, even though staying home lowers utility. We also find that individuals recognize the trade-offs between case reduction and economic slowdown stemming from SAH orders when they decide to stay home or not. Finally, pandemic related factors such as age, ability to work from home, and unemployment status are the major drivers of the heterogeneity in individuals’ WTS.

Don’t judge a book by its cover: examining digital disruption in the book industry using a stated preference approach

This paper uses a market segmentation approach to examine the effects of digital disruption in the book industry. A Bayesian efficient experimental design is employed in order to develop a stated preference discrete choice experiment that incorporates an array of book formats and attributes. The experiment was conducted on a panel of Australian readers. The results were analysed using a latent class model, leading to the identification of three distinct classes of book readers. The largest class of readers is comprised of ‘technological adopters’ who demonstrate a similar willingness to read on both traditional printed book formats and newer digital ones. Members of this class rely on critical review scores to make purchasing decisions and are the youngest of the three classes. Second is a class of ‘popular readers.’ This group consists of price-sensitive readers who clearly favour reading popular fiction on traditional paper-based book formats only. The third group are ‘avid readers’ who exhibit the highest willingness to pay for books and show a desire to read books of all genres. The identification of discrete segments of readers, along with their associated price elasticities and willingness to pay figures, can assist book industry stakeholders (such as book publishers and sellers) with the development of effective strategies to guide them through the various stages of digital book formats technology adoption life cycle. Such results can also be used to help steer cultural policy makers during a period of rapid technological change and uncertainty.

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

BackgroundDecision makers have huge problems when attempting to attribute social value to the improvements achieved by new drugs, especially when considering the use of orphan drugs for rare diseases. We present the results of a pilot study aimed to investigate patient preferences regarding public funding for drugs used to treat rare diseases.MethodsAn online questionnaire was used as a discrete choice experiment (DCE) survey to explore the preferences of patients with cystic fibrosis and haemophilia in Italy. The questionnaire focused on relevant issues that were defined in a review of the literature. A conditional logistic model showed preferences for specific attributes.ResultsA total of 54 questionnaires (20% response rate) were completed. The issues that received the greatest attention were improvement in health, treatment cost and value for money. However, disease severity and the availability of other treatments were important social values that could not be ignored.ConclusionsThe findings presented here provide evidence as to what patients with cystic fibrosis or haemophilia think are the most important considerations on which to base decisions in health technology scenarios, and regarding the priorities for funding.

Societal preferences for fertility treatment in Australia: a stated preference discrete choice experiment

Objective: To investigate preferences for fertility treatment from the Australian general population with the aims of calculating the willingness to pay in tax contribution for attributes (characteristics) that make up treatment and for an “ideal” fertility treatment program. We also assessed whether willingness-to-pay varies by the relationship status or sexual orientation of the patient.Methods: A stated preference discrete choice experiment was administered to a panel of 801 individuals representative of the Australian general population. Seven attributes of fertility treatment under three broad categories were included: outcome, process, and cost. Attributes were identified through published literature, focus group discussions, expert knowledge, and a pilot study. A Bayesian fractional experimental design was used, and data analysis was performed using a generalized multinomial logit model. Further analyses included interaction terms and latent class modeling.Results: Six of the seven attributes influenced the choice of a treatment program. Under process attributes, individuals preferred: continuity of care of clinic staff, where patients are seen by the same doctor but different nurses at each visit; “alternative” treatments being offered to all patients; and onsite clinic counseling and peer-support groups. Personalization and tailoring of the treatment journey were not important. Among outcome attributes, the improved success rate of having a baby per cycle and significant side-effects were considered important. Cost of treatment also influenced the choice of treatment program. Individual preferences for fertility treatment were not associated with patients’ relationship status or sexual orientation. Latent class modeling revealed sub-groups with distinct fertility treatment preferences.Conclusion: This study provides important insights into the attributes that influence the preferences of fertility treatment in Australia. It also estimates socially-inclusive willingness-to-pay values in tax contributions for an “ideal” package of treatment. The results can inform economic evaluations of fertility treatment programs.

Using a stated preference discrete choice experiment to assess societal value from the perspective of decision-makers in Europe. Does it work for rare diseases?

Objectives: To pilot the feasibility of using a discrete choice experiment (DCE) design to investigate individual preferences from the decision-maker perspective regarding the use of public funding for orphan drugs and generate prior information for future experimental designs.Methods: A DCE was used on a convenience sample of participants from five European countries (England, France, Germany, Italy and Spain), exploring their preferences in distinct healthcare scenarios involving orphan drugs. A preliminary review of the empirical literature on distributive preferences informed the selection of attributes and their levels in the design. An online questionnaire was used to conduct the DCE survey.Results: A total of 199 questionnaires were completed. The five country model showed relative preference for some attributes over others: cost of treatment, improvement in health, value for money and availability of treatment alternatives received the greatest attention. However, disease severity, beginning of life, waiting times and side effects were also shown to be important social values that should not be ignored.Conclusions: The findings presented in this study provide insight about the preferences that can influence decisions on orphan drugs in different countries. This study also provides valuable prior information that could inform future DCE designs in this area.

Scale heterogeneity in discrete choice experiment: An application of generalized mixed logit model in air travel choice

This study explores to what extent scale heterogeneity (i.e., varying standard deviation of the errors across consumers) is important in air travel choice using data from a stated preference discrete choice experiment. We used generalized mixed logit model (GMIXL) that nests scale and taste heterogeneity in the context of air travel ticket choice. We found empirical evidence of the importance of often-neglected scale heterogeneity along with pre-dominant taste heterogeneity. The findings suggests that it is important to account for various forms of heterogeneity with GMIXL to model air travel demand to identify variety of consumer segments, which has implications for airline optimal menu of ticket offerings and pricing strategies.

PHP171 - Drivers of Genomic Precision Medicine Adoption in the US: Payer Preferences

The current literature on the drivers of genomic precision medicine adoption is limited. The objective of this study was to estimate healthcare payers’ preferences for genomic precision medicine tests. Using qualitative research methods (n=6 payers), we identified six key attributes for payers’ uptake of genetic tests: type of information the test provides (screening vs. treatment prediction), probability that the member has an informative genetic marker, experts’ agreement on changing medical care based on the marker, members’ quality-of-life gains, life expectancy gains with statistical uncertainty, and cost to the plan. We designed a stated preference discrete choice experiment using these attributes and administered a web-survey on a representative sample of US healthcare payers. We used effects coding and analyzed the data using a nested logit modeling approach. The survey response rate was 58% (150 participants completed the survey). Approximately 53% respondents had prior experience evaluating genetic tests for reimbursements and 85% had greater than 5 years of healthcare decision-making experience. Based on the payers’ preferences, the relative importance of the attributes was in the following order of decreasing importance: quality-of-life, gains in life expectancy, expert agreement in recommendations, probability that the member has an informative genetic marker, cost to the plan, and screening vs treatment prediction. Payers’ marginal willingness to pay (mWTP) was highest for genetic tests that lead to improvement in quality-of-life ($544 to $5856) and lowest for tests that resolved uncertainty in life expectancy gains ($656 to $1679). The mWTP for an increase in the marker probability ranged from $434 to $2846. Payers exhibited a strong preference for genetic tests that improved quality of life and life expectancy. The results of this study can be used to predict genetic test adoption, guide future investment in and design of genetic tests, and inform pricing and reimbursement decisions.

PHP153 - What US Healthcare Providers Value in Genomic Precision Medicine: A Discrete Choice Experiment

The current literature on physician preferences for genomic precision medicine is limited. The objective of this study was to estimate healthcare providers’ preferences for attributes that influence their recommendation of genetic tests to their patients. Using qualitative research (n=5 providers), we identified the following attributes as important to healthcare providers for test recommendation: type of information from the genetic test (disease screening vs. treatment change, or both), prevalence of genetic marker, expert agreement on recommendations, change in quality of life and life expectancy gains (with statistical uncertainty), and test cost. We used these attributes to design a stated preference discrete choice experiment and administered a web-survey on a representative sample of US healthcare providers. We used effects coding and analyzed the data using a nested logit modeling approach. The survey response rate was 67% (356 participants completed the survey). The respondents had a mean practice experience of 21.1 years and 87% had previously ordered genetic testing for their patients. Based on the relative importance of attributes, the genetic tests’ attributes ranked in the following order of decreasing importance: quality-of-life, gains in life expectancy, test cost, expert agreement in recommendations, prevalence of the genetic marker, and screening vs treatment prediction. Providers’ marginal willingness to pay (mWTP) was highest for genetic tests that lead to improvement in quality-of-life ($1199 to $5929) and lowest for tests that resolved uncertainty in life expectancy gains ($64 to $219). The mWTP for an increase in medical experts’ agreement on recommendations ranged from $134 to $1955. Providers exhibited a strong preference for the genetic tests that improved their patients’ quality-of-life, increased patients’ life expectancy, and cost less. The estimated preferences of providers over different characteristics of genetic tests in this study can help predict genetic tests’ adoption and inform patient/provider shared decision making.