Discrete Choice Experiment Data Research Articles

Patients' Preferences for Sphingosine-1-Phosphate Receptor Modulators in Multiple Sclerosis Based on Clinical Management Considerations: A Choice Experiment.

Several sphingosine-1-phosphate receptor (S1PR) modulators are available in the US for treating relapsing forms of multiple sclerosis (RMS). Given that these S1PR modulators have similar efficacy and safety, patients may consider the clinical management characteristics of the S1PR modulators when deciding among treatments. However, none of the S1PR modulators is clearly superior in every aspect of clinical management, and for some treatments, clinical management varies based on a patient's comorbid health conditions (e.g., heart conditions [HC]). This study aimed to determine which S1PR modulator patients with relapsing-remitting multiple sclerosis (RRMS) would prefer based on clinical management considerations, and to estimate how different clinical management considerations might drive these preferences. Preferences were explored separately for patients with and without comorbid HC. A multicriteria decision analysis was conducted on S1PR modulators approved to treat RMS: fingolimod, ozanimod, siponimod, and ponesimod. Clinical management preferences of patients with RRMS were elicited in a discrete choice experiment (DCE) in which participants repeatedly chose between hypothetical S1PR modulator profiles based on their clinical management attributes. Attributes included first-dose observations, genotyping, liver function tests, eye examinations, drug-drug interactions, interactions with antidepressants, interactions with foods high in tyramine, and immune system recovery time. Preferences were estimated separately for patients with HC and without HC (noHC). Marginal utilities were calculated from the DCE data for each attribute and level using a mixed logit model. In the multicriteria decision analysis, partial value scores were created by applying the marginal utilities for each attribute and level to the real-world profiles of S1PR modulators. Partial value scores were summed to determine an overall clinical management value score for each S1PR modulator. Four hundred patients with RRMS completed the DCE. Ponesimod had the highest overall value score for patients both without (n=341) and with (n=59) HC (noHC: 5.1; HC: 4.0), followed by siponimod (noHC: 4.9; HC: 3.3), fingolimod (noHC: 3.4; HC: 2.8), and ozanimod (noHC: 0.9; HC: 0.8). Overall, immune system recovery time contributed the highest partial value scores (noHC: up to 1.9 points; HC: up to 1.2 points), followed by the number of drug-drug interactions (noHC: up to 1.2 points; HC: up to 1.7 points). When considering the clinical management of S1PR modulators, the average patient with RRMS is expected to choose a treatment with shorter immune system recovery time and fewer interactions with other drugs. Patients both with and without heart conditions are likely to prefer the clinical management profile of ponesimod over those of siponimod, fingolimod, and ozanimod. This information can help inform recommendations for treating RRMS and facilitate shared decision making between patients and their doctors.

A Methodological Study to Compare Alternative Modes of Administration with Value EQ-5D Using Preference-Elicitation Techniques

ObjectivesTime trade-off (TTO) and discrete choice experiment (DCE) preference-elicitation techniques can be administered using face-to-face interviews (F2F), unassisted online (UO) surveys, or remote-assisted (RA) interviews. The objective of this study was to explore how the mode of administration affects the quality and reliability of preference-elicitation data. MethodsEQ-5D-5L health states were valued using composite TTO (cTTO) and DCE approaches by the UK general population. Participants were allocated to 1 of 2 study groups. Group A completed both F2F and UO surveys (n = 271), and group B completed both RA and UO surveys (n = 223). The feasibility of survey completion and the reliability and face-validity of data collected were compared across all modes of administration. ResultsFewer participants reported receiving sufficient guidance on the cTTO tasks during the UO survey compared with the 2 assisted modes. Participants across all modes typically reported receiving sufficient guidance on the DCE tasks.cTTO data were less reliable from the UO survey compared with both assisted modes, but there were no differences in DCE data reliability. cTTO data from all modes demonstrated face-validity; however, the UO survey produced higher utilities for moderate and severe health states than both assisted modes. Both F2F and RA modes provided comparably reliable data. ConclusionsThe reliability of DCE data is not affected by the mode of administration. Interviewer-assisted modes of administration (F2F or RA) yield more reliable cTTO data than unassisted surveys. Both F2F and RA surveys produced similar-quality data.

Preference-based utility weights for the Individualized Neuromuscular Quality of Life Questionnaire (INQoL), with a focus on non-dystrophic myotonia (NDM).

The Individualized Neuromuscular Quality of Life Questionnaire (INQoL) is used to measure quality of life in neuromuscular disorders such as non-dystrophic myotonia (NDM). Here we report methods to estimate utilities, with a focus on NDM, from this questionnaire based on two preference elicitation exercises. Eight items from the INQoL were selected with input from three neuromuscular disorder clinical experts with expertise in treating NDM. A discrete choice experiment (DCE) survey of UK general public respondents (n = 508) described outcomes defined by the INQoL items. The same 8 items were also valued using time trade-off (TTO) face-to-face interviews (n = 200). A hybrid regression modelling approach combined both datasets to inform the utility weights. Hybrid modelling of DCE and TTO data in conjunction improved out-of-sample predictive accuracy. The selected INQoL utility model indicates substantial disutility associated with all eight dimensions of health, with the greatest losses associated with subjective items such as pain and depression. The hybrid modelling approach allows us to combine data from the two methodologies and maximize the information from each to inform the utility weights for the INQoL. The TTO is the more conventional valuation method, but combined with the larger DCE study produced better descriptive coverage. This is a relatively novel method for estimating weights which we think is particularly well suited to economic evaluations of orphan drugs.

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life.

The increasing interest in early identification of people at risk of developing dementia, has led to the development of numerous models aimed at estimating the likelihood of progression from mild cognitive impairment (MCI) to dementia. It is important to study both the need for and possible outcomes related with such prediction models, including the impact of risk predictions on perceived quality of life (QoL). This study aimed to quantify the impact that receiving a risk prediction on progression from MCI to dementia has on QoL. A Discrete Choice Experiment (DCE) and Time Trade Off (TTO) study were performed. Participants completed choice tasks related to dementia prognosis while imagining having MCI. We collected DCE data by an online survey, and TTO data via videoconferencing interviews. DCE data were analyzed using a mixed multinomial logit model and were anchored to a health state utility scale using mean observed TTO valuations. 296 people participated in the DCE and 42 in the TTO. Moderate and high predicted dementia risks were associated with decrements in utility (-0.05 and -0.18 respectively), compared to no prognostic information. Low predicted risk was associated with an increase in utility (0.06), as well as the availability of medication or lifestyle interventions (0.05 and 0.13 respectively). This study shows a significant impact of dementia risk predictions on QoL and highlights the importance of caution when sharing information about expected MCI disease courses.

Comparison of four value sets derived using different TTO and DCE approaches: application to the new region-specific PBM, AP-7D

BackgroundAP-7D is a newly developed preference-based measure (PBM) in East and Southeast Asia. However, no value set has been established yet. Comparison of the characteristics of value sets obtained by different methods is necessary to consider the most appropriate methodology for valuation survey of AP-7D.MethodWe surveyed the general population’s preference of AP-7D health states by four valuation methods (a) composite time trade-off (cTTO); (b) simple discrete choice experiment (DCE); (c) DCE with duration; and (d) ternary DCE. In Japan, we collected approximately 1,000 samples for cTTO tasks through a face-to-face survey and 2,500 samples for each of the three DCE tasks. Respondents were selected through quota sampling based on the sex and age. The cTTO data were analyzed using a linear mixed and tobit model; the DCE data were analyzed using a simple and panel conditional logit model. Where the results of the analysis showed inconsistencies, a constrained model was used.ResultsSince all the unconstrained models, except simple DCE, showed one or more inconsistencies, the constrained model was used for the analyses. The minimum values for the models were as follows: TTO model, -0.101; simple DCE model, -0.106; DCE with duration model, -0.706; ternary DCE model, -0.306. The score for the DCE with the duration model was much lower than that for the other models. Although the value sets for AP-7D differed among the four valuation methods, the ternary DCE model showed intermediate characteristics between those of the cTTO and DCE with duration models. As compared with to EQ-5D-5L, the distributions of all the scores on the Japanese AP-7D moved to the left. Although “Energy” was one of the domains with the least influence on the AP-7D score in all four models, “Burden to others” had the largest impact on the preferences.ConclusionWe constructed four value sets using different TTO and DCE methods. Our findings are expected not only to contribute to the development of AP-7D, but also other preference-based measures.

Exploring the Factors that Drive Clinical Negligence Claims: Stated Preferences of Those Who Have Experienced Unintended Harm.

Better understanding of the factors that influence patients to make a financial claim for compensation is required to inform policy decisions. This study aimed to assess the relative importance of factors that influence those who have experienced a patient safety incident (PSI) to make a claim for compensation. Participants completed an online discrete choice experiment (DCE) involving 10 single profile tasks where they chose whether or not to file a claim. DCE data were modelled using logistic, mixed logit and latent class regressions; scenario analyses, external validity, and willingness to accept were also conducted. A total of 1029 participants in the United Kingdom responded to the survey. An appropriate apology and a satisfactory investigation reduced the likelihood of claiming. Respondents were more likely to claim if they could hold those responsible accountable, if the process was simple and straightforward, if the compensation amount was higher, if the likelihood of compensation was high or uncertain, if the time to receive a decision was quicker, and if they used the government compensation scheme. Men are more likely to claim for low impact PSIs. The actions taken by the health service after a PSI, and people's perceptions about the probability of success and the size of potential reward, can influence whether a claim is made. Results show the importance of giving an appropriate apology and conducting a satisfactory investigation. This stresses the importance around how patients are treated after a PSI in influencing the clinical negligence claims that are made.

Middle-aged and older people’s preference for medical-elderly care integrated institutions in China: a discrete choice experiment study

BackgroundWith the continuing impact of the aging population, medical-elderly care integrated institutions, as a way to bear the pressure of medical and elderly care, effectively ensure the quality of life of the elderly in their later years.ObjectivesTo explore the preferences of medical-elderly care integrated institutions among Chinese middle-aged and older people and to provide a reference for establishing elderly-oriented development of medical-elderly care integrated institutions.MethodsIn this study, a discrete choice experiment (DCE) was used to investigate the preferences of people aged 45 years and older in medical-elderly care integrated institutions in China from October 20, 2022, to November 10, 2022. A mixed logit regression model was used to analyze the DCE data. Participants’ willingness to pay for each attribute was also calculated.ResultsData from 420 participants who provided valid responses were included in the analysis. In terms of the choice preference, moderate service quality (vs. poor service quality: β = 1.707, p < 0.001, 95% CI 1.343 ~ 2.071) and high medical technology level (vs. low medical technology level: β = 1.535, p < 0.001, 95% CI 1.240 ~ 1.830) were the most important attributes to middle-aged and older people, followed by monthly cost, environmental facilities, the convenience of transportation, and entertainment activities. Regarding the willingness to pay, participants were more willing to pay for service quality and medical technology level than for other attributes. They were willing to pay $3156 and $2838 more for “poor service quality” and “low medical technology level,” respectively, to receive “moderate service quality " (p = 0.007, 95% CI 963 ~ 5349) and “high medical technology level” (p = 0.005, 95% CI 852 ~ 4824).ConclusionsThe state should attach great importance to the development of medical-elderly care integrated services industry, actively optimize the model of the medical-elderly care integrated service, improve the facilities, and create a healthy environment. At the same time, give full play to the role of medical insurance, long-term care insurance, and commercial insurance, so as to improve the comprehensive quality of life of the elderly.Public contributionThe design of the experimental selection was guided by 10 experts in the field, 5 Chinese government officials, and interviews and focus group discussions, without whose participation this study would not have been possible.

Patient preferences for active ulcerative colitis treatments and fecal microbiota transplantation.

Fecal microbiota transplantation (FMT) is a promising treatment for active ulcerative colitis (UC). Understanding patient preferences can identify treatment features that may impact treatment decisions, improve shared decision-making, and contribute to patient-centered care, which is especially important in the context of novel treatments like FMT. We aimed to quantify preferences for active UC treatments, specifically FMT and biologics, and identify patient characteristics associated with different preference patterns. This is a cross-sectional survey study. We administered a discrete choice experiment (DCE) survey to elicit preferences in a sample of Canadian adults with UC. DCE data were analyzed using a main-effects mixed logit model and used to predict uptake of hypothetical scenarios reflecting alternative combinations of treatment features. Latent class modeling identified heterogeneity in patient preference patterns. Participants' (n = 201) mean age was 47.1 years (SD: 14.5 years), 58% were female, and most (84%) had at least some post-secondary education. Almost half were willing to undergo FMT. When considering treatments for active UC, the most important attributes were chance of remission and severity of rare unknown side effects. All else equal, participants were most likely to uptake treatment that involves oral capsules/pills. Participants in the class with the highest utility for chance of remission were younger, had more severe disease, and 58% indicated that they would be willing to undergo FMT. We identified characteristics of UC patients who are more likely to be interested in FMT using preference elicitation methods. Patient-centered care can be enhanced by knowing which patients are more likely to be interested in FMT, potentially improving satisfaction with and adherence to treatments for active UC to maximize the effectiveness of treatment while considering heterogeneity in patient preferences.

General practitioner preferences for telehealth consultations in Australia: a pilot survey and discrete choice experiment.

To identify and quantify general practitioner (GP) preferences related to service attributes of clinical consultations, including telehealth consultations, in Australia. GPs have been increasingly using telehealth to deliver patient care since the onset of the 2019 coronavirus disease (COVID-19) pandemic. GP preferences for telehealth service models will play an important role in the uptake and sustainability of telehealth services post-pandemic. An online survey was used to ask GPs general telehealth questions and have them complete a discrete choice experiment (DCE). The DCE elicited GP preferences for various service attributes of telehealth (telephone and videoconference) consultations. The DCE investigated five service attributes, including consultation mode, consultation purpose, consultation length, quality of care and rapport, and patient co-payment. Participants were presented with eight choice sets, each containing three options to choose from. Descriptive statistics was used, and mixed logit models were used to estimate and analyse the DCE data. A total of 60 GPs fully completed the survey. Previous telehealth experiences impacted direct preferences towards telehealth consultations across clinical presentations, although in-person modes were generally favoured (in approximately 70% of all scenarios). The DCE results lacked statistical significance which demonstrated undiscernible differences between GP preferences for some service attributes. However, it was found that GPs prefer to provide a consultation with good quality care and rapport (P < 002). GPs would also prefer to provide care to their patients rather than decline a consultation due to consultation mode, length or purpose (P < 0.0001). Based on the findings, GPs value the ability to provide high-quality care and develop rapport during a clinical consultation. This highlights the importance of recognising value-based care for future policy reforms, to ensure continued adoption and sustainability of GP telehealth services in Australia.

Eliciting preferences of persons with dementia and informal caregivers to support ageing in place in the Netherlands: a protocol for a discrete choice experiment

IntroductionAgeing in place (AIP) for persons with dementia is encouraged by European governments and societies. Healthcare packages may need reassessment to account for the preferences of care funders, patients and...

Benefit-risk preferences for treatments for newly-diagnosed multiple myeloma.

320 Background: Clinical studies are generating evidence on benefits and risks of emerging, novel treatments, including bispecifics and CAR-T, for newly diagnosed patients with multiple myeloma (MM) who are not candidates for stem-cell transplant (SCT). This study quantified the extent to which patients would accept short-term risks following MM therapy for the potential benefit of a longer, treatment-free interval. Methods: Adult patients with MM from the Duke Cancer Institute Tumor Registry were invited to complete an online discrete-choice experiment (DCE) survey in which they were to suppose they had a friend (same age and gender) recently diagnosed with MM who is not a candidate for SCT. Respondents chose the better post-induction therapy treatment for their friend from pairs of experimentally designed hypothetical treatments. In each question, treatments varied in terms of time until relapse (3, 5, or 10 years), impact of treatment-related side effects on daily activities (no, minor, or moderate limits), treatment-related mortality (0% to 10% in the first 3 months), and risk of reversible, short-term side effects (described as neurotoxicity or cytokine release syndrome) resulting in a 10-day hospitalization (0% to 20% risk in the first 3 months). DCE data were analyzed with a random-parameters logit model to estimate preference weights (PW) which were used to estimate the maximum level of short-term mortality risk acceptable to patients for longer time to relapse and less impact on daily activities. Results: The survey was completed by 176 patients (mean age; 66 yrs; 51% female, 22% Black) of whom 80% had a transplant and 31% had at least one relapse. Responses to the DCE were logically ordered (patients preferred lower levels of risks and better levels of benefit). For the levels specified, avoiding treatment-related mortality was most important (PW: 3.69), followed by gaining relapse-free years (PW: 3.32), and reducing impact on daily activities (PW: 2.04). Risk of reversible, short-term side effects was relatively least important (PW: 0.58). All else equal, patients would accept 5.7% mortality (95% CI: 3.8-7.2) for a 2-year gain in time to relapse (from 3 to 5 yrs) or 6.0% mortality risk (95% CI: 4.5-7.3) to avoid side effects that moderately limit their daily activities. Conclusions: Patients considering initial treatment following induction therapy for MM assigned least importance to reversible, short-term side effects that may be associated with CAR-T. Specified levels of treatment mortality were acceptable in exchange for longer relapse free intervals and fewer impacts on daily activities.[Table: see text]

Food for thought: Assessing the consumer welfare impacts of deploying irreversible, landscape-scale biotechnologies

Genetically engineered insects have gained attention as regionally deployed pest control technologies, with substantial applications in agriculture for combatting intractable crop pests and diseases. One potential tool is a ‘gene drive’, using CRISPR-based gene editing. In gene drive, preferentially inherited, engineered traits are spread throughout a geographic area to reduce pest populations or inhibit disease transmission, while also potentially reducing pesticide use and crop prices. But the self-perpetuating nature of gene drives presents a consequence, in that consumers could eventually be limited to only host crops grown in the presence of these genetically engineered insects. In this study, we analyze potential consumer welfare impacts of these technologies using discrete choice experiment data from a representative sample of U.S. adults, examining preferences regarding gene drive use to control spotted wing drosophila in blueberries and Asian citrus psyllid in orange juice (OJ) production. We find smaller average discounts for gene drives versus increased conventional pesticide use or genetically modified crops. Only 27% and 25% of blueberry and OJ consumers, respectively, are estimated to derive disutility from gene drives. However, gene drive disutility for these consumers is so large that elimination of non-drive options from their choice sets results in negative (blueberries) or neutral (OJ) effects to aggregate consumer welfare when weighed against gains to other consumers from reduced prices. Positive welfare effects are recovered by retaining availability of non-gene-drive products. We argue that this type of analysis will be increasingly important as landscape-level biotechnologies are deployed to address challenges to agricultural sustainability.

Valuing the Dental Caries Utility Index in Australia.

The Dental Caries Utility Index (DCUI) is a new oral health-specific health state classification system for adolescents, consisting of 5 domains: pain/discomfort, difficulty eating food/drinking, worried, ability to participate in activities, and appearance. Each domain has 4 response levels. This study aims to generate an Australian-specific utility algorithm for the DCUI. An online survey was conducted using a representative sample of the adult Australian general population. The discrete choice experiment (DCE) was used to elicit the preferences on 5 domains. Then, the latent utilities were anchored onto the full health-dead scale using the visual analogue scale (VAS). DCE data were modeled using conditional logit, and 2 anchoring procedures were considered: anchor based on the worst health state and a mapping approach. The optimal anchoring procedure was selected based on the model parsimony and the mean absolute error (MAE). A total of 995 adults from the Australian general population completed the survey. The conditional logit estimates on 5 dimensions and levels were monotonic and statistically significant, except for the second level of the "worried" and "appearance" domains. The mapping approach was selected based on a smaller MAE between the 2 anchoring procedures. The Australian-specific tariff of DCUI ranges from 0.1681 to 1. This study developed a utility algorithm for the DCUI. This value set will facilitate utility value calculations from the participants' responses for DCUI in economic evaluations of dental caries interventions targeted for adolescents. Preference-based quality-of-life measures (PBMs), which consist of a health state classification system and a set of utility values (a scoring algorithm), are used to generate utility weights for economic evaluations.This study is the first to develop an Australian utility value set for the Dental Caries Utility Index (DCUI), a new oral health-specific classification system for adolescents.The availability of a utility value set will enable using DCUI in economic evaluations of oral health interventions targeted for adolescents and may ultimately lead to more effective and efficient planning of oral health care services.

The EQ-5D-3L Valuation Study in Pakistan.

To utilize EQ-5D in economic evaluations, a societal-based value set is needed. To date, no value sets exist for any EQ-5D instrument in Pakistan. Previous EQ-5D studies conducted in Pakistan 'borrowed' health preferences developed in other countries. However, for a value set to be valid for Pakistani population, it should represent the preferences of the Pakistani population, and culture and living standards of Pakistan. The aim of this study was to derive a Pakistani EQ-5D-3L value set. A moderately representative sample aged 18 years and over was recruited from the Pakistani general population. A multi-stage stratified quota method with respect to ethnicity, gender, age and religion was utilized. Two elicitation techniques, the composite time trade-off (cTTO) and discrete choice experiments (DCE) were applied. Interviews were undertaken by trained interviewers using computer-assisted face-to-face interviews with the EuroQol Portable Valuation Technology (EQ-PVT) platform. To estimate the value set, a hybrid regression model combining cTTO and DCE data was used. A total of 289 respondents who completed the interviews were included for the analysis. The hybrid model correcting for heteroskedasticity without a constant was selected as the final model for the value set. It is shown that being unable to do usual activities (level 3) was assigned the largest weight, followed by mobility level 3, self-care level 3, pain/discomfort level 3 and anxiety/depression level 3. The worst health state was assigned the value - 0.171 in the final model. A Pakistani country-specific EQ-5D-3L value set is now available. The availability of this value set may help promote and facilitate health economic evaluations and health-related quality-of-life (HRQoL) research in Pakistan.

Eliciting a value set for the Swedish Capability-Adjusted Life Years instrument (CALY-SWE)

PurposeOur aim was to elicit a value set for Capability-Adjusted Life Years Sweden (CALY-SWE); a capability-grounded quality of life instrument intended for use in economic evaluations of social interventions with broad consequences beyond health.MethodsBuilding on methods commonly used in the quality-adjusted life years EQ-5D context, we collected time-trade off (TTO) and discrete choice experiment (DCE) data through an online survey from a general population sample of 1697 Swedish participants. We assessed data quality using a score based on the severity of inconsistencies. For generating the value set, we compared different model features, including hybrid modeling of DCE and TTO versus TTO data only, censoring of TTO answers, varying intercept, and accommodating for heteroskedasticity. We also assessed the models’ DCE logit fidelity to measure agreement with potentially less-biased DCE data. To anchor the best capability state to 1 on the 0 to 1 scale, we included a multiplicative scaling factor.ResultsWe excluded 20% of the TTO answers of participants with the largest inconsistencies to improve data quality. A hybrid model with an anchor scale and censoring was chosen to generate the value set; models with heteroskedasticity considerations or individually varying intercepts did not offer substantial improvement. The lowest capability weight was 0.114. Health, social relations, and finance and housing attributes contributed the largest capability gains, followed by occupation, security, and political and civil rights.ConclusionWe elicited a value set for CALY-SWE for use in economic evaluations of interventions with broad social consequences.

Abstract P335: Patient Preferences For Renal Denervation In Uncontrolled Hypertension: The RADIANCE PREFER Study

Objective: Blood pressure control is a challenge for patients for reasons including adherence, medication side effects, poor access to healthcare, and inconvenience of long-term treatment. Renal denervation is a treatment option that lowers blood pressure in combination with lifestyle modifications and medications, but it requires a minimally invasive procedure. This study assessed how patients make choices between treatments, and quantified their willingness to undergo renal denervation. Methods: An online discrete choice experiment (DCE) was completed by US adults with uncontrolled hypertension despite being prescribed ≥1 medication. In 10 DCE tasks, participants chose between two hypothetical treatments defined by the 10-year cardiovascular (CV) risk, current treatments (procedure/number of pills per day), durability/need for future treatments (additional procedure or pills), and risks of mild-to-moderate and serious adverse events. The attributes were developed through a targeted literature review, 10 qualitative interviews, and FDA feedback, and were refined through 5 cognitive pilot interviews. DCE data were analyzed using mixed logit models which were used to simulate treatment uptake in different scenarios. Results: Participants (n=258) were 62% female, 40% non-white, and from multiple regions of the US, with a majority from the South (63%). Mean (SD) age was 53 (12) years and BMI was 33 (10) kg/m 2 . All participants were currently taking ≥1 pill/day. Participants put the most weight on CV risk when deciding between treatment options. Given the same number of pills, 42% would choose an interventional treatment if it reduced their 10-year CV risk by 5% more than medication alone. In addition, 42% of patients would prefer a one-time invasive procedure versus taking an additional pill if the procedure had the same effect on CV risk as medication alone. Conclusions: A substantial number of patients taking medication for hypertension would be willing to undergo renal denervation to reduce their CV risk or to avoid an increase in their pill burden.

Reforming the registration policy of female sex workers in Senegal? Evidence from a discrete choice experiment.

Evidence suggests that treating sexually transmitted infections (STIs) amongst female sex workers (FSWs) is a cost-effective strategy to reduce the spread of HIV/AIDS. Senegal is the only African country where sex work is regulated by a public health policy which aims to monitor and routinely treat STIs. The law requires FSWs to be at least 21 years old, register with a health centre and the police, carry an up-to-date registration booklet, attend monthly health check-ups, and test negative for STIs. Despite health and legal benefits of registration, 80% of FSWs in Senegal are not registered. Hence, the potential health benefits of the policy have not materialised. To understand why FSWs do not want to register and to define policy changes that would increase the registration rate of FSWs in Senegal, we designed and implemented a discrete choice experiment (DCE) completed by 241 registered and 273 non-registered FSWs. Participants made choices between a series of hypothetical but realistic registration policy changes. Conditional logit models were used to analyse the DCE data. The results highlighted that confidentiality at the health facility was an important element, registered and non-registered FWs were respectively 26.0 percentage points (pp) and 22.1 pp more likely to prefer a policy that guaranteed confidentiality at the health centre. Similarly, both groups preferred a policy where their health record was only held at the health centre and not with the police. Several interventions to increase FSW registration rate and improve their wellbeing may be implemented without modifying the law. For example, the introduction of psychosocial support in the registration policy package, replacing the registration booklet by a QR code, the use of electronic medical files and the integration of FSWs routine visits with maternal health appointments to increase confidentiality have the potential to encourage registration of FSWs.

Exploring the Preferences of the Australian Public for Antibiotic Treatments: A Discrete Choice Experiment.

Identify Australian public preferences for antibiotic treatments in the context of antibiotic stewardship. A discrete choice experiment (DCE) was conducted in Australia to investigate the importance of seven attributes associated with antibiotic treatments and related stewardship practices: contribution to antimicrobial resistance (AMR), treatment duration, side effects, days needed to recover, days before taking antibiotics, treatment failure and out-of-pocket costs. The DCE data were analysed using conditional logit, mixed logit and latent class conditional logit models. The relative importance of each attribute was calculated. A total of 1882 respondents completed the survey; the main study sample consist of 1658 respondents (mean age 48 years) who passed quality checks. All seven attributes significantly influenced respondents' preferences for antibiotic treatments. Based on the designed attribute levels in the DCE, on average, out-of-pocket costs (32.8%) and contribution to antibiotic resistance (30.3%) were the most important attributes, followed by side effects (12.9%). Days before starting medication was least important (3.9%). Three latent classes were identified. Class 1 (including respondents who were more likely to be older and more health literate; 24.5%) gave contribution to antibiotic resistance greater importance in treatment preferences. Class 2 (including respondents more likely to report poorer health; 25.2%) gave out-of-pocket costs greater importance. The remaining (50.4%), who were generally healthier, perceived side effects as the most important attribute. Despite concerted public awareness raising campaigns, our results suggest that several factors may influence the preferences of Australians when considering antibiotic use. However, for those more likely to be aware of the need to preserve antibiotics, out-of-pocket costs and limiting the contribution to antibiotic resistance are the dominant influence. Delays in starting treatment were not important for any latent class, suggesting public tolerance for this measure. These results could help inform strategies to promote prudent antibiotic stewardship.

Understanding Treatment Preferences Among People Living with HIV in Australia: A Discrete Choice Experiment.

To better understand what is most important to people living with human immunodeficiency virus (PLWH) when choosing their treatment. We assessed how PLWH trade off the potential risks and benefits of oral and long acting injectable (LAI) treatments. Firstly, in-depth interviews were conducted with 11 PLWH to develop a holistic understanding of experiences and determine attributes that contribute to treatment decision-making. Secondly, a discrete choice experiment (DCE) was used to understand the treatment preferences for PLWH with n = 99 PLWH aged 18 years or over with a diagnosis of human immunodeficiency virus (HIV) and who were currently using anti-retroviral therapy (ART). Study participants were presented with 12 scenarios and asked to select their preferred treatment among two hypothetical injectable treatment alternatives, "injection 1" and "injection 2" and their current oral ART treatment. The DCE data were modelled using a latent class model (LCM). The model revealed significant heterogeneity in preferences for treatment attributes among study participants. Two segments/classes of PLWH were identified. The first segment expressed a strong preference for their current oral treatment; the second segment showed strong preference for the injection treatment and for it to be administered in a GP clinic. Overall, out-of-pocket cost was the most important attribute for participants. One-third of PLWH were willing to switch to an LAI. Not all PLWH valued the same treatment attributes equally. Overall, out-of-pocket costs for treatments were considered by respondents as the most determining factor in making treatment choices. Results have important implications for healthcare policy and will serve to better inform patients and stakeholders involved in the treatment decision-making process about the treatment preferences of PLWH. Clinicians are encouraged to consider shared decision-making to establish the treatment course that best aligns with PLWH's treatment goals.

Whose Time Trade-Off Should Be Used? Anchoring Discrete Choice Experiment Latent Utilities in Health State Valuation

ObjectivesTo compare anchored discrete choice experiment (DCE) utility values using own versus others’ time trade-off (TTO) responses in the valuation of SF-6Dv2. MethodsA representative sample of the general population was recruited in China. Through face-to-face interviews, both DCE and TTO data were collected from a randomly selected half of the respondents (own TTO sample), whereas only TTO data were collected from the other half (others’ TTO sample). Conditional logit model was used to estimate DCE latent utilities. Three anchoring methods, including using the observed and the modeled TTO values for the worst state, and mapping DCE values onto TTO, were used to scale the latent utilities to health utilities. Prediction accuracy was assessed using intraclass correlation coefficient, mean absolute difference, and root mean squared difference compared with the mean observed TTO values between the anchoring results using the own versus others’ TTO data. ResultsDemographic characteristics were comparable between the own TTO sample (n = 252) and the others’ TTO sample (n = 251). The mean (SD) observed TTO value for the worst state was −0.259 (0.591) for the own TTO sample and −0.236 (0.616) for the others’ TTO sample. Anchoring DCE using own TTOs consistently showed a better prediction accuracy than using others’ TTOs across the 3 anchoring methods in terms of the intraclass correlation coefficient (0.835-0.873 vs 0.771-0.804), mean absolute difference (0.127-0.181 vs 0.146-0.203), and root mean squared difference (0.164-0.237 vs 0.192-0.270). ConclusionWhen anchoring DCE-derived latent utilities onto the health utility scale, respondents’ own TTO data would be preferred to TTO data obtained from a different sample.