Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report.

OBJECTIVES: Discrete choice experiments (DCEs) are increasingly used to elicit preferences for health and healthcare. Although many applications assume preferences are homogenous, there is a growing portfolio of methods to understand both explained (because of observed factors) and unexplained (latent) heterogeneity. Nevertheless, the selection of analytical methods can be challenging and little guidance is available. This study aimed to determine the state of practice in accounting for preference heterogeneity in the analysis of health-related DCEs, including the views and experiences of health preference researchers and an overview of the tools that are commonly used to elicit preferences. METHODS: An online survey was developed and distributed among health preference researchers and nonhealth method experts, and a systematic review of the DCE literature in health was undertaken to explore the analytical methods used and summarize trends. RESULTS: Most respondents (n = 59 of 70, 84%) agreed that accounting for preference heterogeneity provides a richer understanding of the data. Nevertheless, there was disagreement on how to account for heterogeneity; most (n = 60, 85%) stated that more guidance was needed. Notably, the majority (n = 41, 58%) raised concern about the increasing complexity of analytical methods. Of the 342 studies included in the review, half (n = 175, 51%) used a mixed logit with continuous distributions for the parameters, and a third (n = 110, 32%) used a latent class model. CONCLUSIONS: Although there is agreement about the importance of accounting for preference heterogeneity, there are noticeable disagreements and concerns about best practices, resulting in a clear need for further analytical guidance.

Who Would Pay Higher Taxes for Better Mental Health? Results of a Large-Sample National Choice Experiment.

Policy Points  Public funding for mental health programs must compete with other funding priorities in limited state budgets.  Valuing state-funded mental health programs in a policy-relevant context requires consideration of how much benefit from other programs the public is willing to forgo to increase mental health program benefits and how much the public is willing to be taxed for such program benefits.  Taxpayer resistance to increased taxes to pay for publicly funded mental health programs and perceived benefits of such programs vary with state population size.  In all states, taxpayers seem to support increased public funding for mental health programs such as state Medicaid services, suggesting such programs are underfunded from the perspective of the average taxpayer. CONTEXT: The direct and indirect impacts of serious mental illness (SMI) on health care systems and communities represents a significant burden. However, the value that community members place on alleviating this burden is not known, and SMI treatment must compete with a long list of other publicly funded priorities. This study defines the value of public mental health interventions as what the public would accept, either in the form of higher taxes or in reductions in nonhealth programs, in return for increases in the number of mental health program beneficiaries. METHODS: We developed and fielded a best-practice discrete-choice experiment survey to quantify respondents' willingness to be taxed for increased spending among several competing programs, including a program for treating severe mental health conditions. A realistic decision frame was used to elicit respondents' willingness to support expanded state budgets for mental health programs if that expansion required either cuts in the competing publicly financed programs or tax increases. The survey was administered to a general population national sample of 10,000 respondents. FINDINGS: Nearly half the respondents in our sample either chose "no budget increase" for all budget scenarios or had preferences that were too disordered to estimate trade-off values. Including zero values for those respondents, we found that the mean (median) amount that all respondents were willing to be taxed annually for public mental health programs ranged between $156 ($99) per year for large-population states and $343 ($181) per year for small-population states. Respondents would accept reductions of between 1.6 and 3.4 beneficiaries in other programs in return for 1 additional mental health program beneficiary. CONCLUSIONS: Our results are consistent with findings that a substantial portion of the US public is unwilling to pay higher taxes. Nevertheless, even including the substantial number of respondents who opposed any tax increase, the willingness of both the mean and median respondent to be taxed for mental health program expansions implies that programs providing mental health services such as state Medicaid are underfunded.

The preferences of women with ovarian cancer for oral versus intravenous recurrence regimens.

OBJECTIVE: To assess preferences of women with ovarian cancer regarding features of available anti-cancer regimens for platinum-resistant, biomarker-positive disease, with an emphasis on oral PARP inhibitor and standard intravenous (IV) chemotherapy regimens. METHODS: A discrete-choice-experiment preferences survey was designed, tested, and administered to women with ovarian cancer, with 11 pairs of treatment profiles defined using seven attributes (levels/ranges): regimen (oral daily, IV weekly, IV monthly); probability of progression-free (PFS) at 6 months (40%-60%); probability of PFS at 2 years (10%-20%); nausea (none, moderate); peripheral neuropathy (none, mild, moderate); memory problems (none, mild); and total out-of-pocket cost ($0 to $10,000). RESULTS: Of 123 participants, 38% had experienced recurrence, 25% were currently receiving chemotherapy, and 18% were currently taking a PARP inhibitor. Given attributes and levels, the relative importance weights (sum 100) were: 2-year PFS, 28; cost, 27; 6-month PFS, 19; neuropathy,14; memory problems, nausea, and regimen, all ≤5. To accept moderate neuropathy, participants required a 49% (versus 40%) chance of PFS at 6 months or 14% (versus 10%) chance at 2 years. Given a 3-way choice where PFS and cost were equal, 49% preferred a monthly IV regimen causing mild memory problems, 47% preferred an oral regimen causing moderate nausea, and 4% preferred a weekly IV regimen causing mild memory and mild neuropathy. CONCLUSIONS: These findings challenge the assumption that oral anti-cancer therapies are universally preferred by patients and demonstrate that there is no "one size fits all" regimen that is preferable to women with ovarian cancer when considering recurrence treatment regimens.

Quantifying Value of Hope.

BACKGROUND: 'Hope' is a construct in patient-centered value frameworks, but few studies have attempted to measure the value of hope separately from treatment-related gains in quality of life and survival to support its application in economic evaluation. OBJECTIVE: To generate quantitative information on the "value of hope". METHODS: We designed a discrete-choice experiment in which treatment alternatives varied the probability of achieving 10-year survival, expected survival as the weighted sum of short-term and long-term survival, health status, and out-of-pocket cost. Two-hundred patients with cancer or history of cancer recruited by Cancer Support Community each completed 10 choice questions. We used mixed-logit and latent-class models to analyze the choice data. RESULTS: Relative to fixed survival periods of two, three or five years with 0% chance of 10-year survival, participants positively valued treatments with 5% and 10% chances of 10-year survival. However, participants negatively valued a 20% chance of 10-year survival that required an offsetting 80% chance of shorter survival. This finding was particularly strong when expected survival was two years. Compared to a 0% chance, dollar-equivalent values of 5% and 10% chances of long-term survival were $5,975 and $12,421, respectively, independent of health status or expected survival. The corresponding value for 20% versus 0% chance of long-term survival was negative. Latent-class analysis revealed 4 groups with distinct preference patterns. CONCLUSIONS: Our findings affirm positive value for hope independent of expected survival and health status. However, this finding does not universally hold in all situations nor across all groups.

Surgical treatment for recurrent shoulder instability: factors influencing surgeon decision making.

BACKGROUND: The optimal surgical approach for recurrent anterior shoulder instability remains controversial, particularly in the face of glenoid and/or humeral bone loss. The purpose of this study was to use a contingent-behavior questionnaire (CBQ) to determine which factors drive surgeons to perform bony procedures over soft tissue procedures to address recurrent anterior shoulder instability. METHODS: A CBQ survey presented each respondent with 32 clinical vignettes of recurrent shoulder instability that contained 8 patient factors. The factors included (1) age, (2) sex, (3) hand dominance, (4) number of previous dislocations, (5) activity level, (6) generalized laxity, (7) glenoid bone loss, and (8) glenoid track. The survey was distributed to fellowship-trained surgeons in shoulder/elbow or sports medicine. Respondents were asked to recommend either a soft tissue or bone-based procedure, then specifically recommend a type of procedure. Responses were analyzed using a multinomial-logit regression model that quantified the relative importance of the patient characteristics in choosing bony procedures. RESULTS: Seventy orthopedic surgeons completed the survey, 33 were shoulder/elbow fellowship trained and 37 were sports medicine fellowship trained; 52% were in clinical practice ≥10 years and 48% <10 years; and 95% reported that the shoulder surgery made up at least 25% of their practice. There were 53% from private practice, 33% from academic medicine, and 14% in government settings. Amount of glenoid bone loss was the single most important factor driving surgeons to perform bony procedures over soft tissue procedures, followed by the patient age (19-25 years) and the patient activity level. The number of prior dislocations and glenoid track status did not have a strong influence on respondents' decision making. Twenty-one percent glenoid bone loss was the threshold of bone loss that influenced decision toward a bony procedure. If surgeons performed 10 or more open procedures per year, they were more likely to perform a bony procedure. CONCLUSION: The factors that drove surgeons to choose bony procedures were the amount of glenoid bone loss with the threshold at 21%, patient age, and their activity demands. Surprisingly, glenoid track status and the number of previous dislocations did not strongly influence surgical treatment decisions. Ten open shoulder procedures a year seems to provide a level of comfort to recommend bony treatment for shoulder instability.

Patient preferences for maintenance PARP inhibitor therapy in ovarian cancer treatment.

OBJECTIVE: To measure preferences of women with ovarian cancer regarding risks, side effects, costs and benefits afforded by maintenance therapy (MT) with a poly ADP ribose polymerase (PARP) inhibitor. METHODS: A discrete-choice experiment elicited preferences of women with ovarian cancer regarding 6 attributes (levels in parentheses) relevant to decisions for MT versus treatment break: (1) overall survival (OS; 36, 38, 42 months); (2) progression-free survival (PFS; 15, 17, 21 months); (3) nausea (none, mild, moderate); (4) fatigue (none, mild, moderate); (5) probability of death from myelodysplastic syndrome/acute myelogenous leukemia (MDS/AML; 0% to 10%); (6) monthly out-of-pocket cost ($0 to $1000). Participants chose between 2 variable MT scenarios and a static scenario representing treatment break, with multiple iterations. Random-parameters logit regression was applied to model choices as a function of attribute levels. RESULTS: 95 eligible participants completed the survey; mean age was 62, 48% had recurrence, and 17% were ever-PARP inhibitor users. Participants valued OS (average importance weight 24.5 out of 100) and monthly costs (24.6) most highly, followed by risk of death from MDS/AML (17.9), nausea (14.7), PFS (10.5) and fatigue (7.8). Participants would accept 5% risk of MDS/AML if treatment provided 2.2 months additional OS or 4.8 months PFS. Participants would require gains of 2.6 months PFS to accept mild treatment-related fatigue and 4.4 months to accept mild nausea. CONCLUSIONS: When considering MT, women with ovarian cancer are most motivated by gains in OS. Women expect at least 3-4 months of PFS benefit to bear mild side effects of treatment.

Willingness to Accept Trade-Offs Among COVID-19 Cases, Social-Distancing Restrictions, and Economic Impact: A Nationwide US Study.

OBJECTIVE: To conduct a discrete-choice experiment to quantify Americans' acceptance of severe acute respiratory syndrome coronavirus 2 infection risks for earlier lifting of social-distancing restrictions and diminishing the pandemic's economic impact. METHODS: We designed a discrete-choice experiment to administer 10 choice questions to each respondent representing experimentally controlled pairs of scenarios defined by when nonessential businesses could reopen (May, July, or October 2020), cumulative percentage of Americans contracting coronavirus disease 2019 (COVID-19) through 2020 (2% to 20%), time for economic recovery (2 to 5 years), and the percentage of US households falling below the poverty threshold (16% to 25%). Respondents were recruited by SurveyHealthcareGlobus. RESULTS: A total of 5953 adults across all 50 states completed the survey between May 8 and 20, 2020. Latent-class analysis supported a 4-class model. The largest class (36%) represented COVID-19 risk-minimizers, reluctant to accept any increases in COVID-19 risks. About 26% were waiters, strongly preferring to delay reopening nonessential businesses, independent of COVID-19 risk levels. Another 25% represented recovery-supporters, primarily concerned about time required for economic recovery. This group would accept COVID-19 risks as high as 16% (95% CI: 13%-19%) to shorten economic recovery from 3 to 2 years. The final openers class prioritized lifting social distancing restrictions, accepting of COVID-19 risks greater than 20% to open in May rather than July or October. Political affiliation, race, household income, and employment status were all associated with class membership (P<.01). CONCLUSION: Americans have diverse preferences pertaining to social-distancing restrictions, infection risks, and economic outcomes. These findings can assist elected and public-health officials in making difficult policy decisions related to the pandemic.

Corrigendum: What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

This corrects the article DOI: 10.1038/gim.2016.61.

Estimating Preferences for Complex Health Technologies: Lessons Learned and Implications for Personalized Medicine.

We examine key study design challenges of using stated-preference methods to estimate the value of whole-genome sequencing (WGS) as a specific example of genomic testing. Assessing the value of WGS is complex because WGS provides multiple findings, some of which can be incidental in nature and unrelated to the specific health concerns that motivated the test. In addition, WGS results can include actionable findings (variants considered to be clinically useful and can be acted on), findings for which evidence for best clinical action is not available (variants considered clinically valid but do not meet as high of a standard for clinical usefulness), and findings of unknown significance. We consider three key challenges encountered in designing our national study on the value of WGS-layers of uncertainty, potential downstream consequences with endogenous aspects, and both positive and negative utility associated with testing information-and potential solutions as strategies to address these challenges. We conceptualized the decision to acquire WGS information as a series of sequential choices that are resolved separately. To determine the value of WGS information at the initial decision to undergo WGS, we used contingent valuation questions, and to elicit respondent preferences for reducing risks of health problems and the consequences of taking the steps to reduce these risks, we used a discrete-choice experiment. We conclude by considering the implications for evaluating the value of other complex health technologies that involve multiple forms of uncertainty.

Quantifying the importance of inhaler attributes corresponding to items in the patient satisfaction and preference questionnaire in patients using Combivent Respimat.

BACKGROUND: Physicians consider ease of use, satisfaction, and preferences when prescribing an inhaler device. These factors may impact appropriate usage and compliance. METHODS: The objectives were to quantify the relative importance of inhaler attributes in patients currently using Combivent Respimat by eliciting preferences for performance and convenience attributes assessed by items in the Patient Satisfaction and Preference Questionnaire (PASAPQ). Using a pharmacy database, 19,964 adults in the United States who filled ≥2 Combivent Respimat prescriptions were identified. Of those, 8150 patients were randomly selected to receive invitation letters. The online cross-sectional survey included the PASAPQ and best-worst scaling (BWS) questions. The PASAPQ measures satisfaction with medication attributes across two domains: performance and convenience. BWS questions asked participants to select the most and least important device attributes. A descriptive statistics analysis of the PASAPQ and a random-parameters logit model of BWS responses were conducted. RESULTS: The survey was completed by 503 participants. Most were female (57.3%), white (88.5%), and 51-70 years old (67.6%). Approximately 47% reported a chronic obstructive pulmonary disease diagnosis, 21.9% asthma, 8.2% other lung disease, and 23.1% more than one lung disease. PASAPQ scores indicated that the majority were satisfied or very satisfied; up to 20% reported being dissatisfied with Combivent Respimat. The three most important inhaler attributes were Feeling that your medicine gets into your lungs, Inhaler works reliably, and Inhaler makes inhaling your medicine easy. The most important attributes corresponded to six of seven items in the PASAPQ performance domain. CONCLUSIONS: Most participants reported satisfaction with Combivent Respimat. Performance attributes were more important than convenience attributes.

What are people willing to pay for whole-genome sequencing information, and who decides what they receive?

PURPOSE: Whole-genome sequencing (WGS) can be used as a powerful diagnostic tool as well as for screening, but it may lead to anxiety, unnecessary testing, and overtreatment. Current guidelines suggest reporting clinically actionable secondary findings when diagnostic testing is performed. We examined preferences for receiving WGS results. METHODS: A US nationally representative survey (n = 410 adults) was used to rank preferences for who decides (an expert panel, your doctor, you) which WGS results are reported. We estimated the value of information about variants with varying levels of clinical usefulness by using willingness to pay contingent valuation questions. RESULTS: The results were as follows: 43% preferred to decide themselves what information is included in the WGS report. 38% (95% confidence interval (CI): 33-43%) would not pay for actionable variants, and 3% (95% CI: 1-5%) would pay more than $1,000. 55% (95% CI: 50-60%) would not pay for variants for which medical treatment is currently unclear, and 7% (95% CI: 5-9%) would pay more than $400. CONCLUSION: Most people prefer to decide what WGS results are reported. Despite valuing actionable information more, some respondents perceive that genetic information could negatively impact them. Preference heterogeneity for WGS information should be considered in the development of policies, particularly to integrate patient preferences with personalized medicine and shared decision making.Genet Med 18 12, 1295-1302.

Neoadjuvant Systemic Therapy for Breast Cancer: Factors Influencing Surgeons' Referrals.

BACKGROUND: This study aimed to assess the influence of disease- and patient-related factors on surgeons' decisions to refer patients with early-stage breast cancer (EBC) for neoadjuvant systemic therapy (NST). METHODS: An online survey of United States surgeons evaluated the influence of selected disease- and patient-related factors on surgeons' decisions, rated their influence (individually and in combination), and provided a relative ranking of jointly considered factors using best-worst scaling. RESULTS: The participants in this study were 100 licensed surgeons. The surgeons referred approximately 25 % of EBC patients for NST to improve surgical management. Approximately 75 % of the surgeons agreed that NST is important for EBC, if only to improve surgical management. More than half were "very likely" to refer EBC patients for NST based on anatomicopathologic factors. Less than 50 % were "very likely" to do so when considering tumor phenotype factors. Tumor size and lymph node status were ranked highest in hypothetical patient scenarios. Regarding combinations of factors, the importance of any single factor varied according to the combinations presented. Less than half of the respondents were "very familiar," and half were "somewhat familiar" with NST guidelines for breast cancer. More than half of the respondents were unaware that findings have shown achievement of pathologic complete response (pCR) after NST to be associated with improved survival. CONCLUSIONS: Surgeons' decision to refer for NST is strongly driven by surgical management goals. Anatomicopathologic factors are more influential than tumor phenotype. However, no single disease or patient factor consistently drives the decision to refer for NST. Surgeons' awareness of the association between pCR achievement and longer survival could be improved.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results.

Physicians' preferences for bone metastases drug therapy in the United States.

OBJECTIVE: Several characteristics of bone-targeted agents are considered when making treatment decisions. This study evaluated physicians' therapy preferences for preventing skeletal-related events (SREs) in patients with bone metastases secondary to solid tumors. METHODS: A Web-enabled, discrete-choice experiment online survey was conducted among physicians who treated patients with bone metastases and solid tumors in the United States. Respondents chose between pairs of hypothetical medications defined by combinations of six attributes at varying levels for two hypothetical patients. Preference weights for attribute levels were estimated using a random-parameters logit model. RESULTS: In total, 200 physicians completed the survey. Their mean age was 52 years, 57% were in practice for more than 15 years, 37% were oncologists, and 65% treated 10 or fewer patients with bone metastases weekly. Out-of-pocket cost to patients was the most important attribute overall. Among clinical outcomes, time to first SRE and risk of renal impairment were the most important attributes. Statistically significant preferences were observed for all attribute levels for time to first SRE, risk of renal impairment, and mode of administration. Predicted choice probability analysis showed that physicians preferred a hypothetical medication with attributes similar to those of denosumab over one with attributes similar to those of zoledronic acid. CONCLUSIONS: Physicians indicated that clinical attributes are important when considering bone-targeting therapy for bone metastases, but consistent with the current health care landscape, patient out-of-pocket cost was the most important. With health care costs being increasingly shifted to patients, physicians require accurate information about co-pays and assistance programs to avoid patients receiving less costly, yet potentially inferior, treatment.

Incorporating patient-preference evidence into regulatory decision making.

BACKGROUND: Patients have a unique role in deciding what treatments should be available for them and regulatory agencies should take their preferences into account when making treatment approval decisions. This is the first study designed to obtain quantitative patient-preference evidence to inform regulatory approval decisions by the Food and Drug Administration Center for Devices and Radiological Health. METHODS: Five-hundred and forty United States adults with body mass index (BMI) ≥ 30 kg/m(2) evaluated tradeoffs among effectiveness, safety, and other attributes of weight-loss devices in a scientific survey. Discrete-choice experiments were used to quantify the importance of safety, effectiveness, and other attributes of weight-loss devices to obese respondents. A tool based on these measures is being used to inform benefit-risk assessments for premarket approval of medical devices. RESULTS: Respondent choices yielded preference scores indicating their relative value for attributes of weight-loss devices in this study. We developed a tool to estimate the minimum weight loss acceptable by a patient to receive a device with a given risk profile and the maximum mortality risk tolerable in exchange for a given weight loss. For example, to accept a device with 0.01 % mortality risk, a risk tolerant patient will require about 10 % total body weight loss lasting 5 years. CONCLUSIONS: Patient preference evidence was used make regulatory decision making more patient-centered. In addition, we captured the heterogeneity of patient preferences allowing market approval of effective devices for risk tolerant patients. CDRH is using the study tool to define minimum clinical effectiveness to evaluate new weight-loss devices. The methods presented can be applied to a wide variety of medical products. This study supports the ongoing development of a guidance document on incorporating patient preferences into medical-device premarket approval decisions.

Patient preferences for treatments to delay bone metastases.

BACKGROUND: Most patients with advanced prostate cancer (PCa) develop bone metastases (BM) and present with bone complications like fracture. Bone-targeted agents that prevent metastasis-induced bone complications can cause adverse events. Understanding how patients view treatment options may optimize care. This study aimed to quantify how PCa patients value a hypothetical treatment that delays BM but can cause osteonecrosis of the jaw (ONJ). The study also assessed the value patients place on avoiding metastasis-induced bone complications versus increased survival. METHODS: PCa patients from the United Kingdom (n = 201) and Sweden (n = 200) on androgen-deprivation therapy or hormone therapy for ≥ 3 years completed a 10-question discrete-choice-experiment survey examining whether patients would accept a BM-delaying treatment. Two time-tradeoff questions assessed patients' willingness to tradeoff between survival and bone complications. Percentages of patients choosing treatment were summarized by levels of treatment efficacy and ONJ risk. Odds ratios from a logit model were used to evaluate how patient and medication characteristics affected treatment choice. Proportions of patients choosing each tradeoff scenario were calculated. RESULTS: A majority of patients accepted treatment at the lowest benefit level (5-month BM delay) and highest risk level (9% ONJ risk). PCa symptoms and prior treatment affected patient preferences. Nearly 80% of patients would tradeoff at least 3 months of survival to avoid bone complications. CONCLUSIONS: PCa patients in the U.K and Sweden may value a medication that delays BM, despite the risk of ONJ. Furthermore, patients were willing to tradeoff up to 5 months of survival for prevention of bone complications.

Valuations of genetic test information for treatable conditions: the case of colorectal cancer screening.

BACKGROUND: The value of the information that genetic testing services provide can be questioned for insurance-based health systems. The results of genetic tests oftentimes may not lead to well-defined clinical interventions; however, Lynch syndrome, a genetic mutation for which carriers are at an increased risk for colorectal cancer, can be identified through genetic testing, and meaningful health interventions are available via increased colonoscopic surveillance. Valuations of test information for such conditions ought to account for the full impact of interventions and contingent outcomes. OBJECTIVES: To conduct a discrete-choice experiment to elicit individuals' preferences for genetic test information. METHODS: A Web-enabled discrete-choice experiment survey was administered to a representative sample of US residents aged 50 years and older. In addition to specifying expenditures on colonoscopies, respondents were asked to make a series of nine selections between two hypothetical genetic tests or a no-test option under the premise that a relative had Lynch syndrome. The hypothetical genetic tests were defined by the probability of developing colorectal cancer, the probability of a false-negative test result, privacy of the result, and out-of-pocket cost. A model specification identifying necessary interactions was derived from assumptions of risk behavior and the decision context and was estimated using random-parameters logit. RESULTS: A total of 650 respondents were contacted, and 385 completed the survey. The monetary equivalent of test information was approximately $1800. Expenditures on colonoscopies to reduce mortality risks affected valuations. Respondents with lower income or who reported being employed significantly valued genetic tests more. CONCLUSION: Genetic testing may confer benefits through the impact of subsequent interventions on private individuals.

Getting it right with discrete choice experiments: Are we hot or cold?

Discrete Choice Experiments (DCEs) are widely employed survey-based methods to assess preferences for healthcare services and products. While they offer an experimental way to represent health-related decisions, the stylized representation of scenarios in DCEs may overlook contextual factors that could influence decision-making. The aim of this paper was to evaluate the predictive validity of preferences elicited through a DCE in decisions likely influenced by a hot-cold empathy gap, and compare it to another commonly used method, a direct-elicitation question. We focused on preferences for pain-relief modalities, especially for an epidural during childbirth - a context where direct-elicitation questions have shown a preference for or intention to have a natural birth (representing the "cold" state), yet individuals often opt for an epidural during labor (representing the "hot" state). Leveraging a unique dataset collected from 248 individuals, we incorporated both the stated preferences collected through a survey administered upon hospital admission for childbirth and the actual pain-relief modality usage data documented in medical records. The DCE allowed for the evaluation of scenarios outside of those expected by respondents to simulate decision-making during childbirth. When we compared the predicted epidural use with the actual epidural use during labor, we observed a choice concordance of 71-60%, depending on the model specification. The concordance rate between the predicted and actual choices increased to 77-76% when accounting for the initial use of other ineffective modalities. In contrast, the direct-elicitation choices, relying solely on respondents' baseline expectations, yielded a lower concordance rate of 58% with actual epidural use. These findings highlight the flexibility of the DCE method in simulating complex decision contexts, including those involving hot-cold empathy gaps. The DCE proves valuable in assessing nuanced preferences, providing a more accurate representation of the decision-making processes in healthcare scenarios.

Method for Calculating the Simultaneous Maximum Acceptable Risk Threshold (SMART) from Discrete-Choice Experiment Benefit-Risk Studies.

BACKGROUND: Medical decisions require weighing expected benefits of treatment against multiple adverse outcomes under uncertainty (i.e., risks) that must be accepted as a bundle. However, conventional maximum acceptable risk (MAR) estimates derived from discrete-choice experiment benefit-risk studies evaluate the acceptance of individual risks, assuming other risks are fixed, potentially leading decision makers to misinterpret levels of risk acceptance. DESIGN: Using simulations and a published discrete-choice experiment, we demonstrate a method for identifying multidimensional risk-tolerance measures given a treatment level of benefit. RESULTS: Simultaneous Maximum Acceptable Risk Thresholds (SMART) represents combinations of risks that would be jointly accepted in exchange for specific treatment benefits. The framework shows how the expectation of utility associated with treatments that involve multiple risks are related even when preferences for potential adverse events are independent. We find that the form of the marginal effects of adverse-event probabilities on the expected utility of treatment determines the magnitude of differences between SMART and conventional single-outcome MAR estimates. LIMITATIONS: Preferences for potential adverse events not considered in a study or preferences for adverse-event attributes held constant in risk-tolerance calculations may affect estimated risk tolerance. Further research is needed to understand the right balance between realistically reflecting clinical treatments with many potential adverse events and the cognitive burden of evaluating risk-risk tradeoffs in research and in practice. CONCLUSIONS AND IMPLICATIONS: SMART analysis should be considered in preference studies evaluating the joint acceptance of multiple potential adverse events. HIGHLIGHTS: Conventional approaches to calculate maximum-acceptable risk (MAR) using discrete-choice experiment data account for 1 adverse-event risk at a time, requiring that decision makers infer the acceptability of treatments when patients are exposed to multiple risks simultaneously.The Simultaneous Maximum Acceptable Risk Threshold (SMART) maps combinations of adverse-event risks that would be jointly acceptable given a specific treatment benefit and provides a transparent and precise portrayal of acceptance of multiple risks.Risk levels that would be accepted using individual MAR estimates might not be acceptable when simultaneous risks are considered, especially when marginal expected disutility of risk is decreasing nonlinearly with risk probabilities.Preference researchers should calculate SMARTs in any discrete-choice study in which 2 or more adverse-event risks are presented, particularly if risk preferences are nonlinear.