Stated-preference methods are a class of evaluation techniques for studying the preferences of patients and other stakeholders. While these methods span a variety of techniques, conjoint-analysis methods-and particularly discrete-choice experiments (DCEs)-have become the most frequently applied approach in health care in recent years. Experimental design is an important stage in the development of such methods, but establishing a consensus on standards is hampered by lack of understanding of available techniques and software. This report builds on the previous ISPOR Conjoint Analysis Task Force Report: Conjoint Analysis Applications in Health-A Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. This report aims to assist researchers specifically in evaluating alternative approaches to experimental design, a difficult and important element of successful DCEs. While this report does not endorse any specific approach, it does provide a guide for choosing an approach that is appropriate for a particular study. In particular, it provides an overview of the role of experimental designs for the successful implementation of the DCE approach in health care studies, and it provides researchers with an introduction to constructing experimental designs on the basis of study objectives and the statistical model researchers have selected for the study. The report outlines the theoretical requirements for designs that identify choice-model preference parameters and summarizes and compares a number of available approaches for constructing experimental designs. The task-force leadership group met via bimonthly teleconferences and in person at ISPOR meetings in the United States and Europe. An international group of experimental-design experts was consulted during this process to discuss existing approaches for experimental design and to review the task force's draft reports. In addition, ISPOR members contributed to developing a consensus report by submitting written comments during the review process and oral comments during two forum presentations at the ISPOR 16th and 17th Annual International Meetings held in Baltimore (2011) and Washington, DC (2012).

This study applies conjoint analysis to estimate health-related benefit-risk tradeoffs in a non-expected-utility framework. We demonstrate how this method can be used to test for and estimate nonlinear weighting of adverse-event probabilities and we explore the implications of nonlinear weighting on maximum acceptable risk (MAR) measures of risk tolerance. We obtained preference data from 570 Crohn's disease patients using a web-enabled conjoint survey. Respondents were presented with choice tasks involving treatment options that involve different efficacy benefits and different mortality risks for 3 possible side effects. Using conditional logit maximum likelihood estimation, we estimate preference parameters using 3 models that allow for nonlinear preference weighting of risks--a categorical model, a simple-weighting model, and a rank dependent utility (RDU) model. For the second 2 models we specify and jointly estimate 1- and 2-parameter probability weighting functions. Although the 2-parameter functions are more flexible, estimation of the 1-parameter functions generally performed better. Despite well-known conceptual limitations, the simple-weighting model allows us to estimate weighting function parameters that vary across 3 risk types, and we find some evidence of statistically significant differences across risks. The parameter estimates from RDU model with the single-parameter weighting function provide the most robust estimates of MAR. For an improvement in Crohn's symptom severity from moderate and mild, we estimate maximum 10-year mortality risk tolerances ranging from 2.6% to 7.1%. Our results provide further the evidence that quantitative benefit-risk analysis used to evaluate medical interventions should account explicitly for the nonlinear probability weighting of preferences.

Background Therapy options for mesalamine-refractory ulcerative colitis (UC) include immunosuppressive medications or surgery. Chronic immunosuppressive therapy increases risks of infection and cancer, whereas surgery produces a permanent change in bowel function. We sought to quantify the willingness of patients with UC to accept the risks of chronic immunosuppression to avoid colectomy. Methods We conducted a state-of-the-art discrete-choice experiment among 293 patients with UC who were offered a choice of medication or surgical treatments with different features. Random parameters logit was used to estimate patients’ willingness to accept trade-offs among treatment features in selecting surgery versus medical treatment. Results A desire to avoid surgery and the surgery type (ostomy versus J-pouch) influenced patients’ choices more than a specified range of 10-year mortality risks from lymphoma or infection, or disease activity (mild versus remission). To avoid an ostomy, patients were willing to accept a >5% 10-year risk of dying from lymphoma or infection from medical therapy, regardless of medication efficacy. However, data on patients’ stated choice indicated perceived equivalence between J-pouch surgery and incompletely effective medical therapy. Patient characteristics and disease history influenced patients’ preferences regarding surgery versus medical therapy. Conclusions Patients with UC are willing to accept relatively high risks of fatal complications from medical therapy to avoid a permanent ostomy and to achieve durable clinical remission. However, patients view J-pouch surgery, but not permanent ileostomy, as an acceptable therapy for refractory UC in which medical therapy is unable to induce a durable remission.

Insights from the survival analyses recommend possible inclusion of functional status into SRTR's risk-adjusted models. Moreover, they invite further examination of its use in order to improve current listing and transplantation strategies at transplant centers and potentially reduce deceased-donor kidney discard rate.

Background/Objectives: Potentially inappropriate opioid prescribing (PIP) may contribute to risk for fatal opioid overdose among older adults (age 50+). Our objective was to examine the effect of age on the likelihood of PIP exposure, as well as the effect of PIP exposure on adverse outcomes. Design: Retrospective cohort study Setting: Data from multiple state agencies in Massachusetts, 2011–2015 Participants: Over 3 million adult Massachusetts residents (3,078,163) who received at least one prescription opioid during the study period; approximately half (1,589,365) were older adults (age 50+). Measurements: We measured exposure to five types of PIP: high-dose opioids, co-prescription with benzodiazepines, multiple opioid prescribers, multiple opioid pharmacies, and continuous opioid therapy without a pain diagnosis. We examined three adverse outcomes: non-fatal opioid overdose, fatal opioid overdose, and all-cause mortality. Results: The rate of any PIP exposure increased with age, ranging from 2% among individuals age 18–29 to 14% among those age 50 and older. Older adults also had elevated rates of exposure to two or more different types of PIP, including 5% of adults age 50–69 and 4% of adults age 70 or older, in comparison to 2.5% of age 40–49 and lower percentages in younger age groups. Among covariates assessed, increasing age was the greatest positive predictor of PIP exposure. In analyses stratified by age, exposure to both any PIP and specific types of PIP were associated with non-fatal overdose, fatal overdose, and all-cause mortality among both younger and older adults. Conclusion: Older adults are more likely to be exposed to PIP, which elevates their risk for adverse events. Strategies to reduce exposure to PIP, and to improve outcomes among those already exposed, will be instrumental to addressing the opioid crisis as it manifests among older adults.