Abstract Background The German Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen) adapted the efficiency frontier (EF) approach to ...conform to statutory provisions on cost-effectiveness analysis of health technologies. EF serves as a framework for evaluating cost-effectiveness and indirectly for pricing and reimbursement decisions. Objectives To calculate an EF on the basis of single multidimensional benefit by taking patient preferences and uncertainty into account; to evaluate whether EF is useful to inform decision makers about cost-effectiveness of new therapies; and to find whether a treatment is efficient at given prices demonstrated through a case study on chronic hepatitis C. Methods A single multidimensional benefit was calculated by linear additive aggregation of multiple patient-relevant end points. End points were identified and weighted by patients in a previous discrete-choice experiment (DCE). Aggregation of overall benefit was ascertained using preferences and clinical data. Monte-Carlo simulation was applied. Uncertainty was addressed by price acceptability curve (PAC) and net monetary benefit (NMB). Results The case study illustrates that progress in benefit and efficiency of hepatitis C virus treatments could be depicted very well with the EF. On the basis of cost, effect, and preference data, the latest generations of interferon-free treatments are shown to yield a positive NMB and be efficient at current prices. Conclusions EF was implemented taking uncertainty into account. For the first time, a DCE was used with the EF. The study shows how DCEs in combination with EF, PAC, and NMB can contribute important information in the course of reimbursement and pricing decisions.
Abstract Regulatory decisions are often based on multiple clinical end points, but the perspectives used to judge the relative importance of those end points are predominantly those of expert ...decision makers rather than of the patient. However, there is a growing awareness that active patient and public participation can improve decision making, increase acceptance of decisions, and improve adherence to treatments. The assessment of risk versus benefit requires not only information on clinical outcomes but also value judgments about which outcomes are important and whether the potential benefits outweigh the harms. There are a number of mechanisms for capturing the input of patients, and regulatory bodies within the European Union are participating in several initiatives. These can include patients directly participating in the regulatory decision-making process or using information derived from patients in empirical studies as part of the evidence considered. One promising method that is being explored is the elicitation of “patient preferences.” Preferences , in this context, refer to the individual’s evaluation of health outcomes and can be understood as statements regarding the relative desirability of a range of treatment options, treatment characteristics, and health states. Several methods for preference measurement have been proposed, and pilot studies have been undertaken to use patient preference information in regulatory decision making. This article describes how preferences are currently being considered in the benefit-risk assessment context, and shows how different methods of preference elicitation are used to support decision making within the European context.
This study aimed to assess public preferences for the allocation of donor organs in Germany with the focus on ethical principles of distributive justice. We performed a discrete choice experiment ...(DCE) using a self-completed online questionnaire. Based on a systematic review and focus group discussions, six attributes, each with two–four levels, were selected (corresponding principle of distributive justice in brackets), including (1) life years gained after transplantation (principle of distributive justice: effectiveness/benefit – utilitarianism), (2) quality of life after transplantation (effectiveness/benefit – utilitarianism), (3) chance for a further donor organ offer (principle of distributive justice: medical urgency – favouring the worst-off), (4) age (medical and social risk factors: sociodemographic status), (5) registered donor (principle of distributive justice: value for society), and (6) individual role in causing organ failure (principle of distributive justice: own fault). Each respondent was presented with eight choice sets and asked to choose between two hypothetical patients without an opt-out. Data were analysed using conditional logit, mixed logit and latent class models. The final sample comprised 1028 respondents. Choice decisions were significantly influenced by all attributes except chance for a further donor organ offer. The attributes of good quality of life after transplantation, younger age, and no individual role in causing organ failure had the greatest impact on choice decisions. Life years gained after transplantation and being a registered donor were less important for the public. The latent class model identified four classes with preference heterogeneities. Respondents preferred to allocate deceased donor organs by criteria related to effectiveness/benefit, whereas medical urgency was of minor importance. Therefore, a public propensity for a rational, utilitarian, ethical model of allocation could be identified. Public preferences can help to inform policy to warrant socially responsible allocation systems and thus improve organ donation rates.
•Good quality of life after transplantation and younger age were the most important attributes.•Lower chance for a further donor organ offer was the least important attribute.•Trade-offs between medical urgency and effectiveness were not observable in this study.•Our DCE study linked these preferences with principles of distributive justice.•Understanding of public preferences can help to increase the willingness to donate.
Background The German Institute for Quality and Efficiency in Health Care (IQWiG) uses patient-relevant outcomes to inform decision-makers. Objective IQWiG conducted a pilot study to examine whether ...discrete choice experiments (DCEs) can be applied in health economic evaluations in Germany to identify, weight, and prioritize multiple patient-relevant outcomes, using the example of antiviral therapy for chronic hepatitis C (HCV). A further objective was to contribute to a more structured approach towards eliciting and comparing preferences across key stakeholders. Methods In autumn 2010, a DCE questionnaire was sent to patients with chronic HCV to estimate preferences across seven outcomes ("attributes"), including treatment efficacy sustained viral response (SVR) at 6 months, adverse effects (flu-like symptoms, gastrointestinal symptoms, psychiatric symptoms, and skin symptoms/alopecia), and measures of treatment burden (duration of therapy, frequency of injections). A linear model and an effects coded full model were applied to assess the relative importance of the attributes. Results In total N = 326 patients were included. A clear preference for SVR was shown; frequency of injections and duration of therapy shared the second rank, while psychiatric symptoms ranked third. The duration of flu-like symptoms was the least important attribute. Conclusion Our findings indicate that it is possible to perform a DCE at the national level in a health technology assessment agency. The weighting of multiple outcomes allows an indication-specific and evidence-based measure to be used in health economic evaluations. In decision-making in health care, the approach generally allows for consideration of patient-relevant trade-offs regarding the benefits and harms of medical interventions.
Efforts to reduce Human Immunodeficiency Virus (HIV) transmission through treatment rely on HIV testing programs that are acceptable to broad populations. Yet, testing preferences among diverse ...at-risk populations in Sub-Saharan Africa are poorly understood. We fielded a population-based discrete choice experiment (DCE) to evaluate factors that influence HIV-testing preferences in a low-resource setting.
Using formative work, a pilot study, and pretesting, we developed a DCE survey with five attributes: distance to testing, confidentiality, testing days (weekday vs. weekend), method for obtaining the sample for testing (blood from finger or arm, oral swab), and availability of HIV medications at the testing site. Cluster-randomization and Expanded Programme on Immunization (EPI) sampling methodology were used to enroll 486 community members, ages 18-49, in an urban setting in Northern Tanzania. Interviewer-assisted DCEs, presented to participants on iPads, were administered between September 2012 and February 2013.
Nearly three of five males (58%) and 85% of females had previously tested for HIV; 20% of males and 37% of females had tested within the past year. In gender-specific mixed logit analyses, distance to testing was the most important attribute to respondents, followed by confidentiality and the method for obtaining the sample for the HIV test. Both unconditional assessments of preferences for each attribute and mixed logit analyses of DCE choice patterns suggest significant preference heterogeneity among participants. Preferences differed between males and females, between those who had previously tested for HIV and those who had never tested, and between those who tested in the past year and those who tested more than a year ago.
The findings suggest potentially significant benefits from tailoring HIV testing interventions to match the preferences of specific populations, including males and females and those who have never tested for HIV.
To assess patient preferences for benefits and risks in hemophilia A treatment.
A systematic literature search and pretest interviews were conducted to determine the most patient-relevant endpoints ...in terms of effects, risks, and administration of hemophilia A treatments. A Best–Worst Scaling (BWS; Case 3 or multiprofile case) approach was applied in a structured questionnaire. Patients were surveyed by interviewers in a computer-assisted personal interview. Treatments in the choice scenarios comprised bleeding frequency per year, application type, risk of thromboembolic event risk, and inhibitor development. Each respondent answered 13 choice tasks, including 1 dominant task, comparing 3 treatment profiles. Data were analyzed using a mixed logit model (random-parameters logit).
Data from 57 patients were used. The attributes “bleeding frequency per year” and “inhibitor development” had the greatest impact on respondents’ choice decisions. Patients disliked being at risk of inhibitor development more than being at risk of thromboembolic events. The type of application, whether intravenous or subcutaneous, was of less importance for patients. There was a significant preference variation for all attributes.
Patients value low frequency of bleeding per year and low risk of development of inhibitors the most. An increase of risk and frequency would significantly decrease the impact on choice decisions. The type of application does not seem to influence the choice decision very much compared with the other attributes. Regarding preference heterogeneity, further analysis is needed to identify subgroups among patients and their characteristics. This may help to adapt individually patient-tailored treatment alternatives for hemophilia A patients.
•Among the four attributes defining hemophilia A treatments, “bleeding frequency per year” and “development of inhibitors” were most important and therefore had the highest impact on patients’ choices.•The attributes “type of application” and “risk of thromboembolic events” were less important for hemophilia A patients.•The mixed logit model and the standard deviations showed significant preference heterogeneity for all attributes in the sample.
Background
Deceased donor organs are scarce resources because of a large supply‐and‐demand mismatch. This scarcity leads to an ethical dilemma, forcing priority‐setting of how these organs should be ...allocated and whom to leave behind.
Objective
To explore public preferences for the allocation of donor organs in regard to ethical aspects of distributive justice.
Methods
Focus groups were facilitated between November and December 2018 at Hannover Medical School. Participants were recruited locally. Transcripts were assessed with content analysis using the deductive framework method. All identified and discussed criteria were grouped according to the principles of distributive justice and reported following the COREQ statement.
Results
Six focus groups with 31 participants were conducted. Overall, no group made a final decision of how to allocate donor organ; however, we observed that not only a single criterion/principle but rather a combination of criteria/principles is relevant. Therefore, the public wants to allocate organs to save as many lives as possible by both maximizing success for and also giving priority to urgent patients considering the best compatibility. Age, waiting time, reciprocity and healthy lifestyles should be used as additional criteria, while sex, financial status and family responsibility should not, based on aspects of equality.
Conclusions
All participants recognized the dilemma that prioritizing one patient might cause another one to die. They discussed mainly the unclear trade‐offs between effectiveness/benefit and medical urgency and did not establish an agreement about their importance. The results suggest a need of preference studies to elucidate public preferences in organ allocation.
Objective
To measure preference heterogeneity for monitoring systems among patients with a chronic heart failure.
Methods
A best–worst scaling experiment (BWS case 3) was conducted among patients ...with chronic heart failure to assess preferences for hypothetical monitoring care scenarios. These were characterized by the attributes mobility, risk of death, risk of hospitalization, type and frequency of monitoring, risk of medical device, and system-relevant complications. A latent class analysis (LCA) was used to analyze and interpret the data. In addition, a market simulator was used to examine which treatment configurations participants in the latent classes preferred.
Results
Data from 278 respondents were analyzed. The LCA identified four heterogeneous classes. For class 1, the most decisive factor was mobility with a longer distance covered being most important. Class 2 respondents directed their attention toward attribute “monitoring,” with a preferred monitoring frequency of nine times per year. The attribute risk of hospitalization was most important for respondents of class 3, closely followed by risk of death. For class 4, however, risk of death was most important. A market simulation showed that, even with high frequency of monitoring, most classes preferred therapy with high improvement in mobility, mortality, and hospitalization.
Conclusion
Using LCA, variations in preferences among different groups of patients with chronic heart failure were examined. This allows treatment alternatives to be adapted to individual needs of patients and patient groups. The findings of the study enhance clinical and allocative decision-making while elevating the quality of clinical data interpretation.
PDF
