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Background: Electronic data collection is increasingly being used for discrete choice experiments (DCEs).Objectives: To study whether paper or electronic administration results in measurement effects.Methods: Respondents were drawn from the same sample frame (an Internet panel) and completed a nearly identical DCE survey either online or on paper during the same period. A DCE on preferences for basic health insurance served as a case study. We used panel mixed logit models for the analysis.Results: In total, 898 respondents completed the survey: 533 respondents completed the survey online, whereas 365 respondents returned the paper survey. There were no significant differences with respect to sociodemographic characteristics between the respondents in both samples. The median response time was shorter for the online sample than for the paper sample, and a smaller proportion of respondents from the online sample were satisfied with the number of choice sets. Although some willingness- to-pay estimates were higher for the online sample, the elicited preferences for basic health insurance characteristics were similar between both modes of administration.Conclusions: We find no indication that online surveys yield inferior results compared with paper-based surveys, whereas the price per respondent is lower for online surveys. Researchers might want to include fewer choice sets per respondent when collecting DCE data online. Because our findings are based on a nonrandomized DCE that covers one health domain only, research in other domains is needed to support our findings. [ABSTRACT FROM AUTHOR]

Objectives: To synthesize the findings of cognitive interview and usability studies performed to assess the measurement equivalence of patient-reported outcome (PRO) instruments migrated from paper to electronic formats (ePRO), and make recommendations regarding future migration validation requirements and ePRO design best practice.Methods: We synthesized findings from all cognitive interview and usability studies performed by a contract research organization between 2012 and 2015: 53 studies comprising 68 unique instruments and 101 instrument evaluations. We summarized study findings to make recommendations for best practice and future validation requirements.Results: Five studies (9%) identified minor findings during cognitive interview that may possibly affect instrument measurement properties. All findings could be addressed by application of ePRO best practice, such as eliminating scrolling, ensuring appropriate font size, ensuring suitable thickness of visual analogue scale lines, and providing suitable instructions. Similarly, regarding solution usability, 49 of the 53 studies (92%) recommended no changes in display clarity, navigation, operation, and completion without help. Reported usability findings could be eliminated by following good product design such as the size, location, and responsiveness of navigation buttons.Conclusions: With the benefit of accumulating evidence, it is possible to relax the need to routinely conduct cognitive interview and usability studies when implementing minor changes during instrument migration. Application of design best practice and selecting vendor solutions with good user interface and user experience properties that have been assessed in a representative group may enable many instrument migrations to be accepted without formal validation studies by instead conducting a structured expert screen review. [ABSTRACT FROM AUTHOR]

Background: Constrained optimization methods are already widely used in health care to solve problems that represent traditional applications of operations research methods, such as choosing the optimal location for new facilities or making the most efficient use of operating room capacity.Objectives: In this paper we illustrate the potential utility of these methods for finding optimal solutions to problems in health care delivery and policy. To do so, we selected three award-winning papers in health care delivery or policy development, reflecting a range of optimization algorithms. Two of the three papers are reviewed using the ISPOR Constrained Optimization Good Practice Checklist, adapted from the framework presented in the initial Optimization Task Force Report. The first case study illustrates application of linear programming to determine the optimal mix of screening and vaccination strategies for the prevention of cervical cancer. The second case illustrates application of the Markov Decision Process to find the optimal strategy for treating type 2 diabetes patients for hypercholesterolemia using statins. The third paper (described in Appendix 1) is used as an educational tool. The goal is to describe the characteristics of a radiation therapy optimization problem and then invite the reader to formulate the mathematical model for solving it. This example is particularly interesting because it lends itself to a range of possible models, including linear, nonlinear, and mixed-integer programming formulations. From the case studies presented, we hope the reader will develop an appreciation for the wide range of problem types that can be addressed with constrained optimization methods, as well as the variety of methods available.Conclusions: Constrained optimization methods are informative in providing insights to decision makers about optimal target solutions and the magnitude of the loss of benefit or increased costs associated with the ultimate clinical decision or policy choice. Failing to identify a mathematically superior or optimal solution represents a missed opportunity to improve economic efficiency in the delivery of care and clinical outcomes for patients. The ISPOR Optimization Methods Emerging Good Practices Task Force's first report provided an introduction to constrained optimization methods to solve important clinical and health policy problems. This report also outlined the relationship of constrained optimization methods relative to traditional health economic modeling, graphically illustrated a simple formulation, and identified some of the major variants of constrained optimization models, such as linear programming, dynamic programming, integer programming, and stochastic programming. The second report illustrates the application of constrained optimization methods in health care decision making using three case studies. The studies focus on determining optimal screening and vaccination strategies for cervical cancer, optimal statin start times for diabetes, and an educational case to invite the reader to formulate radiation therapy optimization problems. These illustrate a wide range of problem types that can be addressed with constrained optimization methods. [ABSTRACT FROM AUTHOR]

Objectives: To respond to the 'quality assurance' of the EQ-5D-5L value set for England study.Methods: We provide a point-by-point response to the issues raised by the authors of the quality assurance paper, drawing on theoretical arguments, empirical analyses and practical considerations.Results: We provide evidence to show that many of the points made by the authors of the quality assurance are misleading, suggest misunderstandings, or are irrelevant.Conclusions: The modeling approaches which were used appropriately address the characteristics of the data and provide a reasonable representation of the average stated preferences of general public in England. We provide reflections on the conduct of stated preference studies, and suggestions for the way forward. [ABSTRACT FROM AUTHOR]

Background: Model replication is important because it enables researchers to check research integrity and transparency and, potentially, to inform the model conceptualization process when developing a new or updated model.Objective: The aim of this study was to evaluate the replicability of published decision analytic models and to identify the barriers and facilitators to replication.Methods: Replication attempts of 5 published economic modeling studies were made. The replications were conducted using only publicly available information within the manuscripts and supplementary materials. The replicator attempted to reproduce the key results detailed in the paper, for example, the total cost, total outcomes, and if applicable, incremental cost-effectiveness ratio reported. Although a replication attempt was not explicitly defined as a success or failure, the replicated results were compared for percentage difference to the original results.Results: In conducting the replication attempts, common barriers and facilitators emerged. For most case studies, the replicator needed to make additional assumptions when recreating the model. This was often exacerbated by conflicting information being presented in the text and the tables. Across the case studies, the variation between original and replicated results ranged from -4.54% to 108.00% for costs and -3.81% to 0.40% for outcomes.Conclusion: This study demonstrates that although models may appear to be comprehensively reported, it is often not enough to facilitate a precise replication. Further work is needed to understand how to improve model transparency and in turn increase the chances of replication, thus ensuring future usability. [ABSTRACT FROM AUTHOR]

An increasing number of health-care systems, both public and private, such as managed-care organizations, are adopting results from cost-effectiveness (CE) analysis as one of the measures to inform decisions on allocation of health-care resources. It is expected that thresholds for CE ratios may be established for the acceptance of reimbursement or formulary listing.This paper provides an overview of the development of and debate on CE thresholds, reviews threshold figures (i.e., cost per unit of health gain) currently proposed for or applied to resource-allocation decisions, and explores how thresholds may emerge.At the time of this review, there is no evidence from the literature that any health-care system has yet implemented explicit CE ratio thresholds. The fact that some government agencies have utilized results from CE analysis in pricing/reimbursement decisions allows for retrospective analysis of the consistency of these decisions. As CE analysis becomes more widely utilized in assisting health-care decision-making, this may cause decision-makers to become increasingly consistent.When CE analysis is conducted, well-established methodology should be used and transparency should be ensured. CE thresholds are expected to emerge in many countries, driven by the need for transparent and consistent decision-making. Future thresholds will likely be higher in most high-income countries than currently cited rules of thumb. [ABSTRACT FROM AUTHOR]

Introduction: Statistical analyses of data and making sense of medical data have received much attention in the medical literature, but nevertheless have caused confusion among practitioners. Each researcher provides a different method for comparing treatments. For example, when the end point is binary, such as disease versus no disease, the common measures are odds ratios, relative risk, relative risk reduction, absolute risk reduction, and the number needed to treat. The question faced by the practitioner is then: Which one will help me in choosing the best treatment for my patient? Methods: The purpose of this paper is to illustrate, using examples, how each measure is used, what it means, and what are its advantages and disadvantages. Results: Some pairs of measures present equivalent information. Furthermore, it is shown that different measures result in different impressions. Conclusion: It is recommended that researchers report both a relative and an absolute measure and present these with appropriate confidence intervals. [ABSTRACT FROM AUTHOR]

Abstract Objectives The impact of economic evaluation studies on health-care decision makers has been shown to be rather limited. However, there is an increasing requirement for the cost-effectiveness of health-care interventions to be considered in formulating and implementing guidelines for clinical practice. This paper reports the findings of recent focus group research among UK health authorities, which examined the usefulness of published economic evaluations within the decision-making processes. The findings are presented and discussed in light of other studies that have addressed this issue. Methods Focus group research was conducted with decision makers from a sample of two UK health authorities using the National Health Service Economic Evaluation Database (NHS EED) as a research vehicle to locate and report the findings of relevant economic studies. The study sample was initially invited to respond to questionnaires exploring the usefulness of published economic evaluations in the decision-making process and to outline particular topics that it felt would benefit from similar economic evidence. Following this, a detailed search was undertaken to retrieve structured NHS EED abstracts on these topics such that the usefulness and limitations of economic evaluations to decision making could be determined. Results Decision makers generally recognized the usefulness and necessity of published economic evaluations in informing their decision-making processes. However, the value of studies was often limited because of the poor generalizability of results, the narrowness of research questions, and the lack of methodological rigor common to many published studies. A total of 237 NHS EED full abstracts were retrieved in the specified areas of interest, which, within specified caveats, were generally found to be useful as decision-making tools. There was a general consensus among decision makers in favor of developing a quality-scoring system for studies, thereby... [ABSTRACT FROM AUTHOR]

To perform a systematic literature review on the criteria and scoring functions applied in multi-criteria decision analysis (MCDA) tools and value frameworks relevant to evaluate pharmaceuticals used to treat rare diseases. The aim was to describe published value attributes of treatments for rare diseases, and to categorize these value criteria based on traditional value assessment practices. Methods MCDA or value framework articles relevant for pricing and reimbursement decision making of pharmaceuticals, and structured review papers on orphan drug specific MCDA articles were reviewed. [Extracted from the article]