Dean A. Regier

Conjoint analysis applications in health - A checklist: A report of the ISPOR Good Research Practices for Conjoint Analysis Task Force

BACKGROUND The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards. OBJECTIVE The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health. METHODS The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers. RESULTS Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items. CONCLUSIONS Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies.

Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force

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 forces 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).

ISPOR task force reportConstructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force

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 forces 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).

Evaluating health-related quality-of-life studies in paediatric populations: some conceptual, methodological and developmental considerations and recent applications.

Although numerous paediatric-based health-related quality-of-life (HR-QOL) instruments are currently in use, there still remain conceptual, methodological and developmental issues to address. This paper provides an up-to-date critical review of the HR-QOL literature in paediatric medicine.Our analysis indicates that there is no consensus on how HR-QOL and overall QOL should be defined and measured in children. It is recommended that future studies focus on operationalising and distinguishing these constructs from each other and from traditional health-status measures. A clear empirical basis for generating instrument items and for prioritising specific domains must be described. Researchers should consider using the data gathered during their first interviews as a springboard from which to test their ideas of HR-QOL and QOL, reformulate concepts and subsequently retest their notions before developing instruments.Related to methodological challenges, consistency and agreement are still used interchangeably when comparing child and parent reports of children’s HR-QOL. The Pearson correlation is a measure of co-variation in scores, and not a measure of agreement. We recommend that researchers focus on determining agreement as opposed to consistency. Few, if any, attempts have been made to account for the possibility that a response shift may have occurred in the evaluation of HR-QOL. Most studies have compared HR-QOL scores of children with illness with their healthy peers. As such, there is a dearth of knowledge regarding the normative process of adaptation within the context of illness. It is recommended that researchers focus on gathering data using a relative standard of comparison. We further recommend that researchers interpret HR-QOL data in line with their intended purpose. Regarding developmental consideration, particular attention ought to be paid to developing instruments that consider children’s emerging sense of self, cognitive capacity and emotional awareness. Instruments that include items that are age appropriate are more likely to maximise reliability and validity of reports.The results of many HR-QOL instruments are applied in pharmacotherapeutic and pharmacoeconomic assessments. However, there has been relative infrequent application of economically valid HR-QOL tools (utility scales) and the use of HR-QOL scales as outcome measures in paediatric drug trials. As such, few cost-utility analyses have been performed to inform paediatric decision making. In addition, many of the concerns in the development of HR-QOL instruments should also be applied to the utility scales such that they reflect adequately children’s preferences for health states.

An Overview of Economic Evaluations for Drugs Used in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, progressive, inflammatory disease that affects approximately 0.5–1% of the adult population. The introduction of new disease-modifying antirheumatic drugs (DMARDs) such as leflunomide, anakinra and the tumour necrosis factor (TNF)-α antagonists (infliximab, etanercept and adalimumab) have transformed the management of RA. In particular, the last class of agents has generated substantial controversy. Costing between

Cost-effectiveness of self-managed versus physician-managed oral anticoagulation therapy

US16 000 and

Value for Money? Array Genomic Hybridization for Diagnostic Testing for Genetic Causes of Intellectual Disability

US20 000 per patient-year (2001 values), the potential greater efficacy of treatment with TNFα antagonists comes at much higher drug costs, making these agents natural candidates for cost-effectiveness analyses (CEAs).A MEDLINE search (until 31 January 2004) identified six original CEAs evaluating TNFα antagonists in RA. The aim of a CEA is to facilitate the allocation of scarce health resources and to inform policy decisions. However, to enhance the reliability and relevance of these analyses to policy makers, there must be similarity between the methodologies used. Recently, the OMERACT (Outcome Measures in Rheumatoid Arthritis Clinical Trials) group produced a document to define such a reference case; the OMERACT document was used as a foundation to structure comparisons and highlight discrepancies.The methodologies employed in each analysis differed; in particular, disparate time horizons, comparators, quantities of drug and treatment sequences prohibit the comparison of cost effectiveness between studies. Outcomes also differed between the analyses. Most reported health-related quality of life (HR-QOL) in quality-adjusted life-years (QALYs). The QALYs metric was based on preference scores that were typically derived from linear regressions using the Health Assessment Questionnaire (HAQ). However, models also used American College of Rheumatology (ACR) criteria, as well as the disease activity score (DAS). Common to all studies was the lack of data from long-term randomised studies where efficacy and resource consumption in comparison with standard care has been investigated. As such, investigators combined short-term randomised control trial data with that of a long-term observational cohort, and modelled cost effectiveness over an appropriate time horizon. In addition, most analyses lacked rigorous sensitivity analysis to examine the impact of uncertainty in the parameters.Those analyses that examined time horizons of 6 months and 1 year published incremental cost-effectiveness ratios (ICERs) of

Bayesian and classical estimation of mixed logit: An application to genetic testing

US34 800 per ACR 70% response criteria (ACR70) weighted response (duration 6 months, 1999 values) and

Return of Incidental Findings in Genomic Medicine: Measuring What Patients Value: Development of an Instrument to Measure PReferences for Information from Next-generation Testing (IMPRINT)

US96 166 (duration 1 year, 2002 values). Analyses that modelled costs and health outcomes beyond the first year reported ICER estimates ranging between

Chemotherapy versus supportive care alone in pediatric palliative care for cancer: comparing the preferences of parents and health care professionals

US26 800 (patients’ lifetime, 1998 values) and