SUNDAY, 25 OCTOBER 2009 - MORNING COURSES (8:00 – 12:00)

Use of Pharmacoeconomics / Economic / Outcomes Research Information

Reimbursement Systems in Europe
Faculty: James Furniss, Director, Global Market Access Solutions, Bridgehead International, Melton Mowbray, UK; Kevin W. Mayo PhD, Vice President, Bridgehead USA Inc, New York, NY, USA & Adjunct Professor, University of the Sciences in Philadelphia, Philadelphia, PA, USA; Sasha Richardson MBA, Principal Consultant, Bridgehead International, London, UK
Course Description: This course is designed to provide participants with an understanding of the various procedures employed by European health authorities to regulate market access based upon the appraisal of the clinical and in some countries economic value of new medical technologies. The faculty will systematically describe the reimbursement legislation, processes and organizations within each nation and describe the role of the pharmaceutical and/or medical device manufacturer.  This course is designed for individuals with intermediate experience within a single health care system who wish to broaden their appreciation of other reimbursement systems.

Pharmacoeconomic / Economic Methods

Transferability of Cost-Effectiveness Data between Countries
Faculty: JL Severens PhD, Professor of Medical Technology Assessment, CAPHRI School for Public Health and Primary Care, Department of Health Organization, Policy, and Economics, Faculty of Health, Medicine, and Life Sciences, Maastricht University, & Department of Clinical Epidemiology and MTA, University Hospital Maastricht, Maastricht, The Netherlands; SMAA Evers PhD LL.M, Associate Professor, CAPHRI School for Public Health and Primary Care, Department of Health Organization, Policy, and Economics, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands; MA Joore PhD, Department of Clinical Epidemiology and MTA, University Hospital Maastricht, Maastricht, The Netherlands; S. Knies MPhil, PhD Student, CAPHRI School for Public Health and Primary Care, Department of Health Organization, Policy, and Economics, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
Course Description: Although the number of countries requiring an economic dossier as part of the submission dossier for public reimbursement of new drugs is growing, the pharmaceutical industry cannot conduct economic evaluations in every potential market. However, national decision-makers require country-specific or region-specific data or estimates on health care costs and patient outcomes. More and more, they are only willing to accept foreign or international data when they are transferable to their own specific decision-making context. But little guidance on how to do this exists. This course starts with a discussion of factors that make economic data more difficult to transfer from one country to other countries than clinical data, and will focus on the report of the ISPOR Good Practices on Economic Data Transferability Task Force. Then we review the methods that have been presented to assess the transferability of foreign cost, effects and cost-effectiveness estimates and their pros and cons. This topic will be practically covered in a case study (working in small groups), that will be discussed, subsequently. Methods available focus on trial-based economic evaluation, however we will present transferring issues encountered when assessing model-based economic evaluations. Finally, we will discuss the transferability of health state valuation based on the EQ5-D instrument. The statistical methods to analyze multinational trial data and to transfer these data to a specific country are beyond the scope of this course. This course is for those with advanced understanding of economic evaluations of health care programs and experience in the critical assessment of cost-effectiveness studies.

Cost-Effectiveness Analysis alongside Clinical Trials
Faculty: Scott Ramsey MD, PhD, Full Member & Professor, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Sean D. Sullivan PhD, RPh, MS, Professor and Director, University of Washington, Pharmaceutical Outcomes Research and Policy Program, Seattle, WA, USA; Richard Willke PhD, Senior Director, Head, Global Health Economics and Outcomes Research, Global Market Access, Primary Care Business Unit, Pfizer Inc, Peapack, NJ, USA
Course Description: The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. This course will present the design, conduct, and reporting of cost-effectiveness analyses alongside clinical trials based on, in part, the Good Research Practices for Cost-Effectiveness Analysis alongside Clinical Trials: The ISPOR RCT-CEA Task Force Report. Trial design, selecting data elements, database design and management, analysis, and reporting of results will be presented. Trials designed to evaluate effectiveness (rather than efficacy), as well as clinical outcome measures will be discussed. How to obtain health resource use and health state utilities directly from study subjects and economic data collection fully integrated into the study will also be discussed. Analyses guided by an analysis plan and hypotheses, an incremental analysis using an intention to treat approach, and characterization of uncertainty, and standards for reporting results will be presented. This course is an introductory/intermediate level. Familiarity with economic evaluations will be helpful.

Modeling Methods

Pharmacoeconomic Modeling – Advanced
Faculty: Uwe Siebert MD, MPH, MSc, ScD, Professor and Head, Department of Public Health, Medical Decision Making and Health Technology Assessment, University of Health Sciences, Medical Informatics and Technology, Hall/Innsbruck, Austria, & Associate Professor of Radiology, Harvard Medical School, Director of the Cardiovascular Research Program, Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA; Alexander Göhler MD, MSc, MPH, PhD, Senior Scientist, MGH-Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA and Assistant Professor, Institute for Public Health, Medical Decision Making and HTA, UMIT, Hall, Austria
Course Description: This course will provide an in-depth look at modeling techniques and their application in a “real world” setting. It will discuss the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health Care Evaluations and evaluate its implications for the application of various modeling methods. Using a series of related examples, the course will carefully review steps involved in developing and using these kinds of models. This course will cover the practical steps involved in the selection and modeling of data inputs and practical aspects related to the determination of when, why and how to handle stochastic (i.e., first order Monte Carlo Simulations) and probabilistic uncertainty (i.e., second order Monte Carlo Simulations). This course is intended as a follow-up to the short course, “Pharmacoeconomic Modeling”, and is designed for those with intermediate to advance knowledge of modeling methods.

Quality of Life / Patient-Reported Outcomes / Preference-Based Methods

Advanced Patient-Reported Outcomes Assessment: Psychometric Methods
Faculty: Cheryl Coon PhD, Director, Psychometrics, RTI Health Solutions, Research Triangle Park, NC, USA; Mark Price MA, MEd, Senior Health Outcomes Scientist, Psychometrics, RTI Health Solutions, Research Triangle Park, NC, USA; Lauren Nelson PhD, Director, Psychometrics, RTI Health Solutions, Research Triangle Park, NC, USA (Contributing author)
Course Description: This course will discuss psychometric analysis and the application of various techniques such as structural equation modeling (SEM), factor analysis (FA) and item response theory (IRT) in testing patient-reported outcomes (PRO) instruments, measures and construct / criterion validity.  Validity indicates how well a measurement tool allows us to infer something about the true nature and value of the object or system being considered.  Instructors will explain and demonstrate how to analyze observed and latent constructs and variables within a model as well as to test the validity of a PRO measure.  Specific examples will be given to highlight how researchers can apply these techniques to test methods, criteria and new measures.  This is an advanced course designed for those with a working knowledge of QoL/PRO methods.

Real World Data Methods

Propensity Scores and Comorbidity Risk Adjustment
Faculty: Fadia Shaya MPH, PhD, Associate Professor/Associate Director, University of Maryland School of Pharmacy, Center on Drugs and Public Policy, Baltimore, MD, USA; Priscilla Velentgas PhD, Director, Epidemiology, Outcome, Cambridge, MA, USA
Course Description: A large part of the evidence about the effectiveness of different treatments is based on retrospective studies. Issues of bias and confounding relate to the non-random assignment of subjects and co-morbidity burden. This course will outline the concerns about bias and explain the methods for causal inference in observational studies, where researchers have no control over the treatment assignment. A lack of balance in the covariates between the treatment and control groups can produce biased estimates of the treatment effects. We will explain how propensity scores can be used to reduce bias, through stratification, matching or regression. Confounding and the pros and cons of standard adjustment, propensity scoring methodology (sub classification on one confounding variable, overlap in treatment groups, variable selection) will be discussed. In the second part, we will elaborate on risk adjustment models, focusing on morbidity indices, e.g  the Charlson Comorbidity Index, and Chronic Disease Scores. Examples using a step by step approach will be presented. This is an introductory course, designed for those with little experience with this methodology but some knowledge of observational databases. The short course “Introduction to Statistics” is recommended as a precursor to this course.