SATURDAY, 20 OCTOBER 2007 - ALL DAY COURSES (9:00 - 18:00)

Pharmacoeconomics for Decision-Makers
Faculty: Lieven Annemans PhD, MSC, Professor, Ghent University, Faculty of Medicine, Meise, Belgium.
Course Description: This course is designed to teach clinicians and new researchers how to incorporate pharmacoeconomics into study design and data analysis. Participants will learn how to collect and calculate the costs of different alternatives, determine the economic impact of clinical outcomes, and how to identify, track and assign costs to different types of health care resources used. The development of economic protocols and data collection sheets will be discussed. Different pharmacoeconomic models and techniques will be demonstrated and practiced in lectures and case studies. These include cost-minimization, cost-of-illness, cost effectiveness, cost-benefit, and cost-utility analysis. Decision analysis, sensitivity analysis, and discounting will all be demonstrated and practiced. Participants will also learn to compare and evaluate interventions such as drugs, devices and clinical services. This course is suitable for those with little or no experience with pharmacoeconomics.

Discrete Event Simulation for Economic Analyses
Faculty: J. Jaime Caro MDCM, FCRPC, FACP, Adjunct Professor of Medicine, Adjunct Professor of Epidemiology and Biostatistics, McGill University, Montreal PQ and Senior Vice President, Health Economics, United BioSource, Concord, MA, USA; Jörgen Möller MSc Mech Eng, Simulation Specialist, United BioSource, Concord, MA, USA
Course Description: This course will provide a basic understanding of the key concepts of discrete event simulation. The focus will be on the use of these simulation models to address pharmacoeconomic (and device-related) problems. The course will be structured around practical exercises. Topics to be covered are: Why DES? Dynamic simulation as a tool; Components of a DES; How do you build a model? Modeling of processes and resource use; Modeling of variables and decisions. If time permits, simple animation will be demonstrated. We will use ARENA to build simple models. Instructors will distribute training versions of Arena. This course is designed for those with some experience with modeling. 

SATURDAY, 20 OCTOBER 2007 - MORNING (9:00 - 13:00)

Elements of Pharmaceutical/Biotech Pricing I - Introduction
Faculty: Jack Mycka, President & Partner, MME LLC, Montclair, NJ, USA; Renato Dellamano PhD, President, ValueVector (Value Added Business Strategies), Milan, Italy
Course Description: This course will give participants a basic understanding of  the key terminology and issues involved in pharmaceutical pricing decisions. It will cover the tools to build and document product value including issues, information and processes employed (including pricing research); the role of pharmacoeconomics and the differences in payment systems that help to shape pricing decisions. These tools will be further explored through a series of  interactive exercises. This course is designed for those with limited experience in the area of pharmaceutical pricing and will cover topics within a global context.

Pharmacoeconomic Modeling
Faculty: Uwe Siebert MD, MPH, MSc, ScD, Professor of Public Health; Head of the Department of Public Health, Medical Decision Making and Health Technology Assessment, University of Health Sciences, Medical Informatics and Technology, Hall/Innsbruck, Austria, and Associate Professor of Radiology, Harvard Medical School, Director of the Cardiovascular Research Program, Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA; Björn Stollenwerk PhD, Senior Scientist, Dept. of Public Health, Medical Decision Making and HTA, UMIT, Hall/Innsbruck, Austria.
Course Description: This course provides an introduction to Markov modeling techniques and their practical application in pharmacoeconomic modeling. We present analytic approaches including deterministic cohort simulation and Monte Carlo simulation and we give some technical instructions for modelers. We discuss the concepts of variability, uncertainty, probabilistic sensitivity analysis (PSA), and cost-effectiveness acceptability curves (CEAC). We review the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health Care Evaluations and explore, when and how modeling should be used in economic evaluation. This course is designed for those with some familiarity with modeling techniques.

European Databases and Retrospective Database Analysis
Faculty: Elise Pelletier MSc, Director, IMS Health Consulting, Health Economics and Outcomes Research, Watertown, MA, USA; Erik Spaepen BA Pharmaceutical Sciences Technologies, Senior Data Analyst, IMS Health, Brussels, Belgium
Course Description: Large administrative patient databases provide a unique opportunity toexamine retrospectively the effects of drug use on clinical and economic outcomes in "real world" settings.This course will take a methodological approach to the practical usage of existing patient databases in Europe and cover a discussion of the ISPOR Checklist for Retroactive database studies -Report of the ISPOR Task Force on Retrospective Databases and selected topics related to estimators and sampling distributions, properties of sampling distributions (unbiasedness, efficiency, mean square error), and ordinary least squares (OLS) regression. More complex topics beginning with the problem of endogeneity, identification, instrumental variables, sample selection models, and propensity score models, maximum likelihood methods and the estimation of  limited dependent variables models including logit, multinomial logit, count models, and survival models will be discussed. Discussion will include a reference to the SPOR Digest of  International Databases and its “real world” applications to retrospective data-base analysis. This course assumes participants have knowledge of statistical methods and understanding in the analysis of administrative patient databases.

Application of Item Response Theory in Patient Outcomes Measurement
Faculty: Jakob Bue Bjorner Md, PhD, Professor of Epidemiology, Danish National Centre for the Working Environment, Denmark
Course Description: Item Response Theory measures the mathematical relationship between an examinee ability and item response, in order to attain more accurate readings of actual aptitude/conceptions of health-related devices and issues. It was developed in response to a growing need for more advanced tools and models to measure such constructs. This course will highlight the background of Item Response Theory as well as discuss in-depth its applications in patient outcomes research. Instructors will also evaluate the usefulness of Item Response Theory in comparison with other patient outcomes measures. Various software programs used to analyze data through item response theory (such as Mplus and PARSCALE) will be incorporated into a number of hands-on exercises for the course participants. This course is designed for those with little experience with Item Response Theory.

SATURDAY, 20 OCTOBER 2007 - AFTERNOON COURSES (14:00 - 18:00)

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
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 course is designed for those with little experience with this methodology but some knowledge of observational databases.

Patient Registries: Overview & Application
Faculty: Jeffrey Trotter MBA, Senior Vice President, ICON Clinical Research, Lifecycle Sciences Group, Highland Park, IL, USA
Course Description: This course is designed to provide an overview of patient registries and its applications in identifying 'real world' clinical, safety, and patient-perspective issues. The advantages and disadvantages of patient registry versus other “real world’ data collection will be presented. The course will address safety and clinical objectives, as well as regulatory trends and requirements. Key operational components and challenges, and measures of program success will be discussed. Management issues, including creating effective partnerships with patient-oriented organizations and facilitating long-term program operations within a changing organizational structure will be addressed. This course is designed for those with some or no experience with patient registries.

Modeling Methods

Bayesian Methods in Economic Evaluations
Faculty: Keith R. Abrams PhD, Professor of Medical Statistics, Centre for Biostatistics & Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, U.K.
Course Description: This course is designed to provide an overview of the Bayesian approach and its application to health economics and outcomes research. The course will cover basic elements of  Bayesian statistics, discuss differences between Bayesian and classical (frequentist) approaches, and demonstrate how to apply the Bayesian approach to clinical trials and cost-effectiveness analyses. Available software will be discussed, and examples of studies will be presented. This course is for those with a basic appreciation of statistics and probability.

Utility Measurements (Preference-Based Techniques)
Faculty: Jan Busschbach PhD, Associated Professor, Department for Medical Psychology and Psychotherapy at Erasmus Medical Center, Rotterdam, The Netherlands & Viersprong Institute for Studies on Personality Disorders, Halsteren, The Netherlands; Elly Stolk MSc, Institute for Medical Technology Assessment ((iMTA), Erasmus University Medical Center Rotterdam, The Netherlands
Course Description: Utility measurement is a method of determining an individual's preference for a certain outcome represented by a quantitative score (utility) .During this course, methods for measuring preference-based outcomes like the standard gamble, time trade-off, and visual analogue scale will be demonstrated. Utility measurement however is not only about mastering these techniques; it is about using them in such a way that health care decision-makers can apply the results, for instance in QALY-analyses. For this purpose, one needs to be aware of shortcomings of  the available utility measures and potential solutions. Furthermore one should be aware of  the decision-making context and the way results are interpreted. To equip participants with expertise in the field of utility measurement, the most important issues will be discussed: for instance we will consider potential insensitivity of generic instruments for particular disease specific problems, and discuss to what extent adaptation of generic or disease-specific quality of life instruments may offer a solution. This will be demonstrated with an exercise. Also the issue of  "whose values count: patient values or values from the general public?" will be discussed. Finally we turn to the interpretation in the context of resource allocation. This course is for those with some experience with quality-of-life measures in health economic evaluation.

Instrument Development & Evaluation for Patient-Reported Outcomes Assessment
Faculty: Andrew Lloyd M. Phil, Director, Oxford Outcomes, West Way, Botley, Oxford, UK; Patricia van Hanswijck de Jonge PhD, MSc; Senior Research Associate, Health Care Analytics Group, United BioSource Corporation, London, UK
Course Description: Patient reported outcomes are widely used to evaluate the impact of health technologies, practice innovations or changes in health policy from the patients’ perspective. This course is designed to familiarise people with the range and scope of what PROs are used for; how they are developed and evaluated, and how PRO data can be used to support licensing and reimbursement applications. The course content will describe the scope and range of what patient reported outcomes measure. This includes generic and disease specific measures of health related quality of life (HRQL), as well as measures of patient preference, utility, treatment satisfaction and measures of work productivity. We will describe the steps that researchers generally go through in order to develop and test a new PRO. This will include qualitative work, item development and testing and then validation studies. Finally in the last hour we will frame this in terms of what the FDA and EMEA expect to see when PROs form an important part of a licensing submission. In addition, we will describe the approach of bodies such as NICE and how they review PRO data and use it to guide reimbursement decisions. This is an entry level course which assumes only a passing familiarity with patient reported outcomes.

Cost Estimation and Assessing Financial (Budget) Impact of New Health Care Technologies
Faculty: Josephine Mauskopf PhD, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA; C. Daniel Mullins PhD, Professor and Chair of Pharmaceutical Health Services Research, University of Maryland, School of Pharmacy, Baltimore, MD, USA
Course Description: This course will describe methods to determine the costs associated with a health condition and the budget impact of new technologies for that condition. The course will present incidence and prevalence based costing strategies. Treatment algorithms and event-based approaches will be demonstrated for disease-specific costs from different decision-maker perspectives. Both static and dynamic methods for estimating the budget impact of adding a new drug to a health plan formulary will be presented. Issues related to imputing missing data will also be discussed. This course is designed for those with some experience with pharmacoeconomic analysis.