Short Courses: Sunday, May 15

8:00AM-5:00PM	FULL DAY COURSES
8:00AM-5:00PM Room: Delaware A	Modeling Modeling: Structure & Design of Model - Full Day Course (8:00am-5:00pm) Faculty: Marc Botteman MA, Managing Partner, PharMerit North America, Bethesda, MD, USA; Ben van Hout PhD, Scientific Director, PharMerit, Rotterdam, The Netherlands and Professor in Medical Technology Assessment, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands; Bart Heeg MSc, Consultant, PharMerit, Rotterdam, The Netherlands; Joel Hay PhD, Associate Professor, USC School of Pharmacy, Los Angeles, CA, USA Course description: We will first provide a review of Markov models, discrete event models, and other modeling techniques and their appropriate use, in light of the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health Care Evaluations. Using a series of related examples, the course will carefully review the practical steps involved in developing and using these kinds of models.Examples will be presented using predominantly Microsoft Excel, supplemented with add on simulation software. The goal of the course is to provide an in depth understanding of the simple yet powerful mathematical underpinnings of each of these methods using a relatively transparent tool rather than to teach a new programming language. The second section of this course will cover in details 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). The ISPOR Principles of Good Practice will again be reviewed and discussed in this context. These will include in particular data identification, data modeling, and data incorporation considerations.Issues related to the selection of model input parameters and their distributions for use in probabilistic sensitivity analyses will be considered. Participants will learn the steps required conducting, analyzing, interpreting, and presenting results from probabilistic sensitivity analyses (e.g. using analyses of the cost-effectiveness plane, the "ellipses", and acceptability curves). An introduction to the expected value of perfect information [EVPI] will be provided in the context of the use of probabilistic sensitivity analyses. The above concepts will be illustrated with a series of related examples using Microsoft Excel. Publications from healthcare journals presenting additional examples and theoretical considerations will be provided as a course supplement. This intermediate course requires basic understanding of decision analysis. The course will be conducted more as a seminar, rather than as a hands-on modeling workshop. However, we encourage participants to bring their own laptop computers (with a CD ROM drive and Microsoft Excel) to facilitate the use of the examples and add-on software demo that will be provided. Additionally, we encourage early course registration to allow for early distribution of the examples and add-on software. This intermediate course requires basic understanding of decision analysis. ..........................................................................................................................................
8:00AM-5:00PM Room: Delaware B	Clinical Assessment Retrospective Database Analysis: Econometric Methods - Full Day Course (8:00am-5:00pm) Faculty: William H. Crown PhD, i3 Magnifi, Auburndale, MA, USA; Henry Henk PhD, i3 Magnifi, Eden Prairie, MN, USA Course Description: Large administrative claims databases provide a unique opportunity to examine retrospectively the effects of drug use on clinical and economic outcomes in "real world" settings. The morning session of this full-day course will cover selected topics related to estimators and sampling distributions, properties of sampling distributions (unbiasedness, efficiency, mean square error), and ordinary least squares (OLS) regression. OLS model assumptions and the implications of violations (e.g., heteroscedasticity, multicollinearity, autocorrelation) will also be discussed. The afternoon session will deal with more complex topics beginning with the problem of endogeneity, identification, instrumental variables, sample selection models, and propensity score models. Finally, we will turn our attention to maximum likelihood methods and the estimation of limited dependent variables models including logit, multinomial logit, count models, and survival models. Many of the topics will be illustrated with examples based upon claims data from a large national health plan. Others will be drawn from published retrospective database studies. This course will assume participants have knowledge of statistical methods through OLS regression and experience in the analysis of administrative claims databases.
8:00AM-12:00PM	MORNING COURSES
8:00AM-12:00PM Room: Marriott Ballroom Balcony B	Pharmacoeconomics Elements of Pharmaceutical Pricing - Morning Courses (8:00am-12:00pm) Faculty: Jack Mycka, President, Optimar Strategic Consulting LLC, Montclair, NJ, USA; Renato Dellamano PhD, President, ValueVector (Value Added Business Strategies), Milan, Italy Course Description: This course is designed to cover the elements of pharmaceutical pricing decisions. It will cover the issues, information and processes employed, the role of pharmacoeconomics and the differences in payment systems that help to shape pricing decisions. This course will be interactive and is designed for those with some experience in either pharmacoeconomics, pharmaceutical pricing or marketing. ..........................................................................................................................................
8:00AM-12:00PM Room: Maryland A	Economic Analysis Cost Estimation: Finding and Extracting Cost Data - Morning Courses (8:00am-12:00pm) Faculty: Judith A. O'Brien RN, BSPA, Vice President, Director of Cost Development Research, Caro Research Institute, Concord, MA, USA Course Description: This course will focus on practical aspects of cost development for pharmacoeconomic studies. The objective is to help the participant bridge the gap between understanding pharmacoeconomic theory and the practice of developing cost estimates. Factors to consider when costing pharmacoeconomic analyses, such as perspective, data sources, data classification systems, developing resource use profiles, obtaining unit costs, and making cost adjustments will be presented. Examples of issues encountered when identifying and extracting cost data will be discussed. This course is designed for those with some experience with pharmacoeconomic analysis. ..........................................................................................................................................
8:00AM-12:00PM Room: Maryland B	Quality of Life / Patient-reported Outcomes Old and New Utility Measures in Health Economics and Outcomes Research - Morning Courses (8:00am-12:00pm) Faculty: F. Reed Johnson PhD, Senior Fellow, RTI Health Solutions, Research Triangle Park, NC, USA; A. Brett Hauber PhD, Senior Economist, RTI Health Solutions, Research Triangle Park, NC, USA Course Description: Course participants will learn the conceptual and empirical features of various health-utility measures and their relative advantages for different health care decisions. Health utility measures are often outcomes of interest in their own right. In addition, cost-utility analysis (CUA) and cost-benefit analysis (CBA) are often used to evaluate new health care technologies. Both CUA and CBA are useful for informing decision makers about the relative benefits of an intervention to individual patients and to society as a whole. There are different approaches to estimating benefit measures for comparison with treatment costs. CUA employs health-state utilities based on cardinal utility theory to define quality-adjusted life years (QALYs) for different health states. In contrast, CBA estimates take the form of ordinal utility values expressed as money-equivalent values (often called willingness to pay). This course evaluates new methods for bridging the gap between ordinal and cardinal utility measures. Newer methods allow analysts to estimate �super QALY� values using time or other non-monetary tradeoffs that do not require the restrictive assumptions of conventional cardinal-utility methods. The course focuses particularly on how to derive utility estimates from CA surveys, including developing valid and reliable tradeoff surveys and analyzing the resulting data. This course is designed for those with some experience with psychometric measures. ..........................................................................................................................................
8:00AM-12:00PM Room: Maryland C	Clinical Assessment Meta-Analysis And Systematic Literature Review - Morning Course (8:00am-12:00pm) Faculty: Joseph C. Cappelleri PhD, Senior Associate Director, Pfizer Inc, Groton, CT, USA Course Description: Meta-analysis may be defined as the statistical analysis of data from multiple studies for the purpose of synthesizing and summarizing results, as well as for quantitatively evaluating sources of heterogeneity and bias. A systematic literature review often includes meta-analysis and involves an explicit, detailed description of how a review was conducted. This course highlights and expounds upon four key areas: 1) impetus for meta-analysis and systematic reviews, 2) basic steps to perform a quantitative systematic review, 3) statistical methods of combining data, and 4) appraisal and use of meta-analytic reports. The material is motivated via applications in pharmacoeconomics, outcomes research, and clinical studies from the published literature and hypothetical examples. Interactive exercises are part of the course. This course is designed for those with little experience with meta-analysis.
1:00PM-5:00PM	AFTERNOON COURSES
1:00PM-5:00PM Room: Maryland B	Economic Analysis Statistical Considerations In Economic Evaluations - Afternoon Course (1:00pm-5:00pm) Faculty: Henry Glick PhD, University of Pennsylvania, School of Medicine, Philadelphia, PA, USA; Jalpa Doshi PhD, University of Pennsylvania, School of Medicine, Philadelphia, PA, USA; Daniel Polsky PhD, University of Pennsylvania, School of Medicine, Philadelphia, PA, USA Course Description: The adoption and diffusion of new medical treatments depend increasingly on evidence of costs and cost effectiveness. This evidence is increasingly being generated from patient level data in randomized study designs. This course will discuss design and analysis issues that arise when conducting such analyses. Specifically, we will address topics on strategic issues in the design of economic assessments, sample size and power calculations, analysis of costs and how it is affected by distributional assumptions, and assessing stochastic uncertainty. The course will be practical in orientation and will routinely provide examples to illustrate the "how-to's". This course is an introductory/intermediate level. Familiarity with economics and statistics will be helpful. ..........................................................................................................................................
1:00PM-5:00PM Room: Maryland A	Quality of Life/Patient-reported Outcomes Advanced Quantitative Methods for Quality of Life/Patient-reported Outcomes Research - Afternoon Course (1:00pm-5:00pm) Faculty: John Ware PhD, CEO & Chief Science Officer, Quality Metric Incorporated, Lincoln, RI, USA; Jakob B. Bjorner, MD, PhD, Deputy Chief Science Officer, Quality Metric Incorporated, Lincoln, RI, USA Course Description: This course will describe classical test theory, item response theory [theory and models used with modern� psychometric methods], computer-adaptive testing and analysis. Combining multiple measures and scales and multiple measurement error [effect-indicator and cause-indicator models], reliability and latent variable analysis (exploratory factor analysis, principal components analysis, principal factor analysis, and confirmatory factor analysis) will be described. This course is designed for those with experience with psychometric measures. ..........................................................................................................................................
1:00PM-5:00PM Room: Maryland C	Modeling Discrete Event Simulation for Economic Analyses - Afternoon Course (1:00pm-5:00pm) Faculty: J.Jaime Caro MDCM, FCRPC, FACP, Adjunct Professor of Medicine, Adjunct Professor of Epidemiology and Biostatistics, McGill University, Montreal PQ and Scientific Director, Caro Research Institute, Concord, MA, USA; J�rgen M�ller MSc Mech Eng, Simulation Specialist, Caro Research Institute, 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. Participants who wish to have hands-on experience should bring their laptops. Instructors will distribute training versions of Arena. After the course the participants should understand how to interpret the results of a DES and have an understanding of simulation as a tool - how, where and when to use it. The participants should also be able to map simple dynamic processes in ARENA and build simple models.