SHORT COURSES - SATURDAY MAY 15, 2010
 

SHORT COURSES - SATURDAY, MAY 15, 2010
Short Course Program Overview Short Courses Saturday, May 15 Short Courses Sunday, May 16
SATURDAY, MAY 15 (All Day Courses)
8:00 AM - 5:00 PM

Pharmacoeconomic / Economic Methods

Introduction to Pharmacoeconomics
Faculty: Lorne Basskin PharmD, National Director of Pharmacy, HealthSouth Corporation, Cooper City, FL, USA
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.

Real World Data Methods

Retrospective Database Analysis
Faculty: William H. Crown PhD, President, i3 Innovus, Waltham, MA, USA; Onur Baser MS, PhD, President, STATinMED Research, Director of Analytic Group, M-SCORE, and Assistant Professor of Surgery, Department of Surgery, University of Michigan, Ann Arbor, MI, USA; Henry Henk PhD, Director, i3 Innovus, 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. This course will cover a discussion of the ISPOR Checklist for Retrospective 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. OLS model assumptions and the implications of violations (e.g., heteroscedasticity, multicollinearity, autocorrelation) will also be discussed. 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. This course will assume participants have knowledge of statistical methods through OLS regression and experience in the analysis of administrative claims databases.

Modeling Methods

Bayesian Analysis: Overview and Applications
Faculty: David Vanness PhD, Research Scientist, Center for Health Economics and Science Policy, United BioSource Corporation, Bethesda, MD, USA and Assistant Professor, University of Wisconsin School of Medicine and Public Health (on leave), Madison, WI, USA; Christopher S. Hollenbeak PhD, Associate Professor, Surgery and Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
Course Description: The first portion of this course is designed to provide an overview of the Bayesian approach and its applications to health economics and outcomes research. The course will cover basic elements of Bayesian statistics, contrasting briefly with classical (frequentist) statistics and introduce available statistical packages.  The second part of the course is a "hands-on" workshop where participants will be led through live examples using the free Markov Chain Monte Carlo package WinBUGS.  Attendees will have the chance to apply the principles they have learned in part one to challenging data analysis problems, including the use of Bayesian generalized linear models (GLM) to analyze cost and outcomes data.  This course is designed for those with a limited understanding of Bayesian statistical concepts or for those who want a refresher and more practical experience.

SATURDAY, MAY 15 (Morning Courses)
8:00 AM - 12:00 PM

Use of Pharmacoeconomics / Economic / Outcomes Research Information

Elements of Pharmaceutical/Biotech Pricing I Introduction
Faculty: Jack M. Mycka, Global President  & CEO, MME LLC, Montclair, NJ, USA; Renato Dellamano PhD, President, MME Europe and 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.

Modeling Methods

Introduction to Modeling (Introduction to Decision Analysis)
Faculty: Mark S. Roberts MD, MPP, Professor and Chair, Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA
Course Description: Decision analysis is a tool that uses an explicit, quantitative structure to describe and analyze complex health care decisions. This course will provide an introduction to the principles and practice of decision analysis. Upon completion of the course, participants will be able to evaluate the appropriateness of decision analysis in different settings, construct simple decision trees, understand the basic mechanics of tree evaluation and sensitivity analysis, and acquire skill in the interpretation of a published decision analysis. Extension of basic techniques, such as cost-effectiveness analysis and the assessment of patient preferences will be briefly discussed. Class exercises will be used to illustrate these principles. This course is suitable for those with little experience with decision analysis

Pharmacoeconomic / Economic Methods

Cost-Effectiveness Analysis alongside Clinical Trials
Faculty: Scott D. Ramsey MD, PhD, Member and 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 J. 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, characterization of uncertainty, and standards for reporting results will be presented. This is an introductory/intermediate level course. Familiarity with economic evaluations will be helpful.

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

New! Introduction to Patient-Reported Outcomes
Faculty: Andreas M. Pleil PhD, Senior Director, Ophthalmology/Endocrinology Outcomes Research Lead, Clinical Development and Medical Affairs, Specialty Care Business Unit, Pfizer Inc, San Diego, CA, USA; Charles Petrie PhD, Head of Outcomes Research for Specialty Care, Pfizer Inc, New London, CT, USA;Joseph C. Cappelleri PhD, MPH, Senior Director, Pfizer Inc., New London, CT, USA; Tara Symonds PhD, Head, PRO Centre of Excellence, Primary Care Business Unit, Pfizer Ltd., Kent, UK
Course Description: Conceptual, methodological, and practical methods for measuring quality of life, health status and other types of health outcomes will be presented. Theoretical frameworks, reliability, validity, responsiveness, methods of administration, respondent and administrative burdens, and issues of analysis and interpretation will be discussed using examples drawn from specific quality-of-life instruments and their applications. A model of selecting appropriate instruments from the many existing generic and disease-specific instruments will be presented.  This is an introductory course intended for those with little experience with these methodologies.

SATURDAY, MAY 15 (Afternoon Courses)
1:00 PM - 5:00 PM

Pharmacoeconomic / Economic Methods

Financial Impact / Cost of Illness
Faculty: Josephine Mauskopf PhD, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA; C. Daniel Mullins PhD, Professor and Chair, 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.

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

New! Introduction to Conjoint Analysis
Faculty: A. Brett Hauber PhD, Global Head, Health Preference Assessment, RTI Health Solutions, Research Triangle Park, NC, USA; John F P Bridges PhD, Assistant Professor, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD,USA
Course Description: Course participants will learn the conceptual and empirical basis for using conjoint analysis to elicit preferences in outcomes research.  The course will introduce participants to both the conceptual basis for quantifying decision-maker preferences for medical interventions and the practical design and analytical issues that must be addressed in order to obtain valid empirical preference estimates.  The course will be structured following the good research practice guidelines and discussion being prepared by the ISPOR Good Research Practices for the Application of Conjoint Analysis in Health Task Force. The course will include lectures and interactive group exercises and group discussion.  This course is designed for clinicians, policy makers, researchers, patient advocates/researchers with little or no knowledge of conjoint analysis or other stated-preference methods.

Advanced Patient-Reported Outcomes Assessment: Psychometric Methods
Faculty: Bruce Crawford MPH, MA, General Manager, Asia, Mapi Values, Tokyo, Japan; Kathleen Rosa MS, PhD, Director, Psychometrics and Statistics, Mapi Values, Boston, MA, USA
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.

Modeling Methods

Modeling: Design and Structure of a Model
Faculty: Marc Botteman MA, MSc, Managing Partner and Director of Health Economics, PharMerit North America LLC, Bethesda, MD, USA; Ben van Hout PhD, Scientific Director, PharMerit, Rotterdam, The Netherlands & Professor in Medical Technology Assessment, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands; Maarten Treur MSc, Senior Research Consultant, Pharmerit, Rotterdam, The Netherlands
Course Description: This course will include a review of modeling techniques (Markov models and Monte Carlo techniques) including a discussion of the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health Care Evaluations. Markov models and first and second order Monte Carlo simulations including data identification, data modeling, and data incorporation will be demonstrated. Using a series of examples, the course will carefully review the practical steps involved in developing and using these kinds of models. Examples will be presented using Microsoft Excel, supplemented with add on simulation software. This course will cover the practical steps involved in the selection of models and options in modeling of data inputs. Participants who wish to have hands-on experience should bring their laptops.  Participants should have a basic understanding of decision analysis.  Participation in the short course Introduction to Decision Analysis (or equivalent knowledge) is recommended.

Real World Data Methods

Instrumental Variables in Addressing Selection Bias in Observational Studies
Faculty: Benjamin M. Craig PhD, Assistant Professor, Oncologic Sciences and Economics, University of South Florida & Assistant Member, Moffitt Cancer Center, Tampa, FL, USA; Antoine C. El Khoury PhD, MS, Manager, Global Health Outcomes Department, Merck & Co Inc., West Point, PA, USA, & Adjunct Assistant Professor, Division of Pharmaceutical Evaluation and Policy, University of Arkansas for Medical Sciences College of Pharmacy, Little Rock, AR, USA; Bradley C. Martin PhD, RPh, PharmD, Professor and Head, Division of Pharmaceutical Evaluation and Policy, University of Arkansas for Medical Sciences College of Pharmacy, Little Rock, AR, USA
Course Description: In any non-randomized study, selection bias is a potential threat to the validity of conclusions reached.  Failure to account for sample selection bias can lead to conclusions about treatment effectiveness or treatment cost that are not really due to the treatment at all, but rather to the unobserved factors that are correlated with both treatment and outcomes.  Sample selection models provide a test for the presence of selection bias.  These models also provide a correction for selection bias, enabling an investigator to obtain unbiased estimates of treatment effects.  This course will discuss the various models and their applications, and in particular will address instrument variables (two-stage least squares, intuition, RCTs), including an overview of examples from the current literature.  Participants will benefit from interactive exercises using instrumental variables and sample selection techniques using STATA.  (For those who have STATA loaded on their laptops, you are encouraged to bring your laptop).  This course is suitable for those with some knowledge of econometrics.