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SUNDAY, MAY 20, 2007 8:00 AM - 12:00 PM (Morning
Courses)
Pharmacoeconomic / Economic Methods
Cost-Effectiveness Analysis with Clinical Trials
Faculty: Scott Ramsey MD, PhD, Full Member and Professor, Fred Hutchinson Cancer Research Center, Seattle, WA, USA;
Richard Willke PhD, Senior Director, Group Leader, Global Outcome Research, Worldwide Outcomes Research, US Development Sites Pfizer, Inc., Bridgewater, 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.
Real World Data Methods
Use of Real World Data in Outcomes Research Faculty: Diana Brixner PhD, RPh, Associate Professor and Department Chair, College of Pharmacy, University of Utah, Salt Lake City, UT;
Gregory de Lissovoy PhD, MPH, Senior Research Scientist, Center for Health Economics and Policy, United BioSource Corporation, Bethesda, MD,USA;
Daniel M. Huse MA, Practice Leader, Information Products, Thomson Medstat Inc., Cambridge, MA
Course Description: ‘Real world’ data is defined as information (data) collected beyond that which is normally collected in Phase III clinical trials that focus on efficacy. This course will address the issues and framework for analysis of ‘real world’ data in outcomes research. The types of ‘real world’ data (piggy-back information from Phase III clinical trials, large simple trials, registries, administrative claims databases, surveys) and benefits and challenges of these data, as well as evidence hierarchies and their usefulness will be discussed. Examples of the use of ‘real world’ data for different types of outcomes (clinical outcomes, economic outcomes, and quality of life / patient-reported outcomes) will be presented. Health care payer’s perspectives will also be addressed.
This course is designed for those with little experience with ‘real world’ data assessment and use in health care decisions.
Modeling Methods
Bayesian Analysis: Advanced Faculty:
Bryan Luce MBA, PhD, Senior Vice President,
Science Policy, United BioSource Corporation, Bethesda,
MD, USA; Keith R. Abrams PhD, Department of
Health Sciences, University of Leicester, England, U.K.;
Christopher S. Hollenbeak PhD, Surgery and Health
Evaluation Sciences, Penn State College of Medicine,
Hershey, PA, USA; David Vanness PhD, Assistant
Professor of Population Health Sciences, University of
Wisconsin Medical School, Madison, WI, USACourse Description: This course introduces the use of Bayesian methods in evidence synthesis (including meta-analysis) and allows participants to gain hands on experience using such modeling techniques within WinBUGS. Methodological issues considered in the course include; fixed & random effects models, choice of prior distributions, subgroups, meta-regression and adjusting for baseline risk, together with indirect and mixed treatment comparisons. Further meta-analysis topics for which a Bayesian approach can be of benefit will also be highlighted.
Participants will be expected to be familiar with the use of WinBUGS and will be responsible for bringing a laptop with the latest, unrestricted version of WinBUGS pre-installed [Details at
www.mrc-bsu.cam.ac.uk/bugs ].
This course is a follow-up to the courses: Bayesian Analysis-Overview and Bayesian Analysis-Applications. Basic knowledge of Bayesian approach and use of WinBUGS (equivalent to attendance at Bayesian Analysis-Applications) will be assumed.
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 Scientific Director, Caro Research Institute, Concord, MA, USA;
Jörgen Möller 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.
This course is designed for those with some experience with modeling.
Quality of Life / Patient-Reported Outcomes
/Preference-Based Methods
Patient-Reported Outcomes - Item Response Theory Faculty:
Bryce Reeve PhD, Psychometrician, National Cancer Institute, Bethesda, MD, USA
Course Description: : There is a great need in health outcomes research to develop instruments that accurately measure a person's health status with minimal response burden. This need for psychometrically sound and clinically meaningful measures calls for better analytical tools beyond the methods available from traditional measurement theory. Applications of item response theory (IRT) modeling have increased considerably because of its utility for instrument development and evaluation, assessment of measurement equivalence, instrument linking, and computerized adaptive testing. IRT models the relationship, in probabilistic terms, between a person's response to a survey question and their standing on a health construct such as fatigue or depression. This information allows instrument developers to develop reliable and efficient quality of life measures tailored for an individual or group. This introductory workshop will discuss the basics of IRT models and applications of these models to improve health outcomes measurement. Illustrations will be used throughout the presentation that focuses on measuring key health-related quality of life domains in different disease populations.
This introductory course is designed for those with none to little experience with IRT.
Use of Pharmacoeconomics / Economic /
Outcomes Research Information
Case Studies in Pharmaceutical/Biotech Pricing II – Advanced Faculty:
Jack M. Mycka, President & Partner, MME LLC, Montclair, NJ, USA;
Renato Dellamano PhD, President, ValueVector, s.r.l. (Value Added Business Strategies), Milan, Italy. Course Description: Case studies will be employed to lead participants through the key steps of new product pricing, with focus on the need to thoroughly analyze the business environment and its constraints and opportunities and the need to closely integrate the pricing, reimbursement and PE strategy for the new product with the clinical development and marketing strategies. Practical exercises will allow participants to consolidate the concepts delivered in the “Elements” introductory session and expanded here. Areas covered will include the post-launch issues of reimbursement and pricing maintenance as a part of life-cycle management in a global environment. This course is for individuals who have completed Elements of Pharmaceutical Pricing I – Introduction or are familiar with both the key determinants of pharmaceutical pricing and the main international health systems. Enrollment for this course is limited.
SUNDAY, MAY 20, 2007 1:00 PM - 5:00 PM (Afternoon
Courses)
Pharmacoeconomic / Economic Methods
Statistical Considerations in Economic Evaluations Faculty: Henry Glick PhD, Health Economist, University of Pennsylvania, Division of Internal Med, Philadelphia, PA, USA; Jalpa Doshi PhD, Research Assistant & Professor of Medicine, University of Pennsylvania, School of Medicine, Philadelphia, PA, USA; Daniel Polsky PhD, Research Associate & Professor, 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.
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; Jingshu Wang PhD, Post-doctorate fellow, Center on Drugs and Public Policy, University of Maryland School of Pharmacy, 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 is an introductory course, designed for those with little experience with this methodology but some knowledge of observational databases.
Patient Registries: Overview & Application Faculty:
Jeff Trotter MBA, President, Ovation Research 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.
Quality of Life / Patient-Reported Outcomes
/Preference-Based Methods
Utility Measures Faculty: F. Reed Johnson PhD, Senior Fellow and Principal Economist, RTI Health Solutions, Research Triangle Park, NC, USA;
A. Brett Hauber PhD, Head, Health Preference Assessment,
Senior Economist, Health Economics
, 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 uses for informing health-care decision making. Cost-utility analysis (CUA), risk-benefit analysis (RBA), and cost-benefit analysis (CBA) are often used to evaluate new health-care technologies. These methods are useful for informing decision makers about the relative benefits of an intervention to individual patients and to society as a whole. CUA employs health-state utilities based on cardinal utility theory to define quality-adjusted life years (QALYs) for different health states. RBA employs utility measures to place both risks and benefits in comparable units. CBA estimates take the form of ordinal utility values expressed as money-equivalent values (often called willingness to pay). This course will review the theory and application of utility estimation in health economics and risk-benefit analysis.
Outcomes Research
Outcomes Research for Medical Devices & Diagnostics Faculty:
Seema Sonnad PhD, Associate Professor, Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA;
Stacey Ackerman, MSE, PhD, Vice President, Covance Market Access Services, San Diego, CA, USA; Jason Lerner MBA, Principal, Covance Market Access Services Inc., Gaithersburg, MD, USA
Course Description: This course will present outcomes research practices that are specifically tailored for the fast-paced medical device and diagnostics technology environment and address issues related to these health technology assessment methodologies. Outcomes research including clinical outcomes, economic outcomes, and patient-reported outcomes will be discussed. Outcomes research for medical devices & diagnostics will be differentiated from other health care interventions such as drugs. The evidence hierarchy for medical devices and diagnostic procedures including ‘real world’ outcomes research information in coverage and reimbursement decisions will be discussed.
This course is designed for those with little experience with outcomes research for medical devices and diagnostic technologies.
Use of Pharmacoeconomics / Economic / Outcomes
Research Information
Introduction to Risk/Benefit Management in Health Care
Faculty: Dennis W. Raisch, PhD, Associate Center Director, Scientific Affairs, VA Cooperative Studies Program, Clinical Research Pharmacy, Albuquerque, NM,
Anthony Lockett, MD, PhD, MBA, Medical Director, ICO, Leeds, United Kingdom;
Suellen Curkendall, PhD, Principal Investigator, Cerner Health Insights, Vienna, VA
Course Description: This course will provide an overview of risk/benefit management for pharmaceuticals and devices. The risk/benefit assessment process will be described in regards to stage of product development, from pre-marketing through post-marketing. Risk mitigation includes the various strategies employed by manufacturers, regulators, and health care providers, with an emphasis on international differences in risk mitigation and decision making. Risk/benefit communication processes will be described, focusing upon how decisions regarding risks and benefits of pharmaceuticals and devices are communicated to health care providers and the public. This includes direct mailing, direct-to-consumer marketing, and labeling. Real-world exercises will allow participants to discuss key topics and propose implementation strategies for risk management.
This course is designed for those with a basic understanding of pharmacoepidemiology principles.
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