Sunday, May 21, 2000

Pre-Meeting Training Courses (@ 4 hours)

Morning Session (8 AM - 12 PM)

Decision Analysis - Introduction
Faculty: Mark S. Roberts, MD, MPP, FACP Assistant Professor of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Dr. Roberts is a general internist with substantial formal and practical training in quantitative methods, decision sciences, economics and cost-effectiveness analysis.

Course Description: Decision analysis is a tool that allows explicit structure for solving complicated health care problems. The most difficult part of developing models is finding the appropriate level of detail to address the particular problem being investigated. The design of decision trees, calculation of expected utilities, sensitivity analysis, assessment of patient values, and inclusion of quality-of-life parameters would be discussed. This course is designed for those with little experience in decision analysis.

Quality-of-Life Assessment Fundamentals
Faculty: Pennifer Erickson PhD, Co-founder O.L.G.A (On-Line Guide to Quality-of-Life Assessment), State College, PA, USA. Dr. Erickson has numerous publications and books on health-related quality-of-life assessment.

Course Description: Conceptual, methodological, and practical methods for measuring quality-of-life will be presented. 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 course is designed for those with little experience in health-related quality-of-life research.

Measuring Utilities and Willingness-to-Pay
Faculty: Lieven Annemans PhD, MMan, Director, Health Economics & Disease Management, Mechelen, Belgium.

Course Description: Three instruments commonly used in obtaining utility values for health state in cost-utility analysis are: rating scales, standard gamble, and time trade-off. These instruments including examples of their use will be discussed and compared. Willingness-to-pay is a common instrument used to measure monetary value for health benefits in cost-benefit analysis. Theoretical considerations, who to ask (patient or general population), and interpretation of results will be discussed. This course is designed for those with little experience in utility and willingness-to-pay measurements.

Statistical Considerations in Pharmacoeconomic Evaluations
Faculty: Joseph F. Heyse PhD, Executive Director and John Cook PhD, Director, Biostatistics & Research Data Systems, Merck Research Laboratories, Blue Bell, PA, USA. Dr. Heyse and Dr. Cook collectively have over 25 years of experience providing statistical support to economic evaluations of pharmaceutical and vaccine products and have numerous publications in the area.

Course Description: This course will provide an overview of the terminology, family of technologies, and key methodological features of pharmacoeconomic evaluations. The primary focus will be on the statistical considerations of planning & analyzing studies, and interpreting the results including comparisons of types of analyses used and discuss important study design features for both clinical-economic trials and modeling studies based on available epidemiological and clinical data. Methods of statistical analysis for cost data and for estimating cost-effectiveness ratios will be thoroughly reviewed, making extensive use of real-life examples and published studies. This course is designed for researchers with experience in conducting pharmacoeconomic studies.

Afternoon Session (1 - 5 PM)

Decision Analysis - Advanced
Faculty: Donald B. Chalfin, MD, MS, FCCM, Director, Surgical ICU and Section of Surgical Critical Care and Associate Professor of Medicine, Albert Einstein College of Medicine, New York City, NY, USA. Dr. Chalfin is a critical care physician with substantial training and experience in decision analysis, cost-effectiveness analysis, artificial intelligence, and related simulation and modeling techniques.

Course Description: Complex models and techniques, including Monte Carlo simulations, Markov models, Bayesian analysis, and DEALE (declining exponential approximation of life expectancy) will be discussed. How these techniques are used in health care decision-making will be emphasized. This course is a continuation of Decision Analysis - Introduction (morning session course).

Quality-of-Life Data Analysis
Faculty: Paul Kind PhD, Senior Research Fellow, Centre for Health Economics, University of York, York, UK. Course Description: Quality-of-life measurements in clinical studies will be discussed. Choosing the appropriate measurement instrument, sample size, statistical test, missing data, test repeat, psychometric reporting protocol, and analysis and interpretation of data will be examined. A panel critique of several published studies will be presented. This course is designed for those with experience in quality-of-life research.

Retrospective Database Analysis
Faculty: David Thompson, PhD, Managing Director, Lisa McGarry, MPH, Project Manager, Innovus Research Inc., Medford, MA, USA

Course Description: Current research methods in retrospective database studies will be profiled. The course will provide an historical background and discussion of strengths and limitations. Techniques of quasi-experimental design as they relate to drug-drug comparisons, case-control studies, and longitudinal analyses of treatment patterns will be highlighted. Commonly encountered threats to the internal and external validity of such studies will be examined. Special emphasis will be on selection bias in database analyses. The course is designed for researchers with some experience with retrospective database analysis.

Measuring Productivity
Faculty: Paul Stang1 PhD, Ron Kessler2 PhD, Wendy Lynch3 PhD, and Laurie Burke4 RPh, MPH, 1Professor, Executive VP, Galt Associates Inc, Blue Bell, PA, USA, 2Professor, Department of Health Care Policy, Harvard University Medical School, Boston, MA, USA, 3Senior Consultants, Health Management, William Mercer and Company, 4Chief, US FDA DDMAC, Rockville, MD, USA.

Course Description: Intervention, observational and retrospective productivity studies will be discussed. Measurement issues including linking available data, role of assumptions and models, using job classification information, self-report vs. objective measurement will be examined. The issues and needs of the corporate benefit managers, FDA and other users of productivity measurements will be explored including examples of studies. This course is designed for researchers with some experience in measuring productivity.