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May 16-19, 2004, Crystal Gateway Marriott, Arlington, VA
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PRE-MEETING SHORT COURSES |
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Sunday, May 16:
Full Day Courses (8:00am-5:00PM) |
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Clinical Assessment |
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Retrospective Database Analysis: Data sources
and Methods (full-day course)
Faculty: Lisa Stockwell-Morris
PhD, RPh, IMS Health, Plymouth Meeting, PA, USA;
William H. Crown PhD, Ingenix Pharmaceutical Services,
Auburndale, MA, 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 examine the
characteristics of retrospective databases and the statistical issues,
which necessitates the use of multivariate methods. The ISPOR Checklist
for Retrospective Database Studies, a useful tool for assessing as well
as conducting retrospective studies will be discussed. This course will
focus on concepts and examples. This course will describe analytical
approaches such as OLS, logistic, and Poisson regression, survival
analysis, and the Kaplan-Meier Sample Average (KMSA) method. Also
discussed will be the use of propensity scores, instrumental variables,
and nonparametric bootstrapping, as well as methods for selection of
model covariates and testing of model assumptions. Examples of published
retrospective database studies will be discussed. This course will
assume participants have knowledge of statistical methods and/or
econometrics and experience in the analysis of administrative claims
databases.
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May 16: Morning Courses (8:00am-12:00PM) |
| Quality of Life / Patient-reported Outcomes
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Advanced Quantitative Methods for Quality of
Life / Patient-reported Outcomes Research
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.
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Modeling |
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Bayesian Analysis : Overview
Faculty: Bryan Luce MBA, PhD, Senior
Research Leader & CEO, MEDTAP International, Bethesda, MD, USA;
Christopher S. Hollenbeak PhD, Surgery and Health Evaluation Sciences,
Penn State College of Medicine, Hershey, PA, USA; Elisabeth Fenwick PhD,
Lecturer, Department of Economics and Related Studies, University of
York, York, UK
Course Description: 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. This course is designed for those with a limited
understanding of Bayesian statistical concepts.
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Economic Analysis |
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Introduction to
Probabilistic Cost-Effectiveness Modeling
Faculty: Andrew Briggs Dphil, Professor, Health Economics Research
Centre, University of Oxford, Institute of Health Sciences Headington,
Oxford, UK; Mark Sculpher MSc, PhD, Professor, University of York,
Centre for Health Economics, Heslington, York, UK
Course Description:
This course will introduce the participant to the construction of
probabilistic cost-effectiveness models. The rationale, construction,
choice of distribution, implementation and presentation of probabilistic
cost-effectiveness models will be outlined. A straightforward Markov
model will be used to illustrate the principles. The focus will be on
understanding how to implement distributions in a standard spreadsheet
package rather than using a dedicated software programme or spreadsheet
add-in. Illustrations of a real-life model will be used in order to keep
the course interactive and the Excel-based illustration will be made
available to participants as an example after the course. This course is
designed for those with some experience in economic analysis.
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Clinical Assessment |
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Meta-Analysis And
Systematic Literature Review
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.
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Decision Analysis |
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Introduction To Decision Analysis
Faculty: Mark Roberts MD, MPP, FACP,
Associate Professor and Chief, Section of Decision Sciences and Clinical
Systems Modeling University of Pittsburgh School of medicine,
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. Pen and paper exercises
will be used to illustrate these principles. This course is suitable
for those with little experience with decision analysis.
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May 16: Afternoon Courses (1:00-5:00PM) |
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Pharmacoeconomics |
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Elements of Pharmaceutical Pricing
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 and the role
of pharmacoeconomics in helping to shape pricing decisions. This
course will be interactive and is designed for those with some
experience in either pharmacoeconomics or pharmaceutical pricing.
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Quality of Life / Patient-reported
Outcomes |
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Old and New Utility
Measures in Health Economics and Outcomes Research
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.
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Modeling |
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Bayesian Analysis : Applications
Faculty: Bryan Luce MBA, PhD,
Senior Research Leader & CEO, MEDTAP International, Bethesda, MD, USA;
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, USA;
Elisabeth Fenwick PhD, Lecturer, Department of Economics and Related
Studies, University of York, York, UK
Course Description: This course will
focus on the Bayesian “informative prior.” Several example vignettes of
how a Bayesian analysis can be used within outcomes modeling problems
will be presented. Participants will learn how a Bayesian approach is
different and why it is useful for their work and what tools are
available to them. This course is designed for those with a limited
understanding of Bayesian statistical concepts.
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Economic Analysis |
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Statistical
Considerations In Economic Evaluations
Faculty: John Cook PhD, Director, Merck Research
Laboratories, Blue Bell, PA, USA; Joseph Heyse PhD, Executive
Director, Biostatistics & Research Decision Sciences, Merck Research
Laboratories, West Point, PA, USA; George W. Carides PhD, Senior
Biometrician, Merck, Blue Bell, PA, USA
Course Description: This course will
focus on the statistical considerations of planning & analyzing studies
and interpreting the results, including comparisons of types of analyses
used and discussing 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 those with experience
in conducting economic studies.
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Decision Analysis |
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Computer-Assisted Decision Analysis Applications
Faculty:
Andrew Sheldon,
Programmer and Trainer, TreeAge Software, Inc., Williamstown, MA, USA
Course description: During this
course, the participants will build a decision tree to represent a
cost-effectiveness decision using DATA, will be learn the basics of
Markov modeling, build a simple Markov model, and run a Monte Carlo
simulation. This course is suitable for those with little experience
building decision trees.
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9th Annual International Meeting Main Page
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