ISPOR 11th Annual
International Meeting May 20-24, 2006
Marriott Philadelphia, Philadelphia, PA
PRE-MEETING SHORT COURSES, SATURDAY, MAY 20
8:00 AM – 5:00 PM
ALL DAY COURSES
8:00 AM - 5:00PM
Pharmacoeconomic / Economic Methods
Pharmacoeconomics for Decision-Makers
Faculty: Lorne Basskin PhD, Director,
Pharmacy Services, Healthsouth Sunrise Rehab Hospital, 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.
Faculty: William H. Crown PhD, Senior Vice
President, Economics and Outcomes Research
i3 Innovus, Auburndale, MA, USA; Henry Henk PhD, Researcher, Ingenix,
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
Retroactive 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.
8:00 AM - 5:00PM
Modeling Methods
Modeling: Design and Structure of a Model
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; Joel Hay PhD, Associate Professor, USC
School of Pharmacy, Los Angeles, CA, USA
Course description: This course will include a review of Markov
models, discrete event models, and other modeling techniques and
their appropriate including a review of the ISPOR Principles of Good
Practice for Decision Analytic Modeling in Health Care Evaluations
in particular data identification, data modeling, and data
incorporation considerations. 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. This course will cover 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). 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. This intermediate course
requires basic understanding of decision analysis. Enrollment for this course
is limited; please register early.
8:00 AM – 12:00 PM
MORNING COURSES
8:00 AM - 12:00PM
Pharmacoeconomic / Economic Methods
Finding and Extracting Cost Data
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.
8:00 AM - 12:00PM
Modeling Methods
Bayesian Analysis: Overview
Faculty: Bryan Luce MBA, PhD,
Senior Vice President, Science Policy, United BioSource Corporation,
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
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
1:00PM – 5:00PM
AFTERNOON SHORT COURSES
1:00 PM - 5:00PM
Pharmacoeconomic / Economic Methods
Financial Impact / Cost of Illness
Faculty:Josephine Mauskopf PhD, Global Head, Health Economics and
Outcomes Strategy, RTI Health Solutions, Research Triangle Park, NC,
USA; C. Daniel Mullins PhD, Professor and Chair of Pharmaceutical
Health Services Research, University of Maryland, School of
Pharmacy, Baltimore, MD, USA
Course Description: This will describe methods to determine the
cost-of-illness of a health condition using a “top-down” or
“bottom-up” approach. Participants will also learn how to estimate
the impact of new healthcare technologies on disease-specific costs
from different decision-maker perspectives. Actuarial methods using
straight-line projections and nonlinear trends will be described.
Both static and dynamic methods for estimating the budget impact of
adding a new drug to a health plan formulary will also be presented.
This course is designed for those with some experience with
pharmacoeconomic analysis.
1:00 PM - 5:00PM
Modeling Methods
Bayesian Analysis: Applications
Faculty:Bryan Luce MBA, PhD,
Senior Vice President, Science Policy, United BioSource Corporation,
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
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. Participants of this course should be prepared to
use their own laptops as the exercises presented use interactive
software. This course is designed for those with a limited
understanding of Bayesian statistical concepts.
1:00 PM - 5:00PM
Patient-Reported Outcomes /Quality of Life /
Preference-Based Methods
Qualitative Methods for Quality of Life/Patient-Reported Outcomes
Faculty: Carol Tishelman RN,
Professor, Karolinska Institutet and R& D unit
Foundation Stockholms Sjukhem, Stockholm Sweden
Course Description: It is vital that patients’ views inform the conceptual development and use of patient-reported outcome (PRO) measures. This type of data can be fruitfully generated by the use of qualitative or inductive approaches, such as semi-structured/open interviews or focus groups. This course will describe how a variety of qualitative methods can be used to complement the use of other measurement approaches in investigating subjective perspectives (e.g. consumers, patients, professional and family caregivers) about functional status, health perceptions, and health-related quality of life issues that are of importance and/or concern to various stakeholders. This course will focus on orienting the participant to a multitude of ways qualitative approaches can be used to further investigations of these issues, either alone or in combination with other approaches. We will discuss how these methods relate to the ISPOR report “Incorporating the Patient’s Perspective into Drug Development and Communication: An Ad Hoc Task Force Harmonization Group Meeting at the Food and Drug Administration”. Design issues distinguishing qualitative from more quantitative approaches will be particularly addressed.
This course is designed for those with little to no experience with qualitative measures.