| SATURDAY, MAY 19, 2007 8:00 AM - 5:00 PM (All Day
Courses)
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.
Real World Data Methods
Retrospective Database Analysis – Econometric Methods
Faculty: William H. Crown PhD, Senior Vice President, Economics and Outcomes Research
i3 Innovus, Auburndale, MA, USA; Henry Henk PhD, Associate 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 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.
Modeling Methods Modeling: Design and Structure of a
Model
Faculty: Marc Botteman MA,
Managing Partner and Director of Health Economics, 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
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.
Bayesian Analysis: Overview & Applications
Faculty: Bryan Luce MBA, PhD, Senior Vice President, Science Policy, United BioSource Corporation, Bethesda, MD, USA;
Christopher S. Hollenbeak PhD, Assistant Professor, Surgery & 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: 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 portion of 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.
SATURDAY, MAY 19, 2007 8:00 AM - 12:00 PM (Morning
Courses)
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.
Use of Pharmacoeconomics / Economic / Outcomes
Research Information
Elements of Pharmaceutical/Biotech
Pricing I - Introduction 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: 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.
SATURDAY, MAY 19, 2007 1:00 PM - 5:00 PM (Afternoon
Courses)
Pharmacoeconomic / Economic Methods
Financial Impact / Cost of Illness Faculty:
C. Daniel Mullins PhD, Professor and Chair of Pharmaceutical Health Services Research, University of Maryland, School of Pharmacy, Baltimore, MD, USA
Stephanie Earnshaw PhD, MS, US Head Health Economics, RTI Health Solutions, Research Triangle Park, NC, 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 Methods
Advanced Quantitative Methods for Quality of Life / Patient-Reported Outcomes Faculty:
Bruce Crawford MPH, MA, Director, Patient Reported Outcomes and Regulatory Consulting-Operations Director, Mapi Values, Boston, MA, USA;
Kathleen Rosa, PhD, Director of Psychometrics and Statistics, Mapi Values, Boston, MA, USA
Course Description: This course will provide an in-depth discussion of operating characteristics, validity testing, analysis and interpretation with examples of each. It will provide a range of methods that may help to solve common problems encountered with quality of life / patient-reported outcomes. These include an overview of psychometric validation methods including: a brief overview of Rasch analysis, pragmatic issues in validating a PRO from clinical trial data, ePRO validation, methods of estimation of minimally clinically important differences and alternatives to provide information on interpretation Clinical trial analysis will include missing data analysis techniques and mixed modeling appropriate to PRO data and study design, There will be a focus on addressing these issues within the framework provided by the PRO guidance recently released by the SEALD group at the FDA. Specific examples will be used throughout the course and participants will be asked to complete a short exercise.
This course is designed for those with intermediate experience in health-related quality-of-life assessment.
Real World Data Methods
Instrumental Variables in Addressing Selection Bias in Observational Studies Faculty:
Benjamin M Craig PhD, Assistant Professor, University of Wisconsin, Department of Family Medicine, Madison, WI, USA;
Antoine C. El Khoury, PhD, Health Economist, 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 Martin PhD, RPh, PharmD, Associate Professor & Division Chair, College of Pharmacy University of Arkansas for Medical Sciences, Department of Pharmacy Practice, 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, RTCs), 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.
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