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.
 

8:00 AM - 5:00PM 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, 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.


Short Courses - Sunday, May 21st
 


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