ISPOR 20th Annual International Meeting Short Course Program

The ISPOR Short Course Program is offered in conjunction with ISPOR meetings around the world as a series of 4 and 8-hour training courses, designed to enhance your knowledge and technique in 7 key topic areas (“Tracks”) related to pharmacoeconomics & outcomes research.  Short courses range in skill level from Introductory to Advanced.

For more information on ISPOR Short Courses, please visit https://www.ispor.org/education/shortcourses.asp or for questions related to this or any other ISPOR Short Course Program, please contact shortcourse@ispor.org.

Click on a tab below to view short courses presented at the ISPOR 20th Annual International Meeting by date, track, level or instructors.
Click on a heading to expand and a title to view the details
Laptop icon Indicates hands-on exercises requiring the use of your personal laptop.
Please note: Separate Short Course registration is required.


Program by Date Program by Track Program by Level Program by Instructor
Saturday, May 16, 2015 - Full Day
Sold Out Introduction to Pharmacoeconomics
 
Saturday, May 16, 2015
8:00 AM - 5:00 PM
Room: Grand Ballroom, Salon A (Level 5)
Track: Economic Methods
Level: Introductory This course is suitable for those with little or no experience with pharmacoeconomics.
Faculty:
Lorne Basskin, PharmD Lorne Basskin, PharmD, Adjunct Professor of Healthcare Leadership, School of Professional Studies, Brown University, Providence, RI, 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 first review the basic principles and concepts of health economic evaluations, then discuss 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. Different pharmacoeconomic models and techniques will be demonstrated, including cost-minimization, cost-effectiveness, cost-benefit, cost-utility, and budget impact analysis. Decision analysis, sensitivity analysis, and discounting will all be demonstrated and practiced.
Bayesian Analysis - Overview and Applications
 
Saturday, May 16, 2015
8:00 AM - 5:00 PM
Room: Grand Ballroom, Salon I (Level 5)
Track: Modeling Methods
Level: Introductory-Intermediate This course is designed for those with a limited understanding of Bayesian statistical concepts or for those who want a refresher and more practical experience.
Faculty:
Christopher S. Hollenbeak, PhD Christopher S. Hollenbeak, PhD, Professor, Surgery and Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
David J. Vanness, PhD David J. Vanness, PhD, Assistant Professor, University of Wisconsin, School of Medicine and Public Health, 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 part of the course is a "hands-on" workshop where participants will be led through live examples using the free Markov Chain Monte Carlo package WinBUGS. Attendees will have the chance to apply the principles they have learned in the morning session to challenging data analysis problems, including the use of Bayesian generalized linear models (GLM) to analyze cost and outcomes data.
Saturday, May 16, 2015 - Morning Session
Sold Out Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data
 
Saturday, May 16, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon B (Level 5)
Track: Observational Data Methods
Level: Introductory This course is recommended as a pre-requisite to the short courses "Use of Propensity Scores in Observational Studies of Treatment Effects" and "Use of Instrumental Variables in Observational Studies of Treatment Effects."
Faculty:
Bradley C. Martin, PharmD, RPh, PhD Bradley C. Martin, PharmD, RPh, PhD, Professor & Head, Division of Pharmaceutical Evaluation and Policy, University of Arkansas for Medical Sciences College of Pharmacy, Little Rock, AR, USA
Course Description: Retrospective studies require strong principles of epidemiologic study design and complex analytical methods to adjust for bias and confounding. This course will provide an overview of the structures of commonly encountered retrospective data sources with a focus on large administrative data as well as highlight design and measurement issues investigators face when developing a protocol using retrospective observational data. Approaches to measure and control for patient mix, including patient comorbidity and the use of restriction and stratification, will be presented. Linear multivariable regression, logistic regression, and propensity scoring analytic techniques will be presented and include examples and SAS code that can later be used by participants. This course is an introductory course designed to prepare participants to take intermediate and advanced observational research courses.
Introduction to Modeling Methods
 
Saturday, May 16, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon C (Level 5)
Track: Modeling Methods
Level: Introductory This course is suitable for those with little experience with decision analysis, and is recommended as a pre-requisite to the short courses, “Modeling: Design and Structure of a Model,” “Discrete Event Simulation for Economics Analyses,” “Bayesian Analysis,” and “Advanced Decision Modeling for Health Economic Evaluations.
Faculty:
Mark S. Roberts, MD, MPP Mark S. Roberts, MD, MPP, Professor & Chair, Department of Health Policy and Management, University of Pittsburgh, Graduate School of Public Health, 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. Class exercises will be used to illustrate these principles.
Introduction to Patient-Reported Outcomes
 
Saturday, May 16, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon D (Level 5)
Track: Patient-Reported Outcomes Methods
Level: Introductory This course is intended for those with little experience with these methodologies.
Faculty:
Andreas Pleil, PhD Andreas Pleil, PhD, Senior Director & Team Leader, Outcomes and Evidence, Global Health & Value, Pfizer, Inc., San Diego, CA, USA
Alexandra Barsdorf, PhD Alexandra Barsdorf, PhD, Director, PRO Center, Outcomes & Evidence, Global Health & Value, Pfizer, Inc., New York, NY, USA
Course Description: Conceptual, methodological, and practical methods for measuring quality of life, health status, and other types of health outcomes will be presented. Theoretical frameworks, 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.
Introduction to Conjoint Analysis
 
Saturday, May 16, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon J (Level 5)
Track: Patient Preference Methods
Level: Introductory
Faculty:
A. Brett Hauber, PhD A. Brett Hauber, PhD, Senior Economist & Vice President, Health Preference Assessment, RTI Health Solutions, Research Triangle Park, NC, USA
Deborah Marshall, PhD, MHSA Deborah Marshall, PhD, MHSA, Canada Research Chair, Health Services and Systems Research, Associate Professor, Department of Community Health Sciences Faculty of Medicine, University of Calgary, and Director, Health Technology Assessment, Alberta Bone and Joint Health Institute, Calgary, AB, Canada
Course Description: Course participants will learn the conceptual and empirical basis for using conjoint analysis to elicit preferences in outcomes research. The course will introduce participants to both the conceptual basis for quantifying decision-maker preferences for medical interventions and the practical design and analytical issues that must be addressed in order to obtain valid empirical preference estimates. Course material will be structured following the good research practice guidelines and discussion prepared by the ISPOR Good Research Practices for the Application of Conjoint Analysis in Health Task Force, and will include lectures and interactive group exercises and discussions.
Sold Out Elements of Pharmaceutical/Biotech Pricing I – Introduction
 
Saturday, May 16, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon K (Level 5)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information Methods
Level: Introductory This course is designed for those with limited experience in the area of pharmaceutical pricing and covers topics within a global context.
Faculty:
Jack M. Mycka Jack M. Mycka, Global President and CEO, MME LLC, Montclair, NJ, USA
Renato Dellamano, PhD Renato Dellamano, PhD, President, MME Europe & ValueVector (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.
Saturday, May 16, 2015 - Afternoon Session
Sold Out Meta-Analysis and Systematic Reviews in Comparative Effectiveness Research
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon B (Level 5)
Track: Outcomes Research Methods
Level: Introductory This course is designed for those having little experience with meta-analysis, or as a refresher and update for those with more experience.
Faculty:
Joseph C. Cappelleri, PhD, MS, MPH Joseph C. Cappelleri, PhD, MS, MPH, Senior Director, Pfizer Inc., Groton, CT, USA
Jeroen P. Jansen, MSc, PhD Jeroen P. Jansen, MSc, PhD, Founding Partner & Director, Redwood Outcomes, San Francisco, CA, USA
Course Description: Comparative effectiveness research is a rigorous evaluation of the impact of different options that are available for treating a given medical condition for a particular set of patients. Its purpose is to assist consumers, clinicians, purchasers, and policy makers to make the informed decisions that will improve health care at both the individual and population levels. Systematic reviews are considered the standard practice to inform evidence-based decision making of medical technology. A systematic literature review includes the identification, selection, appraisal, and summary of evidence that can answer a particular research question. Results of several similar studies identified with a systematic literature review can be quantitatively synthesized by means of meta-analysis to obtain a pooled estimate of the outcome of interest and the evaluation of heterogeneity. In its basic form, a meta-analysis typically involves comparisons of two interventions for one particular endpoint, but can be expanded with multiple treatment comparisons or outcomes. This course highlights and expounds upon six key and interrelated areas: 1) comparative effectiveness research, 2) impetus for systematic reviews and meta-analysis, 3) basic steps to perform a systematic literature review, 4) statistical methods of combining data, 5) reporting of results, and 6) appraisal and use of meta-analytic reports. The material is motivated by instructive and real examples. Interactive exercises are an integral part of this short course.
Utility Measures
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon L (Level 5)
Track: Patient Preference Methods
Level: Introductory No prior knowledge of utilities or health-related quality of life is assumed.
Faculty:
John Brazier, PhD John Brazier, PhD, Professor of Health Economics, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
Brendan Mulhern Brendan Mulhern, Research Fellow, Health Economics and Outcomes Research, Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia
Course Description: This course is designed to provide an introduction and overview of utility measures to support economic evaluations. The concepts of health-related quality of life and utility will be introduced and discussed in terms of their differences and similarities. Faculty will describe how these data can be combined with survival to estimate quality-adjusted life years. Some issues for debate will be introduced. In the second section, course participants will explore the methods that are used to capture utilities such as standard gamble, time trade off, and rating scales. Building on this will be a presentation of the different generic instruments that have been developed for measuring quality of life such as the EQ-5D, Health Utilities Index, and SF-36. Estimating utilities from a condition-specific measure will also be discussed. In the third section we will describe approaches that can be used when utility data from trials are not available. The development of mapping functions and other crosswalks will be described from disease-specific measures to generic HRQL measures. The pros and cons of the different main approaches will be discussed. Other approaches to addressing a lack of utility data will also be described including prospective observational studies, systematic reviews, critical appraisal of published values, and the valuation of vignette type descriptions of health. In the final section we will describe the requirements and preferences of different reimbursement agencies around the world including UK/Australia/Canada; US agencies; other EU markets such as Sweden/Belgium/Netherlands/Germany; Asia; and Latin America. The course will be interactive with break-out sessions and group discussion.
Modeling: Design and Structure of a Model
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon D (Level 5)
Track: Modeling Methods
Level: Intermediate Participants should have a basic understanding of decision analysis.
Prerequisite: Participation in the short course “Introduction to Modeling Methods,” or equivalent knowledge, is required.
Faculty:
Shelby Corman, PharmD, MS, BCPS Shelby Corman, PharmD, MS, BCPS, Lead Clinical Outcomes Scientist, Pharmerit International, Bethesda, MD, USA
Mark S. Roberts, MD, MPP Mark S. Roberts, MD, MPP, Professor & Chair, Department of Health Policy and Management, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA, USA
Andrew Munzer Andrew Munzer, Director, Training & Product Management, TreeAge Software, Inc., Williamstown, MA, USA
Course Description: During this course, students will have hands-on experience in constructing and analyzing a decision analysis tree using TreeAge Pro software including Markov models and one-way, two-way, and probabilistic sensitivity analysis. Instructors will provide a series of short lecture-based sessions followed by model-building exercises in the software. Sessions will demonstrate how to build a simple decision tree, extend a decision model to incorporate costs and utilities, and replace terminal nodes with state-transition (Markov) models to represent time-varying events. Other more advanced topics will be covered if time permits. Participants are required to bring laptops equipped with software provided to course registrants.
Sold Out Case Studies in Pharmaceutical / Biotech Pricing II – Advanced
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon K (Level 5)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information Methods
Level: Intermediate This course is designed for those with limited experience in the area of pharmaceutical pricing and covers topics within a global context.
Prerequisite: Participation in the short course “Elements of Pharmaceutical / Biotech Pricing I – Introduction,” or equivalent knowledge, is required.
Faculty:
Jack M. Mycka Jack M. Mycka, Global President and CEO, MME LLC, Montclair, NJ, USA
Renato Dellamano, PhD Renato Dellamano, PhD, President, MME Europe & ValueVector (Value Added Business Strategies), Milan, Italy
Course Description: Case studies will be employed to lead participants through the key steps of new product pricing, with focus on the need to thoroughly analyze the business environment and its constraints and opportunities, and the need to closely integrate the pricing, reimbursement, and pharmacoeconomic strategy for the new product with the clinical development and marketing strategies. Practical exercises will allow participants to consolidate the concepts delivered in the “Elements” introductory session and expanded here. Areas covered will include the post-launch issues of reimbursement and pricing maintenance as a part of life-cycle management in a global environment.
Sold Out Cost-Effectiveness Analysis Alongside Clinical Trials
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon C (Level 5)
Track: Economic Methods
Level: Intermediate Familiarity with economic evaluations will be helpful.
Faculty:
Scott D. Ramsey, MD, PhD Scott D. Ramsey, MD, PhD, Member, Fred Hutchinson Cancer Research Center and Professor, Department of Medicine, University of Washington, University of Washington
Sean Sullivan, PhD, MSc, RPh Sean Sullivan, PhD, MSc, RPh, Professor & Dean, Pharmaceutical Outcomes Research and Policy Program, School of Pharmacy, University of Washington, Seattle, WA, USA
Richard J. Willke, PhD Richard J. Willke, PhD, Vice President, Outcomes & Evidence, Global Health & Value, Pfizer Inc., New York, NY, USA
Course Description: The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. This course will present the design, conduct, and reporting of cost-effectiveness analyses alongside clinical trials based on, in part, Good Research Practices for Cost-Effectiveness Analysis alongside Clinical Trials: The ISPOR RCT-CEA Task Force Report. Trial design, selecting data elements, database design and management, analysis, and reporting of results will be presented. Trials designed to evaluate effectiveness (rather than efficacy), as well as clinical outcome measures, will be discussed. How to obtain health resource use and health state utilities directly from study subjects and economic data collection fully integrated into the study will also be discussed. Analyses guided by an analysis plan and hypotheses, an incremental analysis using an intention to treat approach, characterization of uncertainty, and standards for reporting results will be presented.
Sold Out Advanced Patient-Reported Outcomes
 
Saturday, May 16, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon J (Level 5)
Track: Patient-Reported Outcomes Methods
Level: Advanced
Faculty:
Karon F. Cook, PhD Karon F. Cook, PhD, Research Professor, Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Michael A. Kallen, PhD, MPH Michael A. Kallen, PhD, MPH, Research Associate Professor, Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Course Description: This course provides an in-depth discussion of both the methods that are used to validate and refine PRO measures (including ePROs) and the analytic methods that are used to model PRO data over time in clinical trials. PRO measure validation methods include factor analysis and item response theory (IRT; including Rasch models) to evaluate the psychometric properties of the scale and other statistical methods to examine construct validity (e.g., known groups validity, convergent validity, responsiveness). This includes methods to estimate minimally important differences (MIDs) using anchor- and distribution-based methods, including use of receiver operating characteristic (ROC) curve and area under the curve (AUC) analysis to look at the sensitivity and specificity of the measure. Clinical trial PRO data analysis will include missing data analysis techniques and mixed modeling appropriate to PRO data and study design. Specific examples will be used throughout the course.
Sunday, May 17, 2015 - Morning Session
Discrete Event Simulation for Economic Analyses - Concepts
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon A-B (Level 5)
Track: Modeling Methods
Level: Introductory This course is designed for those with some familiarity with modeling.
Faculty:
J. Jaime Caro, MDCM, FRCPC, FACP J. Jaime Caro, MDCM, FRCPC, FACP, Chief Scientist, Evidera, Lexington, MA, USA and Adjunct Professor of Medicine & Adjunct Professor of Epidemiology and Biostatistics, McGill University, Montreal, QC, Canada
Jörgen Möller, MSc Mech Eng Jörgen Möller, MSc Mech Eng, Vice-President, Modeling, Evidera, Hammersmith, UK and Associate Researcher, Division of Health Economics, Faculty of Medicine, Lund University, Lund, Sweden
Course Description: This course will provide a basic understanding of the key concepts of discrete event simulation (DES). DES topics to be covered are: how does DES work; what are the components; where is it used; for which problems is DES well-suited; what are the advantages and disadvantages of DES; probabilistic sensitivity analysis (PSA) as a simple task. The focus will be on the use of these simulation models to address pharmacoeconomic (and device-related) problems. Faculty will also discuss the recently published ISPOR-SMDM guidelines on DES.
Statistical Methods in Economic Evaluations
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon C-D (Level 5)
Track: Economic Methods
Level: Intermediate Participants should have basic knowledge of economic evaluations and statistics.
Faculty:
Shelby Reed, RPh, PhD Shelby Reed, RPh, PhD, Professor, Duke Clinical Research Institute, Durham, NC, USA
Brad Hammill, MS Brad Hammill, MS, Senior Biostatistician, Duke Clinical Research Institute, Durham, NC, USA
Course Description: Economic evaluations play an integral role in informing health care policy decisions. These studies often rely on data from clinical trials, prospective registries, and secondary data. The availability of patient-level data allows analysts to apply conventional and innovative statistical methods to patient-level data. In this course, faculty will examine statistical approaches that address common features of resource use and cost data, including distributional characteristics, censoring, hierarchical data structures, and potential confounding. Faculty will also examine additional statistical issues that arise when combining patient-level estimates of costs and effectiveness. Throughout the course, faculty will include examples of statistical analyses.
Risk Sharing / Performance-Based Arrangements for Drugs and Other Medical Products
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon F (Level 5)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Prerequisite: It will be helpful for individuals taking this course to have completed the short course, “Elements of Pharmaceutical / Biotech Pricing I – Introduction,” or to be familiar with both the key determinants of pharmaceutical pricing and the main international health systems.
Faculty:
Lou Garrison, PhD Lou Garrison, PhD, Professor, Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, WA, USA
Adrian Towse, MA, MPhil Adrian Towse, MA, MPhil, Director, Office of Health Economics, London, UK
Josh Carlson, PhD Josh Carlson, PhD, Assistant Professor, Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, WA, USA
Course Description: There is significant and growing interest among both the payers and producers of medical products for arrangements that involve a “pay-for-performance” or “risk-sharing” element. These payment schemes involve a plan by which the performance of the product is tracked in a defined patient population over a specified period of time and the level of reimbursement is tied by formula to the outcomes achieved. Although these agreements have an intrinsic appeal, there can be substantial barriers to their implementation. Issues surrounding theory and practice, including incentives and barriers, will be analyzed along with several examples of performance-based schemes from Europe, the United States, and Australia. A hypothetical case study will be used in an interactive session to illustrate a systematic approach to weighing their applicability and feasibility.
Sold Out NEW! Development of Conceptual Models
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon K (Level 5)
Track: Modeling Methods
Level: Introductory
Faculty:
Neil Hawkins, PhD, CStat Neil Hawkins, PhD, CStat, Reader in Health Technology Assessment, London School of Hygiene and Tropical Medicine, London, UK
Elisabeth Fenwick, PhD, MSc Elisabeth Fenwick, PhD, MSc, Director Health Economics, ICON Health Economics, Oxford, UK
Paul Tappenden, MSc, PhD Paul Tappenden, MSc, PhD, Reader in Health Economic Modelling, Health Economics and Decision Science, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
Course Description: Within the context of health care, models may be used to inform decisions regarding reimbursement, pricing, and use of technologies. Models may be conceptual or quantitative: conceptual models identify and describe the important entities within a model, the nature of these entities and the relationships between them; quantitative models aim to represent these entities and their relationships numerically or mathematically. Depending on the nature of a particular problem, a conceptual model may be sufficient to inform decisions regarding study design whereas a quantitative model may be needed to inform reimbursement decisions. The development of a clear conceptual model, an important pre-cursor to the development of quantitative models, is important is assisting to communicate and clarify the intent and structure of a proposed quantitative analysis. This course will reference and build on the report of the ISPOR-SMDM Modeling Good Research Practices Task Force on conceptual modeling. The course will review important practical aspects of the development of conceptual models using a series of case studies, which will illustrate the role of clear conceptual models in the iterative process of model development. The course will also illustrate the need to consider various aspects when developing conceptual models (including the decision problem, service framework, disease pathway, causal pathway, and quantitative model design aspects) and will provide overview of useful graphical tools for illustrating these aspects.
Applications in Using Large Databases
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon G (Level 5)
Track: Observational Data Methods
Level: Intermediate Participants must have some knowledge of administrative health care database analysis.
Prerequisite: Previous attendance at the short course “Introduction to the Design and Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.
Faculty:
Joanne LaFleur, PharmD, MSPH Joanne LaFleur, PharmD, MSPH, Assistant Professor, Department of Pharmacotherapy, University of Utah and Principal Investigator, George E. Whalen Veterans Health Administration IDEAS Center, Salt Lake City, Utah, USA
Antonis Kousoulis, MD, MSc Antonis Kousoulis, MD, MSc, Acting Head, Business Development, CPRD (Clinical Practice Research Datalink), London, UK
Pamela Landsman-Blumberg, MPH, DrPH Pamela Landsman-Blumberg, MPH, DrPH, Director & Team Lead, Applied Data Analytics, Xcenda, Tampa, FL, USA
Helen Strongman, MA, MSc Helen Strongman, MA, MSc, Research Scientist, CPRD (Clinical Practice Research Datalink), London, UK
Course Description: This course will provide a review of three health care databases – CPRD (UK database), GE Centricity electronic medical record (US database), and Medicare (US database). Each database will be discussed in-depth including directions on how to access the information and how researchers utilize this information. Instructors will distinguish the important differences between these databases including the limitations and strategies to maximize their value through the use of an interactive format with interactive examples. The ISPOR International Digest of Databases and its use in identifying health care databases around the globe will be briefly discussed.
Patient-Reported Outcomes – Item Response Theory
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon I-J (Level 5)
Track: Patient-Reported Outcomes Methods
Level: Introductory This course is designed for those with little to no experience with IRT.
Faculty:
Bryce Reeve, PhD Bryce Reeve, PhD, Associate Professor, Lineberger Comprehensive Cancer Center & Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Course Description: There is a great need in health outcomes research to develop instruments that accurately measure a person's health status with minimal response burden. This need for psychometrically sound and clinically meaningful measures calls for better analytical tools beyond the methods available from traditional measurement theory. Applications of item response theory (IRT) modeling have increased considerably because of its utility for instrument development and evaluation, assessment of measurement equivalence, instrument linking, and computerized adaptive testing. IRT models the relationship, in probabilistic terms, between a person's response to a survey question and their standing on a health construct such as fatigue or depression. This information allows instrument developers to develop reliable and efficient quality of life measures tailored for an individual or group. This introductory course will discuss the basics of IRT models and applications of these models to improve health outcomes measurement. Illustrations that focus on measuring key health-related quality of life domains in different disease populations will be used throughout the presentation. The NIH Patient-Reported Outcomes Measurement Information System (PROMIS) project will also be discussed for its relevance for assessing patient-reported outcomes using modern psychometric methods.
Use of Instrumental Variables in Observational Studies of Treatment Effects
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon L (Level 5)
Track: Observational Data Methods
Level: Intermediate This course is suitable for those with some knowledge of econometrics.
Prerequisite: Previous attendance at the short course “Introduction to the Design and Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.
Faculty:
Benjamin Craig, PhD Benjamin Craig, PhD, Assistant Member, Health Outcomes and Behavior, Moffitt Cancer Center and Associate Professor, Department of Economics, University of South Florida, Tampa, FL, USA
Bradley C. Martin, PharmD, RPh, PhD Bradley C. Martin, PharmD, RPh, PhD, Professor & Head, Division of Pharmaceutical Evaluation and Policy, University of Arkansas for Medical Sciences College of Pharmacy, Little Rock, AR, USA
Antoine C. El Khoury, PhD, MS Antoine C. El Khoury, PhD, MS, Director, Market Access and Health Economics, Johnson and Johnson, Horsham, PA, USA and Adjunct Assistant Professor, Division of Pharmaceutical Evaluation and Policy, University of Arkansas for Medical Sciences College of Pharmacy, 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, and RCTs), 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.
Budget Impact Analysis I: A 6-Step Approach
 
Sunday, May 17, 2015
8:00 AM - 12:00 PM
Room: Grand Ballroom, Salon E (Level 5)
Track: Economic Methods
Level: Intermediate
Prerequisite: This course is designed for those with some experience with pharmacoeconomic analysis.
Faculty:
Josephine Mauskopf, PhD Josephine Mauskopf, PhD, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA
C. Daniel Mullins, PhD C. Daniel Mullins, PhD, Professor, Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD, USA
Stephanie Earnshaw, PhD, MS Stephanie Earnshaw, PhD, MS, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA
Course Description: This course will describe the methods used to estimate the budget impact of a new health care technology, and will present six basic steps for estimating budget impact: 1) estimating the target population; 2) selecting a time horizon; 3) identifying current and projected treatment mix; 4) estimating current and future drug costs; 5) estimating change in disease-related costs; and 6) estimating and presenting changes in annual budget impact and health outcomes. Both static and dynamic methods for estimating the budget and health impact of adding a new drug to a health plan formulary will be presented. These six steps will be illustrated using actual budget impact models.
Sunday, May 17, 2015 - Afternoon Session
NEW! Introduction to Big Data Analysis: Graph Analytics
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon G (Level 5)
Track: Observational Data Methods
Level: Introductory-Intermediate
Faculty:
David R. Holmes III, PhD David R. Holmes III, PhD, Collaborative Scientist, Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, USA
Course Description: Semantic graph databases can change the way that we look at data, and graph analytics yields new insights into existing and soon-to-be collected datasets. This course will address how graph analytics are used to deal with issues of data quality and data completeness, the implications for the confidence in the conclusions drawn from these analyses, and where the challenges still lie in data migration and data quality. Issues related to node-typed, edge-typed, and directed graphs, using the resource description framework (RDF) to describe information in a graph, using SPARQL, and application of inferential rules and ontologies to the dataset will be discussed.
Budget Impact Analysis II: Applications & Design Issues
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon E (Level 5)
Track: Economic Methods
Level: Intermediate This course is designed for those who have basic knowledge of budget impact analyses and desire exposure to these analyses in Excel.
Prerequisite: Participation in the short course “Budget Impact Analysis I: A 6-Step Approach,” or equivalent knowledge, is recommended.
Faculty:
Stephanie Earnshaw, PhD, MS Stephanie Earnshaw, PhD, MS, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA
Anita Brogan, PhD Anita Brogan, PhD, Head, Decision-Analytic Modeling, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA
Sorrel Wolowacz, PhD Sorrel Wolowacz, PhD, Head, Health Economics, RTI Health Solutions - Europe, Manchester, UK
Course Description: This course provides hands-on experience utilizing an Excel workbook-based approach to working with and modifying budget impact analysis models. Participants will receive an actual Excel-based budget impact analysis developed for use in the real world in order to gain greater understanding of applications of the 6-step approach presented in the complementary introductory course. Participants will be able to actively interpret the model’s results and adapt the analysis to include new inputs and calculations to handle important issues such as patient copayments, adherence, and generics. Topics such as issues to consider when adapting to another country, inclusion of a companion diagnostic or use of off-label drugs, and sensitivity analyses will also be covered. This course will provide a key opportunity for attendees to gain exposure to the more practical/applied aspects of performing budget impact analyses. Participants who wish to gain hands-on experience must bring their laptops with Microsoft Excel for Windows installed..
Discrete Event Simulation for Economic Analyses - Applications
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon K (Level 5)
Track: Modeling Methods
Level: Intermediate This course is designed for those with some understanding of discrete event simulation and who wish to have more practical modeling experience.
Prerequisite: Attendance at the short course “Discrete Event Simulation for Economics Analyses - Concepts,” or equivalent knowledge, is required.
Faculty:
J. Jaime Caro, MDCM, FRCPC, FACP J. Jaime Caro, MDCM, FRCPC, FACP, Chief Scientist, Evidera, Lexington, MA, USA and Adjunct Professor of Medicine & Adjunct Professor of Epidemiology and Biostatistics, McGill University, Montreal, QC, Canada
Jörgen Möller, MSc Mech Eng Jörgen Möller, MSc Mech Eng, Vice-President, Modeling, Evidera, Hammersmith, UK and Associate Researcher, Division of Health Economics, Faculty of Medicine, Lund University, Lund, Sweden
Course Description: This course is structured around practical discrete event simulation exercises. Topics to be covered are: components of a DES; how do you build a model; modeling of processes and resource use; modeling of variables and decisions. Simple animation will be demonstrated. We will use ARENA to build entry level models. Instructions for downloading a training version of ARENA will be distributed prior to the course. Participants who wish to have hands-on experience must bring their laptops with ARENA installed.
Network Meta-Analysis
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon A-B (Level 5)
Track: Outcomes Research Methods
Level: Intermediate This course requires at least a basic knowledge of meta-analysis and statistics.
Prerequisite: The short course, “Meta-Analysis & Systematic Review for Comparative Effectiveness Research,” or equivalent knowledge, is a prerequisite for this course. Participants must have knowledge of statistical methods.
Faculty:
Joseph C. Cappelleri, PhD, MS, MPH Joseph C. Cappelleri, PhD, MS, MPH, Senior Director, Pfizer Inc., Groton, CT, USA
Jeroen P. Jansen, MSc, PhD Jeroen P. Jansen, MSc, PhD, Founding Partner & Director, Redwood Outcomes, San Francisco, CA, USA
Course Description: For several medical questions of interest, many treatment options exist for the same indication. These treatments may have been compared against placebo or against each other in clinical trials. Knowing whether one specific treatment is better than placebo or some other specific comparator is only a fragment of the big picture, which should incorporate all available information. Ideally, one would like to know how all the different treatment options rank against each other and how big the differences are in effect size between all the available options. Network meta-analysis offers a quantitative method of integrating all the data from all the available comparisons. Based in part on two ISPOR Task Force Reports on Indirect Treatment Comparisons, the fundamentals and concepts of network meta-analysis will be presented, which is especially useful when there’s little or no evidence from direct comparisons. Network meta-analysis provides an integrated and unified analysis that incorporates all direct and indirect comparative evidence about treatments. Nevertheless, the evaluation of networks also presents special challenges and caveats, which will also be highlighted in this course. The material in this course is motivated by instructive and real examples. Case studies are implemented with the WinBUGS package.
Use of Propensity Scores in Observational Studies of Treatment Effects
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon I-J (Level 5)
Track: Observational Data Methods
Level: Intermediate This course is designed for those with little experience with this methodology but some knowledge of observational databases.
Prerequisite: Previous attendance at the short course “Introduction to the Design and Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.
Faculty:
John Seeger, PharmD, DrPH John Seeger, PharmD, DrPH, Assistant Professor of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Harvard Medical School/Brigham and Women's Hospital, Boston, MA, USA
Jeremy Rassen, ScD Jeremy Rassen, ScD, Chief Scientific Officer, Aetion, Inc., New York, NY, USA
Course Description: In observational research, issues of bias and confounding relate to study design and analysis in the setting of non-random treatment assignment where compared subjects might differ substantially with respect to comorbidities. No control over the treatment assignment and the lack of balance in the covariates between the treatment and control groups can produce confounded estimates of treatment effect. Faculty will explain how propensity scores can be used to mitigate confounding through standard observational approaches (restriction, stratification, matching, regression, or weighting). The advantages and disadvantages of standard adjustment relative to propensity score-based methods will be discussed. Details of propensity score methodology (variable selection, use, and diagnostics) will also be discussed. The course will also elaborate briefly on risk adjustment models that collapse predictors of outcomes and their use relative to propensity scores.
Advanced Decision Modeling For Health Economic Evaluations
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon F (Level 5)
Track: Modeling Methods
Level: Advanced Participants should have an understanding of decision analysis.
Prerequisite: Previous attendance at the short course “Modeling: Design and Structure of a Model,” or equivalent knowledge, is required.
Faculty:
Andrew Briggs, DPhil, MSc Andrew Briggs, DPhil, MSc, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
Elisabeth Fenwick, PhD, MSc Elisabeth Fenwick, PhD, MSc, Director Health Economics, ICON Health Economics, Oxford, UK
Course Description: During this course, the key aspects and new developments of decision modeling for economic analysis will be considered. How models can be made probabilistic to capture parameter uncertainty (including rationale, choosing parameter distributions, and types of uncertainty) will be covered. How to analyze and present the results of probabilistic models, how the results of probabilistic decision modeling should be interpreted, and how decisions should be made (including decisions with uncertainty and expected value of perfect information [EVPI]), will be presented. Specific examples using Excel programming will be used to illustrate concepts.
NEW! Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications
 
Sunday, May 17, 2015
1:00 PM - 5:00 PM
Room: Grand Ballroom, Salon C-D (Level 5)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information Methods
Level: Advanced Participants should have an understanding of decision analysis.
Faculty:
Maarten Ijzerman, PhD Maarten Ijzerman, PhD, Professor & Head, Department of Health Technology & Services Research, University of Twente, Enschede, The Netherlands
Kevin Marsh, PhD Kevin Marsh, PhD, Senior Research Scientist, EU Director of Modelling and Simulation, Evidera, London, UK
Nancy Devlin, PhD Nancy Devlin, PhD, Director of Research, Office of Health Economics, London, UK
Praveen Thokala, PhD, MASc Praveen Thokala, PhD, MASc, Research Fellow, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
Course Description: Many health care decisions – such as portfolio optimization, benefit-risk assessment (BRA), health technology assessment (HTA), and shared decision making (SDM) – require a careful assessment of the underlying options and the criteria used to judge these options. This assessment can be challenging given the tradeoffs between multiple value criteria. In light of this, many decision makers have begun investigating the use of multi-criteria decision analysis (MCDA) in support of these decisions. This course reviews the current MCDA landscape, including a review of MCDA studies in health care and the different approaches employed. Best practices for conducting MCDA will also be outlined, as well as issues related to selecting the right data approach. Steps involved in conducting MCDA (such as criteria definition, scoring performance, weighting criteria, and uncertainty analysis), and current and future applications in health care decision making will be discussed. Faculty will draw from a number of real world examples and will reference the ISPOR Good Practice Guidelines for MCDA.
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