ISPOR 22nd 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 22nd 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 20, 2017 - Full Day
Introduction to Pharmacoeconomics
 
Saturday, May 20, 2017
8:00 AM - 5:00 PM
Room: Sheraton-Constitution A-2nd Floor
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, 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 20, 2017
8:00 AM - 5:00 PM
Room: Sheraton-Fairfax-3rd Floor
Track: Modeling Methods
Level: 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 & Chief, Division of Outcomes Research and Quality, Penn State College of Medicine, Hershey, PA, USA
David J. Vanness, PhD David J. Vanness, PhD, Associate Professor, Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, 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. Participants are required to bring a full charged Windows laptop (or MacBook with Windows running in a Parallels Desktop) pre-loaded with the course software provided to course registrants.
Saturday, May 20, 2017 - Morning Session
Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources
 
Saturday, May 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Republic-2nd Floor
Track: Observational Data Methods
Level: Introductory This course is recommended as a pre-requisite to the ISPOR Short Courses, “Use of Propensity Scores in Observational Studies of Treatment Effects” and “Use of Instrumental Variables in Observational Studies of Treatment Effects.”
Faculty:
Benjamin M. Craig, PhD Benjamin M. Craig, PhD, Associate Professor, Department of Economics, University of South Florida and Assistant Member, Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, 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 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Constitution B-2nd Floor
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 ISPOR Short Courses, “Modeling: Design and Structure of a Model,” “Using DICE Simulation for Health Economic 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 basic methods of decision modeling for health care applications. The course will introduce several of the common methods available as well as provide more detailed introductions to basic decision analysis, the use of sensitivity analysis, and how to interpret decision model outputs. The importance of data sources for calibrating models, the incorporation of multiple outcomes such as quality of life and costs, state-transition (Markov) models, and structures used to represent events over time, will be presented. Throughout the course, the recommendations of the joint SMDM/ISPOR Modeling methods Good research practices recommendations will be reviewed.
Introduction to Patient-Reported Outcomes
 
Saturday, May 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Liberty-2nd Floor
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 I Barsdorf, PhD Alexandra I Barsdorf, PhD, Director, Outcomes & Evidence, Global Health and Value, Pfizer, Inc, New York, NY, USA
Course Description:
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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 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay B-2nd Floor
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 A. Marshall, PhD Deborah A. Marshall, PhD, Canada Research Chair, Health Services and Systems Research, Associate Professor, Department of Community Health Sciences, Faculty of Medicine, University of Calgary, 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.
Interoperability and Informatics - Practical Tools and Strategies for Analyzing Real World Data
 
Saturday, May 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay D-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory
Faculty:
Scott D. Nelson, PharmD, MS Scott D. Nelson, PharmD, MS, Principal Domain Specialist, EHR Portfolio, Vanderbilt University Medical Center, Nashville, TN, USA
Olivier Bodenreider, MD, PhD Olivier Bodenreider, MD, PhD, Senior Scientist & Branch Chief, Cognitive Science Branch, U.S. National Library of Medicine, Bethesda, MD, USA
Daniel C. Malone, PhD, RPh, FAMCP Daniel C. Malone, PhD, RPh, FAMCP, Professor of Pharmacy, College of Pharmacy & Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
Richard D. Boyce, PhD Richard D. Boyce, PhD, Assistant Professor, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA
Course Description:
What is health information exchange (HIE) and how can we bridge the 'data islands' to improve the delivery and evaluation of health services? Health care data currently exists locked up in many different islands making data integration, exchange, and aggregation difficult. Bridges between these 'data islands' are needed, but how do we get everyone to speak or understand the same language? HIE and interoperability require standard data exchange formats and terminologies to promote understanding across systems. This course will provide an introduction to health information exchange, standardized data exchange formats and pharmacy terminologies, the pharmacy "Rosetta stone" RxNorm, and application of these topics, such as using RxNorm to identify medications of interest for health outcomes studies, especially when the products are off-patent and made by numerous manufacturers. Faculty will also discuss the use of common data models, such as the Observational Health Data Sciences and Informatics (OHDSI, ohdsi.org) collaborative research network. Participants will be encouraged to share their experiences and views, and will have opportunity to provide feedback and ask questions. Participants who wish to fully participate in the hands-on course exercise are encouraged to bring their laptops.
Cost-Effectiveness Analysis Alongside Clinical Trials
 
Saturday, May 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Independence-2nd Floor
Track: Economic Methods
Level: Intermediate Familiarity with economic evaluations will be helpful.
Faculty:
Scott D. Ramsey, MD, PhD Scott D. Ramsey, MD, PhD, Full Member, HICOR, Public Health Sciences Division, Fred Hutchinson Cancer Research Center and Professor, Department of Medicine, University of Washington, Seattle, WA, USA
Richard J. Willke, PhD Richard J. Willke, PhD, Chief Science Officer, International Society for Pharmacoeconomics and Outcomes Research, Lawrenceville, NJ, 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 Reports. 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.
Elements of Pharmaceutical/Biotech Pricing I - Introduction
 
Saturday, May 20, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay C-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
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 Mycka Jack Mycka, Global President & CEO, Medical Marketing Economics LLC (MME), 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 20, 2017 - Afternoon Session
Meta-Analysis and Systematic Reviews in Comparative Effectiveness Research
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Republic-2nd Floor
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, MS, MPH, PhD Joseph C. Cappelleri, MS, MPH, PhD, Senior Director of Biostatistics, Pfizer Inc., Groton, CT, USA
Jeroen P. Jansen, PhD, MSc Jeroen P. Jansen, PhD, MSc, Vice President & Chief Scientist, Evidence Synthesis and Decision Modeling, Precision Health Economics, Oakland, 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 in making informed decisions that will improve health care at both individual and population levels. As a central part of comparative effectiveness research and reviews, 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. In its basic form, meta-analysis typically involves head-to-head (direct) comparisons between treatments. Based in part on two ISPOR Good Research Practice Task Force Reports on Indirect Treatment Comparison, a description of network meta-analysis will also be presented and proposed when there’s little or no evidence from direct comparisons. This course highlights and expounds upon six key and interrelated areas: 1) comparative effectiveness research; 2) impetus for meta-analysis and systematic reviews; 3) basic steps in performing a quantitative systematic 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 the course.
Utility Measures
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay D-2nd Floor
Track: Patient Preference Methods
Level: Introductory No prior knowledge of utilities or health-related quality of life is assumed.
Faculty:
John Brazier, PhD, MSc John Brazier, PhD, MSc, Professor of Health Economics, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
Brendan Mulhern, MRes Brendan Mulhern, MRes, 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 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Liberty-2nd Floor
Track: Modeling Methods
Level: Intermediate Participants should have a basic understanding of decision analysis.
Prerequisite: Participation in the ISPOR Short Course, “Introduction to Modeling Methods,” or equivalent knowledge, is required.
Faculty:
Shelby L. Corman, PharmD, MS, BCPS Shelby L. Corman, PharmD, MS, BCPS, Director, Health Economics and Outcomes Research, 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
Course Description:
During this course, students will have hands-on experience in constructing and analyzing a decision analysis tree – including Markov models and one-way, two-way, and probabilistic sensitivity analysis – using TreeAge Pro software. Instructors will provide a series of short lecture-based sessions followed by the opportunity for participants to engage in model-building exercises using 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 their personal laptops equipped with software provided to course registrants, those without full Administrator rights on their computer will not be able to authorize the software onsite.
Applications in Using Large Databases
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Commonwealth-3rd Floor
Track: Observational Data Methods
Level: Intermediate Participants must have some knowledge of administrative health care database analysis.
Prerequisite: Previous attendance at the ISPOR Short Course, “Introduction to Design &Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.
Faculty:
Diana Brixner, PhD, RPh, FAMCP Diana Brixner, PhD, RPh, FAMCP, Professor, Department of Pharmacotherapy, University of Utah College of Pharmacy, Executive Director, Pharmacotherapy Outcomes Research Center, and Director of Outcomes, University of Utah Health Sciences Center, Salt Lake City, UT, USA
Joanne LaFleur, PharmD, MPH Joanne LaFleur, PharmD, MPH, Assistant Professor, Department of Pharmacotherapy, University of Utah and Associate Investigator, George E. Whalen Veterans Health Administration IDEAS Center, Salt Lake City, UT, USA
Course Description:
This course will provide an overview of various three health care databases including the Quintiles EMR database, the VA database, the CPRD (UK database) and assorted claims and survey based databases. Each database will be discussed in-depth including directions on how to access the information and how researchers utilize this data to generate information for health care decision making. Instructors will distinguish the important differences between these databases including the limitations and strategies to maximize their value through the use of an interactive assignments and workshops with the audience. The ISPOR International Digest of Databases and its use in identifying health care databases around the globe will be briefly discussed.
Use of Propensity Scores in Observational Studies of Treatment Effects
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Constitution B-2nd Floor
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 ISPOR Short Course, “Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.
Faculty:
John D Seeger, PharmD, DrPH John D Seeger, PharmD, DrPH, Chief Scientific Officer, Epidemiology, Optum, Waltham, MA, USA
Jeremy A. Rassen, ScD Jeremy A. Rassen, ScD, Co-Founder & Chief Scientific Officer, Aetion, Inc., New York, NY, USA
Course Description:
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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 Patient-Reported Outcomes
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Independence-2nd Floor
Track: Patient-Reported Outcomes Methods
Level: Advanced
Faculty:
Cheryl D. Coon, PhD Cheryl D. Coon, PhD, Principal, Outcometrix, Tucson, AZ, USA
Course Description:
This course provides an in-depth discussion of psychometric methods used to develop, evaluate, and interpret patient-reported outcome instruments. Participants will learn a range of methods for item-level evaluation, determining a scoring algorithm, scale-level evaluation, and interpreting scores. In particular, the course will cover methods used to evaluate the performance of items and response categories, determine the relationship between and dimensionality of items, assess the reliability, validity, and responsiveness of scores, and set thresholds for interpreting scores and score changes. While psychometric jargon can be daunting, this course will take an accessible approach to understanding the goals of each psychometric method. A variety of quantitative methods will be presented, and the course will emphasize that different paths can be taken to achieve similar solutions. Course participants will engage in an interactive exercise throughout the session to gain experience in making instrument development and interpretation decisions based on the integration of qualitative and quantitative information. 
NEW! Using Dynamic Simulation Models for Decision Making in Health Care Delivery
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay B-2nd Floor
Track: Modeling Methods
Level: Intermediate This course is designed for beginners in simulation modeling, but some experience with HTA and decision modeling.
Faculty:
Deborah A. Marshall, PhD Deborah A. Marshall, PhD, Canada Research Chair, Health Services and Systems Research, Associate Professor, Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Alberta Bone and Joint Health Institute, Calgary, AB, Canada
Maarten J. IJzerman, PhD Maarten J. IJzerman, PhD, Professor, Department of Health Technology & Services Research, University of Twente, Enschede, The Netherlands
Elisabeth Fenwick, PhD Elisabeth Fenwick, PhD, Principal, ICON Health Economics and Epidemiology, Abingdon, UK
Course Description:
The course aims to provide a basic overview of common simulation modeling methods that can be applied in health care delivery research. This course will first review of traditional questions posed for health economics and the traditional modelling approaches employed to answer these questions. Faculty will then introduce the types of questions that might be posed when assessing health care delivery and the simulation models that can be used to address these questions using the ISPOR Dynamic Simulation Modeling Application in Health Care Delivery Research Emerging Good Practices Task Force report as a basis. Faculty will subsequently detail the specifics of three common simulation modeling approaches (system dynamics, discrete event simulation, and agent based models), the types of problems that each can address, and their advantages and disadvantages. A case study will be used to illustrate the advantages and disadvantages of each type of modeling method.
Case Studies in Pharmaceutical/Biotech Pricing II - Advanced
 
Saturday, May 20, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay C-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
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 ISPOR Short Course, “Elements of Pharmaceutical / Biotech Pricing I – Introduction,” or equivalent knowledge, is required.
Faculty:
Jack Mycka Jack Mycka, Global President & CEO, Medical Marketing Economics LLC (MME), 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.
Sunday, May 21, 2017 - Morning Session
Using DICE Simulation for Health Economic Analyses
 
Sunday, May 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay D-2nd Floor
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, Waltham, MA, USA and Adjunct Professor of Medicine, Adjunct Professor of Epidemiology and Biostatistics, McGill University, Montreal, QC, Canada
Jorgen Moller, MSc, Mech Eng Jorgen Moller, MSc, Mech Eng, Vice President, Modelling Technologies and Simulation, Evidera, Hammersmith, UK
Course Description:
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This course will provide a basic understanding of the concepts of discretely-integrated condition event (DICE) simulation as it is applied in health technology assessment (HTA). Topics to be covered are: what is the basic idea of DICE; what are its components; how does it work; how is it conceptualized; how are outcomes obtained; how to implement a DICE in EXCEL (including both discrete event simulation and Markov models, and their combination in a single structure); how to do structural sensitivity analyses; what are the advantages and disadvantages of DICE.

Statistical Methods in Economic Evaluations
 
Sunday, May 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Constitution B-2nd Floor
Track: Economic Methods
Level: Intermediate Participants should have basic knowledge of economic evaluations and statistics.
Faculty:
Shelby D. Reed, PhD, RPh, Shelby D. Reed, PhD, RPh,, Professor, Medicine, Duke University, Durham, NC, USA
Brad Hammill, DrPh, MS Brad Hammill, DrPh, MS, Faculty Biostatistician, Duke School of Medicine & 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 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay C-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Prerequisite: Helpful for those 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:
Louis P. Garrison, PhD Louis P. Garrison, PhD, Professor, Pharmaceutical Outcomes Research and Policy Program, School of Pharmacy, University of Washington, Seattle, WA, USA
Adrian Towse, MA, MPhil Adrian Towse, MA, MPhil, Director, Office of Health Economics, London, UK
Josh J. Carlson, MPH, PhD Josh J. Carlson, MPH, PhD, Associate 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.
NEW! Collecting Health-State Utility Estimates for Economic Models in Clinical Studies
 
Sunday, May 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay A-2nd Floor
Track: Patient Preference Methods
Level: Intermediate This course is for those with some experience with quality of life measures in health economic evaluation.
Faculty:
Sorrel Wolowacz, PhD Sorrel Wolowacz, PhD, Senior Director, Market Access and Outcomes Strategy, RTI Health Solutions, Manchester, UK
Andrew Briggs, DPhil Andrew Briggs, DPhil, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, University of Glasgow, Glasgow, UK
Andrew J. Lloyd, DPhil Andrew J. Lloyd, DPhil, Director, Bladon Associates, Ltd, Oxford, UK
Lynda Doward, MRes Lynda Doward, MRes, Head, European Health Economics, RTI Health Solutions, Manchester, UK
Course Description:
Health state utility (HSU) estimates are among the most important and uncertain data inputs in cost-utility models and are increasingly being used to inform health technology assessment, pricing, and reimbursement decisions in many countries. The ISPOR Outcomes Research Guideline, Collecting Health-State Utility Estimates for Economic Models in Clinical Studies, has been developed recently by an ISPOR Task Force (https://www.ispor.org/Estimating-Health-State-Utility-Economic-Models-Clinical-Studies-guidelines.asp) to help researchers plan the collection and analysis of health utility data in clinical studies in order to provide high quality HSU estimates appropriate for economic. This short course provides an opportunity to review and discuss the content of the guideline, with a view to improving the effectiveness of utility data measurement in clinical studies. The focus will be on optimizing the collection of utility data to provide HSU estimates for economic models. Specifically, the course will address key challenges surrounding study design, data collection and analysis. This will include how to anticipate and address common issues that may affect data quality, alignment with the needs of economic model, acceptability to the model audience, and how to apply good research practices for HSU estimation in future research. The course will not cover the fundamentals of utility theory, the development of generic or condition-specific preference-based multi-attribute utility instruments, or how to perform time trade-off or standard gamble experiments. Nor will it cover statistical methods for mapping/cross-walking from a condition-specific HRQL measure. The course will be of value for researchers actively involved in the design or implementation of HSU data collection or analysis, those involved in patient-reported outcomes research, economic modeling, economic evaluation or health technology assessment.
Patient-Reported Outcomes - Item Response Theory
 
Sunday, May 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Constitution A-2nd Floor
Track: Patient-Reported Outcomes Methods
Level: Introductory This course is designed for those with little to no experience with Item Response Theory (IRT).
Faculty:
Bryce B. Reeve, PhD Bryce B. 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 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Back Bay B-2nd Floor
Track: Observational Data Methods
Level: Intermediate This course is suitable for those with some knowledge of econometrics.
Prerequisite: Previous attendance at the ISPOR short course, “Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources”, or equivalent knowledge, is recommended.
Faculty:
Benjamin M. Craig, PhD Benjamin M. Craig, PhD, Associate Professor, Department of Economics, University of South Florida and Assistant Member, Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA
Bradley C. Martin, PharmD, PhD, RPh Bradley C. Martin, PharmD, PhD, RPh, Professor & Head, Division of Pharmaceutical Evaulation 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 & Head, Market Access and Accounts Value Management, Janssen GCC, Dubai, United Arab Emirates
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 randomized controlled trials (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 21, 2017
8:00 AM - 12:00 PM
Room: Sheraton-Independence-2nd Floor
Track: Economic Methods
Level: Intermediate 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 & Chair, Pharmaceutical Health Services Research, University of Maryland, School of Pharmacy, Baltimore, MD, USA
Stephanie R. Earnshaw, PhD, MS Stephanie R. 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 21, 2017 - Afternoon Session
Introduction to Big Data Analysis: Graph Analytics
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay B-2nd Floor
Track: Observational Data Methods
Level: Intermediate
Faculty:
David R. Holmes III, PhD David R. Holmes III, PhD, Director, Biomedical Imaging Resource and 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 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Independence-2nd Floor
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 “Introduction to Budget Impact Analysis: A 6-Step Approach,” or equivalent knowledge, is recommended. Knowledge of Excel is highly recommended.
Faculty:
Stephanie R. Earnshaw, PhD, MS Stephanie R. Earnshaw, PhD, MS, Vice President, Health Economics, RTI Health Solutions, Research Triangle Park, NC, USA
Anita J. Brogan, PhD Anita J. Brogan, PhD, Head, Decision-Analytic Modeling, RTI Health Solutions, Research Triangle Park, NC, USA
Thor-Henrik Brodtkorb, PhD Thor-Henrik Brodtkorb, PhD, Senior Director, Health Economics, RTI Health Solutions, Ljungskile, Sweden
Course Description:
This course provides an opportunity for participants to engage with concrete applications of the six-step approach for developing budget impact analyses and to participate in hands-on learning with two different budget impact models programmed in Excel. The course will review the basics of budget impact analysis, interpretation of results, critical questions to consider when using a budget impact analysis, and how such analyses are used by payers and other decision makers. The course will cover technical topics such as use of static versus dynamic budget impact models, considerations for budget impact analyses of device and diagnostic technologies, and how to handle important issues such as patient copayments and use of generics. To help participants engage with the course content, the instructors will walk through two different budget impact analyses programmed in Excel (one static and one dynamic), work with participants on hands-on exercises to enhance these models, present conceptual content, and lead discussion on various topics. The instructors will also review good practices for building budget impact models and provide a number of Excel tips. The Excel-based budget impact models used for the course will be provided to participants in advance of the conference. Participants who wish to gain hands-on experience must bring their personal laptops with Microsoft Excel for Windows installed.
Sold Out NEW! US Payers – an Introduction to Their Structures, Evidence Needs, and Decision-Making Process
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay C-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory This course is designed for those having minimal experience in understanding differences in perspectives and evidence needs for various access decision makers in the US Health Care system.
Faculty:
Priti Jhingran, PhD Priti Jhingran, PhD, Independent Consultant, HEOR, Plainsboro, NJ, USA
Ambarish J. Ambegaonkar, PhD Ambarish J. Ambegaonkar, PhD, Managing Partner, APPERTURE LLC., Marlboro, NJ, USA
Helen Sherman, PharmD, RPh Helen Sherman, PharmD, RPh, Area Vice President, Solid Benefit Guidance, Portland, OR, USA
Course Description:
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In a dynamic US Healthcare environment where value, quality, and cost management are key strategic priorities for access decision makers, focus on value evidence and outcomes has increased significantly. Mechanisms are being put in place to drive quality of care, improved patient centric and economic outcomes at the population health level. This requires individuals to focus on outcomes based value conversations with traditional public (Medicare, Medicaid, Veteran Administration, and Department of Defence, etc.) and private (regional and national health plans) payers, in addition to emerging access decision makers such as Provider Networks, Integrated Delivery Networks, Accountable Care Organizations, Patient Center Medical Homes, Pathways organizations, Oncology Care Models, etc. The intent of this course is to better understand characteristics of various access decision makers within the US Healthcare system, understand the scope and perspectives as well as their outcomes evidence needs. This session will facilitate the increased level of competency needed to adapt the communication of outcomes evidence to various access decision makers and enhance evidence driven access decision making.

Network Meta-Analysis
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Constitution A-2nd Floor
Track: Outcomes Research Methods
Level: Intermediate This course requires at least a basic knowledge of meta-analysis and statistics.
Prerequisite: The ISPOR 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:
Jeroen P. Jansen, PhD, MSc Jeroen P. Jansen, PhD, MSc, Vice President & Chief Scientist, Evidence Synthesis and Decision Modeling, Precision Health Economics, Oakland, CA, USA
Joseph C. Cappelleri, MS, MPH, PhD Joseph C. Cappelleri, MS, MPH, PhD, Senior Director of Biostatistics, Pfizer Inc., Groton, CT, 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 know how all the treatment options rank against each other and the level of differences in treatment effects between all the available options. Network meta-analysis provides an integrated and unified method that incorporates all direct and indirect comparative evidence about treatments. Based in part on the ISPOR Task Force Reports on Indirect Treatment Comparisons, the fundamentals and concepts of network meta-analysis will be presented. The evaluation of networks presents special challenges and caveats, which will also be highlighted in this course. The material is motivated by instructive and concrete examples. The ISPOR-AMCP-NPC questionnaire for assessing the credibility of a network meta-analysis will also be introduced.
Advanced Decision Modeling for Health Economic Evaluations
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay A-2nd Floor
Track: Modeling Methods
Level: Advanced Participants should have an understanding of decision analysis.
Prerequisite: Previous attendance at the ISPOR Short Course, “Modeling: Design and Structure of a Model,” or equivalent knowledge, is required.
Faculty:
Andrew Briggs, DPhil Andrew Briggs, DPhil, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, University of Glasgow, Glasgow, UK
Mark Sculpher, PhD Mark Sculpher, PhD, Professor of Health Economics, Centre for Health Economics & Director, University of York, Heslington, York, 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.
Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Constitution B-2nd Floor
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory The course is designed for those unfamiliar with MCDA, but who have a basic understanding of other evaluation methodologies.
Faculty:
Maarten J. IJzerman, PhD Maarten J. IJzerman, PhD, Professor, Department of Health Technology & Services Research, University of Twente, Enschede, The Netherlands
Kevin Marsh, PhD Kevin Marsh, PhD, Executive Director, Evidera, London, UK
Nancy Devlin, PhD Nancy Devlin, PhD, Director of Research, Office of Health Economics, London, UK
Course Description:
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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 trade-offs 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 provides an introduction to MCDA for health care. The course will focus on the use of MCDA for HTA, and will be organised around the following parts: 1) Introduction to MCDA: What is it and how is it being use in HTA?; 2) Implementing MCDA 1: Practical tips when implementing MCDA; 3) Implementing MCDA 2: Methodological options when designing an MCDA; and 4) Using MCDA for HTA. Challenges and possible solutions. These parts are designed to familiarise participants with the steps involved in undertaking an MCDA, the alternative ways of implementing these steps, and good practice guidelines. The course will also review the current MCDA HTA landscape, including current use of MCDA for HTA and the challenges this poses. The course is designed for those unfamiliar with MCDA, but who have a basic understanding of other evaluation methodologies.

Advanced Topics in Decision Analytic Modeling
 
Sunday, May 21, 2017
1:00 PM - 5:00 PM
Room: Sheraton-Back Bay D-2nd Floor
Track: Modeling Methods
Level: Advanced This course is designed for those with basic understanding of decision analytic modeling and interested in building relatively complex models.
Prerequisite: Participation in the ISPOR short course, “Introduction to Modeling Methods,” or equivalent knowledge, is recommended and basic understanding of calculus and statistics is helpful, but is not required.
Faculty:
Jagpreet Chhatwal, PhD Jagpreet Chhatwal, PhD, Assistant Professor, Radiology, Harvard Medical School and Senior Scientist, Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA
Elamin H. Elbasha, PhD, MA Elamin H. Elbasha, PhD, MA, Distinguished Scientist, Outcomes Research, Merck Research Laboratories, North Wales, PA, USA
Course Description:
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Decision analytic models are commonly used in pharmacoeconomics and medical decision making. For example, a decision to reimburse a new pharmaceutical is typically informed by an economic evaluation such as a cost-effectiveness analysis. The basis of such an economic evaluation is usually a decision analytic model (e.g., a Markov model). The choice of a modeling technique—cohort versus individual-level (microsimulation, discrete event simulation or agent-based modeling), static versus dynamic, and continuous- versus discrete-time—can influence the results. In addition, incorrect modeling assumptions can also result in misleading outcomes. Faculty will highlight a few typical mistakes that can lead to biases in the outcomes of interest and provide advanced methods to avoid such mistakes, which could be unavoidable with commonly used software. The course will also review the recommendations of the ISPOR-SMDM Modeling Good Research Practices Task Force. This course will cover advanced topics in the following three modeling approaches: cohort-based models, patient-level models, and population-based models, and is divided in five modules. This course is intended to fill such training gaps in the field of pharmacoeconomics. The course will include a combination of didactic lectures, discussions and hands-on exercises. Several tools will be made available to participants for practical implementation of the covered topics. Participants are required to bring personal laptops equipped with software provided to course registrants.

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