ISPOR 19th Annual European Congress 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 19th Annual European Congress 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, 29 October 2016 - Full Day
Introduction to Health Economic / Pharmacoeconomic Evaluations
 
Saturday, 29 October 2016
9:00 - 18:00
Room: Hall E1 (L0)
Track: Economic Methods
Level: Introductory This course is suitable for those with little or no experience with pharmacoeconomics.
Faculty:
Lieven Annemans, PhD, MSc Lieven Annemans, PhD, MSc, Senior Full Professor of Health Economics, ICHER (Interuniversity Center for Health Economics Research), Ghent University - Brussels University, Ghent, Belgium
Course Description:
This course is designed to teach health care professionals, industry executives and new researchers how to incorporate health economics/pharmacoeconomics into the development of innovations in health care. Participants will review the basic principles and concepts of health economic evaluations, and discuss how to collect and calculate data on costs and effects of different alternatives. Both modeling techniques and prospective health economic evaluations are discussed. Special attention is moreover given to specific issues such as uncertainty analyses, discounting, perspective of the analysis, and to how health economic evaluations are important within the entire life cycle of health innovations.
Saturday, 29 October 2016 - Morning Session
Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall E2 (L0)
Track: Observational Data Methods
Level: Introductory
Faculty:
Linus Jönsson, PhD, MD, MSc Linus Jönsson, PhD, MD, MSc, Vice President, Medical Affairs & Clinical Development Centres, H. Lundbeck A/S, Valby, Denmark
Bradley C. Martin, PharmD, PhD, RPh Bradley C. Martin, PharmD, PhD, RPh, 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 using 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 Patient-Reported Outcomes Assessment: Instrument Development & Evaluation
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall K1 (L -2)
Track: Patient-Reported Outcomes Methods
Level: Introductory This is an entry level course which assumes only a passing familiarity with patient-reported outcomes.
Faculty:
Kellee Howard, MA, MSc Kellee Howard, MA, MSc, Senior Principal, Clinical Outcomes Assessments, ICON Commercialisation and Outcomes, San Francisco, CA, USA
Jennifer Petrillo, PhD Jennifer Petrillo, PhD, Associate Director, HEOR, Global Market Access, Biogen, Cambridge, MA, USA
Helen A Doll, MSc, DPhil Helen A Doll, MSc, DPhil, Senior Principal, Clinical Outcomes Assessment, ICON Commercialisation and Outcomes, San Francisco, CA, USA
Course Description:
Patient-reported outcomes (PROs) are widely used to evaluate the impact of health technologies, practice innovations, or changes in health policy from the patients' perspective. This course is designed to familiarize people with the range and scope of what PROs are used for, how they are developed and evaluated, what they measure, and how PRO data can be used to support licensing and reimbursement applications.  This includes generic and disease-specific measures of health-related quality of life (HRQL) as well as measures of patient preference, systems, functioning, utility, and treatment satisfaction. The faculty will describe the steps that researchers generally go through in order to develop and test a new PRO. This will include qualitative work, item generation and testing, and then validation. Finally, in the last hour, faculty will frame this in terms of what the FDA and EMEA expect to see when PROs form an important part of a licensing submission. In addition, we will describe the approach of bodies such as NICE and how they review PRO data and use it to guide reimbursement decisions.
Introduction to Modeling
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall K2 (L -2)
Track: Modeling Methods
Level: Introductory This course is designed for those with some familiarity with modeling techniques.
Faculty:
Uwe Siebert, MD, MPH, MSc, ScD Uwe Siebert, MD, MPH, MSc, ScD, Professor & Chair, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Austria, Adjunct Professor, Health Policy and Management, Harvard School of Public Health, Boston, MA, USA, and Director, Division for HTA, ONCOTYROL – Center for Personalized Cancer Medicine, Hall i.T., Austria
Course Description:
This course gives a brief overview of different decision-analytic model types and provides an introduction to Markov modeling techniques and their practical application in economic evaluation and outcomes research. Faculty will present analytic approaches including deterministic cohort simulation and Monte Carlo microsimulation, and will provide some technical instructions for modelers. Participants learn about the concepts of variability, uncertainty, probabilistic sensitivity analysis (PSA), and cost-effectiveness acceptability curves (CEAC). Additionally, faculty will use the recommendations of the ISPOR-SMDM Joint Modeling Good Research Practices Task Force to explore when and how modeling should be used in economic evaluation and which are the suitable model techniques.

Statistical Methods for Pharmacoeconomics & Outcomes Research
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall G1 (L -2)
Track: Economic Methods
Level: Introductory This course is intended for participants with little (or rusty!) statistical training.
Faculty:
James Lewsey, PhD James Lewsey, PhD, Reader, Medical Statistics and Director for HTA, Health Economics and Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
Gerd K. Rosenkranz, PhD Gerd K. Rosenkranz, PhD, Professor, Applied Mathematics, Probability Theory, Statistics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria
Course Description:
This course will provide an introduction to statistical concepts with an emphasis on the use of techniques commonly employed in pharmacoeconomics and outcomes research.  Faculty will begin by introducing the concept of random variables and will then proceed to discuss the foundations of statistical estimation and the testing of hypotheses, followed by a discussion of the importance of correlating between variables and the use of regression techniques. The differences between a classical (frequentist) approach to statistics and a Bayesian view of probability will also be outlined.
Development of Conceptual Models
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall G2 (L -2)
Track: Modeling Methods
Level: Introductory
Faculty:
Neil Hawkins, PhD, CStat Neil Hawkins, PhD, CStat, Professor of HTA, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
Elisabeth Fenwick, PhD Elisabeth Fenwick, PhD, Principal, ICON Health Economics and Epidemiology, Abingdon, UK
Paul Tappenden, PhD, MSc Paul Tappenden, PhD, MSc, Reader in Health Economic Modelling, Health Economics and Decision Science (HEDS), School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
Beth Woods, MSc Beth Woods, MSc, Research Fellow, Team for Economic Evaluation and Health Technology Assessment (TEEHTA), Centre for Health Economics, University of York, Heslington, York, UK
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:
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.
Elements of Pharmaceutical / Biotech Pricing
 
Saturday, 29 October 2016
9:00 - 13:00
Room: Hall F1 (L0)
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 will cover 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, 29 October 2016 - Afternoon Session
Introduction to Health Technology Assessment
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall F1 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory This course is suitable for those with little or no experience with HTA.
Faculty:
Uwe Siebert, MD, MPH, MSc, ScD Uwe Siebert, MD, MPH, MSc, ScD, Professor & Chair, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Austria, Adjunct Professor, Health Policy and Management, Harvard School of Public Health, Boston, MA, USA, and Director, Division for HTA, ONCOTYROL – Center for Personalized Cancer Medicine, Hall i.T., Austria
Course Description:
This introductory course is designed to teach academic researchers, health policy decision makers, manufacturers, and clinicians about the key elements, methods, and language of health technology assessment (HTA). The course provides an overview of basic HTA principles including benefit assessment (biostatistics, clinical epidemiology, patient-relevant outcomes, risk-benefit assessment), economic evaluation (costing, cost-effectiveness analysis, pharmacoeconomic modeling, budget impact analysis, resource allocation), and ELSI (ethical, legal, and social implications). Using real world examples covering both drugs and devices, the course will review the practical steps involved in developing and using HTA reports in different countries and health care systems. Group discussion will focus on the perspectives of different stakeholders and the implementation of HTA in health care decision making.
Meta-Analysis & Systematic Literature Review
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall G2 (L -2)
Track: Outcomes Research Methods
Level: Intermediate
Prerequisite: Previous attendance at the ISPOR short course, “Statistical Methods for Pharmacoeconomics & Outcomes Research”, or equivalent knowledge, is recommended.
Faculty:
Olivia Wu, PhD Olivia Wu, PhD, Professor & Director, HEHTA Research Unit, Health Economics and Health Technology Assessment, University of Glasgow, Glasgow, UK
Neil Hawkins, PhD, CStat Neil Hawkins, PhD, CStat, Professor of HTA, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
Course Description:
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. A systematic literature review often includes meta-analysis and involves an explicit, detailed description of how a review was conducted. This course highlights and expounds upon four key areas: 1) impetus for meta-analysis and systematic reviews; 2) basic steps to perform a quantitative systematic review; 3) statistical methods of combining data; and 4) an introduction to methods for indirect comparisons. The material includes practical examples from the published literature relevant to pharmacoeconomic and PRO research. This course is designed for those with little experience with meta-analysis and includes interactive exercises. Participants who wish to gain hands-on experience must bring their personal laptops with Microsoft Excel for Windows installed.
Cost-Effectiveness Analysis Alongside Clinical Trials
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall G1 (L -2)
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, Cancer Prevention Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center and Professor, School of Medicine, School of Pharmacy, and the Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
Richard J. Willke, PhD Richard J. Willke, PhD, Chief Science Officer, International Society for Pharmacoeconomics and Outcomes Research (ISPOR), 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 all be presented. Trials designed to evaluate effectiveness (rather than efficacy), as well as clinical outcome measures, will also be discussed, including how to obtain health resource use and health state utilities directly from study subjects and economic data collection fully integrated into the study. 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.
Use of Propensity Scores in Observational Studies of Treatment Effects
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall E2 (L0)
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 and Assistant Professor, Division of Pharmacoepidemiology and Pharmacoeconomics, Harvard Medical School/Brigham and Women's Hospital, Boston, MA, USA
Rishi Desai, MS, PhD Rishi Desai, MS, PhD, Instructor of Medicine, Harvard Medical School and Associate Epidemiologist, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA, 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.
NEW! Collecting Health-State Utility Estimates for Economic Models in Clinical Studies
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall K2 (L -2)
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, Head, European Health Economics, 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, Patient-Reported Outcomes, 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 (http://www.ispor.org/Estimating-Health-State-Utility-Economic-Models-Clinical-Studies-guidelines.aspto 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.
Pharmacoeconomic Modeling – Applications
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall K1 (L -2)
Track: Modeling Methods
Level: Intermediate
Prerequisite: Previous attendance at, or familiarity with the topics discussed in the ISPOR short course, “Introduction to Modeling”, is required.
Faculty:
Shelby L. Corman, PharmD, MS, BCPS Shelby L. Corman, PharmD, MS, BCPS, Associate 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, Universtiy 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.
Patient Registries
 
Saturday, 29 October 2016
14:00 - 18:00
Room: Hall F2 (L0)
Track: Observational Data Methods
Level: Introductory This course is designed for those with some or no experience with patient registries.
Faculty:
Leanne Larson, MHA Leanne Larson, MHA, Vice President & Global Head, Observational Research, PAREXEL International, Waltham, MA, USA
Angela Vinken, MSc Angela Vinken, MSc, Senior Director, Observational Research, PAREXEL International, Amsterdam, The Netherlands
Course Description:
This course is designed to provide an overview of patient registries and their applications in identifying real world clinical, safety, and patient-perspective issues. The advantages and disadvantages of patient registry versus other real world data collection will be presented. The course will address safety and clinical objectives as well as regulatory trends and requirements. Key operational components, challenges, and measures of program success will be discussed. Management issues, including creating effective partnerships with patient-oriented organizations and facilitating long-term program operations within a changing organizational structure, will be addressed.
Sunday, 30 October 2016 - Full Day
Bayesian Analysis – Overview and Applications
 
Sunday, 30 October 2016
8:00 - 17:00
Room: Hall G1 (L -2)
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, Penn State College of Medicine, Hershey, PA, USA
Keith R. Abrams, PhD Keith R. Abrams, PhD, Professor of Medical Statistics, Department of Health Sciences, University of Leicester, Leicester, UK
Course Description:
The first portion of this course is designed to provide an overview of the Bayesian approach and its applications to health economics/pharmacoeconomics 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 a series of exercises 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 encouraged to bring their personal laptops equipped with software provided to course registrants.
Sunday, 30 October 2016 - Morning Session
Using DICE Simulation for Health Economic Analyses
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall G2 (L -2)
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
Jorgen Moller, MSc, Mech Eng Jorgen Moller, MSc, Mech Eng, Vice President, Modelling Technologies and Simulation, 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 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.
Use of Instrumental Variables in Observational Studies of Treatment Effects
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall K1 (L -2)
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 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 & 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.
Mixed Methods Approaches for Patient-Centered Outcomes Research: Group Concept Mapping
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall K2 (L -2)
Track: Patient-Reported Outcomes Methods
Level: Advanced This course assumes a basic understanding of qualitative interviewing methods and measurement properties of patient-reported outcomes (PRO) instruments.
Faculty:
Louise Humphrey, MSc Louise Humphrey, MSc, Director, Clinical Outcomes Assessment (COA), Clinical Outcomes Solutions Ltd., Manchester, UK
Helen Kitchen, MSc Helen Kitchen, MSc, Senior Consultant & Specialist Team Lead, Clinical Outcomes Assessment, DRG Abacus, Manchester, UK
Sarah L Shingler, MSc Sarah L Shingler, MSc, Consultant, Clinical Outcomes Assessment, Decision Resource Group (DRG), Oxfordshire, UK
Course Description:
Mixed methods approaches are increasingly acknowledged by both regulatory authorities and the wider scientific community as an important part of the outcomes researcher’s toolkit. Yet there is currently a lack of guidance on how to conduct mixed methods research. This course will guide participants through the different approaches to mixed methods and in particular will expand upon Group Concept Mapping (GCM) – a structured, mixed methods approach ideal for eliciting patient insight into their own disease and treatment experiences and understanding what is most important or burdensome from the patients’ perspective. GCM is a method that can be conducted online and performed in small samples, making it both convenient and cost-effective. Moreover, GCM methodology can be used beyond patient settings and is advocated for use in a diverse range of situations where complex decision making is required and the views of multiple stakeholders must be considered. The benefits and limitations of the innovative GCM approach will be discussed in context of FDA Guidance for Industry – Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims, and EMA Reflection Paper on the Regulatory Guidance on the Use of Health-Related Quality of Life (HRQL) Measures in the Evaluation of Medicinal Products. The course will also reference ISPOR Good Research Practices for Evaluating and Documenting Content Validity for the Use of Existing Instruments and Their Modifications PRO Task Force Report. During this short course, participants will take part in a practical exercise giving them real-life experience in conducting and analyzing GCM and allowing them to understand the methodology from the perspective of both a participant and a researcher.
Transferability of Cost-Effectiveness Data Between Countries
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall E1 (L0)
Track: Economic Methods
Level: Advanced This course is for those with advanced understanding of economic evaluations of health care programs and experience in the critical assessment of cost-effectiveness studies.
Faculty:
Silvia Evers, PhD, LLM Silvia Evers, PhD, LLM, Professor of Public Health Technology Assessment, Department of Health Services Research, CAPHRI School for Public Health and Primary Care and Netherlands School of Primary Care Research (CaRe), Maastricht University, Maastricht, The Netherlands
Manuela A. Joore, PhD Manuela A. Joore, PhD, Professor of Health Technology Assessment & Decision Making, Department of Clinical Epidemiology and Medical Technology Assessment, School for Public Health and Primary Care (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Center, Maastricht University, Maastricht, The Netherlands
Course Description:
Although the number of countries requiring an economic dossier as part of the submission dossier for public reimbursement of new drugs is growing, the pharmaceutical industry cannot conduct economic evaluations in every potential market. However, national decision makers require country-specific or region-specific data or relevant estimates on health care costs and patient outcomes. More and more, they are only willing to accept foreign or international data when transferable to their own decision-making context. However, little guidance exists on how to do this. This course starts with a discussion of factors that make economic data more difficult to transfer from one country to another than clinical data, and will focus on the report of the ISPOR Good Practices on Economic Data Transferability Task Force. In this respect, faculty will discuss the transferability of health state valuations based on the EQ-5D instrument and the transferability of lost productivity data. Next, faculty will review the methods that have been presented to assess the transferability of foreign cost, effects, and cost-effectiveness estimates and their pros and cons. This topic will be practically covered in a case-study while working in small groups. A stepwise procedure will illustrate how to select a foreign cost-effectiveness model for adaptation to your own decision-making context. Finally, a detailed approach on how to adapt a cost-effectiveness model calculation will be illustrated using the case of breast cancer treatment. During the course, faculty will present transferring issues encountered when assessing model-based economic evaluations.

Please note: The statistical methods used to analyze multinational trial data and to transfer these data to a specific country are beyond the scope of this course

Conjoint Analysis – Theory & Methods
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall E2 (L0)
Track: Patient Preference Methods
Level: Intermediate This course is designed for clinicians, policymakers, researchers, and patient advocates/researchers with some familiarity with conjoint analysis or other stated-preference methods.
Faculty:
A. Brett Hauber, PhD A. Brett Hauber, PhD, Senior Economist & Vice President, Health Preference Assessment, RTI Health Solutions, Research Triangle Park, NC, USA
Juan Marcos Gonzales, PhD Juan Marcos Gonzales, PhD, Senior Research Economist, Health Preference Assessment, RTI Health Solutions, Research Triangle Park, NC, USA
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. The course 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. The course will include lectures and interactive group exercises and group discussion.
Budget Impact Analysis I: A 6-Step Approach
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall D (L -2)
Track: Economic Methods
Level: Intermediate This course is designed for those with some experience with pharmacoeconomic analysis.
Faculty:
Stephanie R. Earnshaw, PhD, MS Stephanie R. Earnshaw, PhD, MS, 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
Anita J Brogan, PhD Anita J Brogan, PhD, Head, Decision-Analytic Modeling, 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.
Risk-Sharing / Performance-Based Arrangements for Drugs and Other Medical Products
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall F1 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Prerequisite: It would be helpful for individuals taking this course to have completed the ISPOR short course, “Elements of Pharmaceutical/Biotech Pricing”, or to be familiar with both the key determinants of pharmaceutical pricing and the main international health sys
Faculty:
Louis P. Garrison, PhD Louis P. 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
Paolo Daniele Siviero, MSc Paolo Daniele Siviero, MSc, Senior Advisor & Fund Manager, Principia III, Rome, Italy
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! Understanding Survival Modeling with Application to HTA
 
Sunday, 30 October 2016
8:00 - 12:00
Room: Hall F2 (L0)
Track: Modeling Methods
Level: Intermediate
Faculty:
Andrew Briggs, DPhil Andrew Briggs, DPhil, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, University of Glasgow, Glasgow, UK
Christopher Parker, MSc Christopher Parker, MSc, Senior Health Economist, ICON Health Economics & Epidemiology, Abingdon, UK
Andrew Davies, MSc Andrew Davies, MSc, Principal Health Economist, ICON Health Economics & Epidemiology, Oxford, UK
Course Description:
Time-to-event (survival) analysis is an important element in many economic analyses of health care technologies. This is particularly true in oncology given the requirement to estimate lifetime costs and outcomes (i.e. extrapolate) beyond the follow-up typically observed in clinical trials. Cost-effectiveness estimates can be sensitive to the methods applied in modelling survival data. Recommendations for selecting a parametric survival model have been recently been published; following a review of extrapolation modelling in National Institute for Health and Care Excellence (NICE) technology appraisals. The purpose of this course is to provide participants with an understanding of the fundamentals of survival analysis and key issues to be considered when comparing alternative survival models for inclusion in cost-effectiveness analysis. This will include an understanding of differences between partitioned survival and Markov-based approaches.
Sunday, 30 October 2016 - Afternoon Session
Budget Impact Analysis II: Applications & Design Issues
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall D (L -2)
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: Previous attendance at, or familiarity with the topics discussed in, the ISPOR short course “ Budget Impact Analysis I: A 6-Step Approach” is 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 modify and complete these models, present conceptual content, and lead discussion on various topics. The instructors will also discuss 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.
NEW! Advanced Methods for Addressing Selection Bias in Real-World Effectiveness and Cost-Effectiveness Studies
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall K1 (L -2)
Track: Observational Data Methods
Level: Intermediate
Faculty:
Richard Grieve, PhD Richard Grieve, PhD, Professor of Health Economics Methodology, London School of Hygiene and Tropical Medicine, London, UK
Noemi Kreif, PhD Noemi Kreif, PhD, Assistant Professor, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
Course Description:
Reimbursement agencies require real-world evidence on the effectiveness and cost-effectiveness of new drugs and medical devices. In many settings, randomised controlled trial (RCT) data is unavailable or insufficient. Where non-randomised data is used to estimate treatment effectiveness and cost-effectiveness, the main methodological challenge is selection bias from confounding by indication. Standard regression or propensity score methods are frequently used to adjust for selection bias, but estimates of treatment effectiveness may be highly sensitive to the chosen parametric form of these models, and evidence that relies on such methods may be viewed as insufficient by reimbursement agencies. While new, more advanced methods for allowing for confounding cannot offer a panacea, they have been shown to provide estimates of treatment effectiveness that are relatively robust. This course offers an in-depth description of ‘cutting edge’ methods for addressing this form of selection bias. These methods include flexible regression which uses machine learning for model selection, propensity score matching with regression adjustment, and Genetic Matching, a recently developed approach that extends propensity score matching. The course introduces the participants to these methods using the R software, through a series of real world data examples. Faculty will also demonstrate sensitivity analyses that convey to decision makers the extent to which the estimates of effectiveness and cost-effectiveness are robust to that assumption of no unobserved confounding. Participants who wish to have hands-on experience must bring their personal laptops with appropriate software installed.
Introduction to the Economic Analysis of Diagnostics
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall E1 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Faculty:
John E. Schneider, PhD John E. Schneider, PhD, Chief Executive Officer & Founder, Avalon Health Economics, Morristown, NJ, USA
Andrew Briggs, DPhil Andrew Briggs, DPhil, William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, University of Glasgow, Glasgow, UK
Course Description:
There has been dramatic progress in the science and applications of diagnostics in recent years, especially in the areas of molecular and genomic diagnostics and personalized medicine. The new generation of tests offers opportunities to improve patient care and treatment outcomes. However, there remain a number of challenges in translating technological advances in diagnostics to improved patient care, and the impact of the new generation of diagnostics on the costs of care and payer budgets is variable. One of those challenges is establishing the economic value of new tests. The economic evaluation of diagnostics follows the same basic structure of any economic evaluation of medical care interventions, but has several important additional considerations, including clinical decision making, test applications, test performance, tested populations, outcome measurement, data, and evidence requirements. This course is designed to expand upon economic evaluation of diagnostic devices, including companion diagnostics, molecular diagnostics, rapid point-of-care tests, and so on.
Network Meta-Analysis in Relative Effectiveness Research
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall K2 (L -2)
Track: Outcomes Research Methods
Level: Intermediate This course requires at least a basic knowledge of meta-analysis and statistics.
Faculty:
Jeroen P. Jansen, PhD, MSc Jeroen P. Jansen, PhD, MSc, Chief Scientist, Evidence Synthesis and Decision Modeling, Precision Health Economics, San Francisco, CA, USA
Steve Kanters, MSc Steve Kanters, MSc, Director, Health Analytics, Precision Health Economics, 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 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.
Risk-Sharing/Performance-Based Arrangements in Central & Eastern Europe: Implementation of Managed Entry Agreements
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall F1 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Faculty:
Zoltán Kaló, PhD Zoltán Kaló, PhD, Professor of Health Economics, Eötvös Loránd University (ELTE), Budapest, Hungary
Rok Hren, PhD, MSc IHP (HE) Rok Hren, PhD, MSc IHP (HE), Professor, University of Ljubljana, Ljubljana, Slovenia
Katarzyna Kolasa, PhD Katarzyna Kolasa, PhD, Market Access Director Region East, Lundbeck, Warszawa, Poland and Department of Health Economics, Collegium Medicum, The Nicolaus Copernicus University, Bydgoszcz, Poland
Course Description:
During the recent years, Managed Entry Agreements (MEAs) have become instrumental in ensuring the access of the innovative medicines. This course is designed for health care professionals (including public decision-makers, academia and industry) involved in pricing and reimbursement decisions who are wishing to understand the applicability and technical aspects of managed entry agreements (MEAs) in countries with severe economic constraints and explicit cost-effectiveness criterion. The topic will be introduced with key features of pricing and reimbursement systems in Central-Eastern European countries to understand why special methods are needed to facilitate evidence-based reimbursement policies of new health technologies.  Faculty will present an economic model to explain the methodology and implications of managed entry agreements in cost-effectiveness and budget impact analysis. Participants will then have the opportunity to apply what they have learned through a hands-on exercise on making pricing and reimbursement decisions. A decision algorithm will be presented to support evidence and value based policy decisions of high-cost new technologies in CEE countries. A series of password protected economic models will add more and more complexity to a pragmatic case study on a new pharmaceutical product in oncology. To close the course faculty will lead a discussion on the applicability of a pragmatic decision tool illustrating the pros and cons of different managed entry agreements and their usefulness in CEE settings. Participants who wish to gain hands-on experience must bring their laptops with Microsoft Excel for Windows installed.
NEW! Adjusting for Time-Dependent Confounding and Treatment Switching Bias in Observational Studies and Clinical Trials: Purpose, Methods, Good Practices and Acceptance in HTA
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall G2 (L -2)
Track: Observational Data Methods
Level: Intermediate
Faculty:
Uwe Siebert, MD, MPH, MSc, ScD Uwe Siebert, MD, MPH, MSc, ScD, Professor & Chair, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Austria, Adjunct Professor, Health Policy and Management, Harvard School of Public Health, Boston, MA, USA, and Director, Division for HTA, ONCOTYROL – Center for Personalized Cancer Medicine, Hall i.T., Austria
Nicholas Latimer, MSc, PhD Nicholas Latimer, MSc, PhD, Senior Research Fellow, Health Economics, ScHARR, University of Sheffield, Sheffield, UK
Felicitas Kühne, MSc Felicitas Kühne, MSc, Senior Scientist, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT, Hall i.T., Austria
Course Description:
In specific situations, clinical studies need causal inference methods to estimate a valid causal effect of a health intervention. Causal adjustment is needed if there is confounding-by-indication in observational studies or when ITT analyses lead to biased effect estimates in RCTs with noncompliance/treatment switching. Since first HTA agencies have accepted and requested the use of causal methods, a paradigm shift is taking place, and the selection of the appropriate method has become crucial to yield patient access to innovative treatments. This course will (1) introduce causal diagrams as a tool for causal assessment, (2) give an overview on causal methods (e.g., rank preserving structural failure time models, marginal structural models, two-stage approach), (3) present lessons learned from applied cases examples in HTA, (4) provide recommendations regarding when to use which methods, and (5) discuss acceptance and barriers from an HTA agency perspective.
Reimbursement Systems for Pharmaceuticals in Europe
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall E2 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate This course is designed for individuals with intermediate experience within a single health care system wishing to broaden their appreciation of other reimbursement systems.
Faculty:
Mondher Toumi, MD, PhD, MSc Mondher Toumi, MD, PhD, MSc, Professor, Public Health, Faculté de Médecine, Laboratoire de Santé Publique, Aix-Marseille Université, Université de la Méditerranée, Marseille, France
Course Description:
Unlike marketing authorization for pharmaceuticals, mainly regulated at the European level by EMA, pricing and reimbursement decisions in Europe are managed by individual member states. Health care services are generally covered by a single public health insurer operating under the Ministry of Health supervision. As a monopoly buyer, this situation provides a leading position for the public health insurer to set reimbursement conditions. Therefore, based on each country’s set of regulations, processes, and values, wide variations exist in pricing and reimbursement decisions of pharmaceuticals. Using up-to-date governmental regulation sources and the ISPOR Global Health Care Systems Roadmap, this course will discuss health technology decision-making processes for reimbursement decisions for pharmaceuticals in France, Germany, Hungary, Italy, Poland, Spain, Sweden, and the UK. The course will describe these reimbursement systems, as well as compare, and bring into contrast their key characteristics.
Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications
 
Sunday, 30 October 2016
13:00 - 17:00
Room: Hall F2 (L0)
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory Participants should have an understanding of decision analysis.
Faculty:
Maarten IJzerman, PhD Maarten IJzerman, PhD, Professor and Head, Department of Health Technology & Services Research, University of Twente, Enschede, The Netherlands
Nancy Devlin, PhD Nancy Devlin, PhD, Director of Research, Office of Health Economics, London, UK
Martina Garau Martina Garau, Senior Economist, Office of Health Economics, London, 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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