ISPOR Europe 2018 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 Europe 2018 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, 10 November 2018 - Full Day
Introduction to Health Economic Evaluations Register Now
 
Saturday, 10 November 2018
8:00 - 17:00
Room: TBD
Track: Economic Methods
Level: Introductory This course is suitable for those with little or no experience with pharmacoeconomics.
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, 10 November 2018 - Morning Session
Introduction to the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
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 Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
Track: Patient-Reported Outcomes Methods
Level: Introductory This is an entry level course which assumes only a passing familiarity with patient-reported outcomes.
Faculty:
Kevin Weinfurt, PhD Kevin Weinfurt, PhD, Professor, Department of Psychiatry and Behavioral Sciences and Department of Psychology and Neuroscience, Duke Clinical Research Institute, Durham, NC, 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 of PRO domains and the role they can play in evaluating the effects of healthcare interventions. This includes symptoms (including those that arise as side-effects of treatment), functioning, general health perceptions, and health-related quality of life. The faculty will describe the steps that researchers generally go through in order to develop and test a new PRO measure. This will include qualitative concept elicitation work, item generation, cognitive interviewing, testing measurement models (when appropriate), and finally, assessment of validity and reliability. The course will also cover issues such as the role of the recall period and cultural/linguistic translation of measures.
Introduction to Modeling Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
Track: Modeling Methods
Level: Introductory This course is designed for those with some familiarity with modeling techniques.
Faculty:
Uwe Siebert, Prof, MPH, MSc, ScD, MD Uwe Siebert, Prof, MPH, MSc, ScD, MD, Professor & Chair, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria and Professor, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health. Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA
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.
Development of Conceptual Models Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
Track: Modeling Methods
Level: Introductory
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.
NEW! Tools for Reproducible Real-World Data Analysis Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
Track: Outcomes Research Methods
Level: Introductory
Course Description:
This course will focus on the concepts and tools of reproducible research and reporting of modern data analyses. The need for more reproducible tools in health economics and outcomes research is growing rapidly as analyses of real world data become more frequent, involve larger datasets, and employ more complex computations. This course will cover the principles of structuring and organizing a modern data analysis, literate statistical analysis tools, formal version control, software testing and debugging, and developing reproducible reports. Numerous real-world examples and an interactive class exercise will be used to reinforce the concepts and tools introduced.
Elements of Pharmaceutical/Biotech Pricing Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
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.
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
Conjoint Analysis - Theory & Methods Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
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.
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.
NEW! Introduction to Constrained Optimization Methods for Health Care Research Register Now
 
Saturday, 10 November 2018
8:00 - 12:00
Room: TBD
Track: Modeling Methods
Level: Introductory Attendees should be familiar with the standard techniques of cost-effectiveness analysis.
Course Description:
Instructors will provide an overview of the major steps in formulating a mathematical model, the major types of modelling approaches (e.g. linear/nonlinear, static/dynamic, continuous/discrete, deterministic/stochastic) and how these methods compare to and complement other modelling approaches (e.g. traditional health economic modelling and simulation methods). The short course will also provide an overview of the types of health care problems which can be tackled using CONOPT, and will present the CONOPT checklist developed by the ISPOR Task Force on Constrained Optimization who also contribute to this course as faculty members. The short course is intended to provide an introduction to constrained optimization models. Linear programming is the most straightforward of the CONOPT methods, but also the most fundamental for understanding other techniques that can account for complexities, such as nonlinearities, uncertainty, decisions that unfold dynamically over time, and multiple competing objectives. In addition to discussing a graphical approach to linear programming models, the simplex method will be presented. The simplex method is the most widely used algorithm for solving LPs with large numbers of constraints and inputs. Finally, the course will include a hands-on exercise where students formulate the mathematical representation of a linear program to maximize public health subject to budget (and possible other) constraints. Health economists, pricing/reimbursement strategists, HTA specialists, analysts who are working with payers/ policy makers, statisticians, and decision makers /planners to address problems in health care, students and researchers who are interested in analytics/quantitative methods would benefit from attending this course.
Saturday, 10 November 2018 - Afternoon Session
Introduction to Health Technology Assessment Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Introductory This course is suitable for those with little or no experience with HTA.
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 Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
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.
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.
Statistical Methods for Health Economics and Outcomes Research Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
Track: Economic Methods
Level: Introductory This course is intended for participants with little (or rusty!) statistical training.
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.
Use of Propensity Scores in Observational Studies of Treatment Effects Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
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: revious 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.
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.
Collecting Health-State Utility Estimates for Economic Models in Clinical Studies Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
Track: Patient Preference Methods
Level: Intermediate This course is for those with some experience with quality of life measures in health economic evaluation.
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.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.
Pharmacoeconomic Modeling - Applications Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
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.
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.
NEW! Analysis of Longitudinal Data: Fixed and Random Effects Models Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
Prerequisite: Participants should be familiar with linear regression.
Course Description:
Longitudinal data is often encountered by researchers, allowing them to use the time dimension to uncover deeper insights than what is possible with a traditional cross-sectional snapshot. But this advantage comes at a cost: the assumption that each observation is independent is broken due to the fact that patients are measured on multiple occasions over time. Failure to account for this feature when analyzing data can result in bias, and longitudinal methods should be used to account for this problem. Two powerful but simple solutions are the fixed and random effects estimators, both of which have recently become more popular in medical research. A key feature of both is that they model the unobserved differences between patients, and can even control for unobserved confounding. This course will discuss the methods and intuition behind both modelling techniques, alongside practical examples and interactive sessions in STATA. Attendees will gain both knowledge and practical skills in this course. Although not essential, those who have STATA loaded on their laptops are encouraged to bring your laptop in order to participate in interactive sessions.
Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
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.
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 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.
NEW! Alternative Economic Assessment for Expressing Healthcare Value and Informing Resource Allocation Decisions Register Now
 
Saturday, 10 November 2018
13:00 - 17:00
Room: TBD
Track: Economic Methods
Level: Introductory For more basic information regarding constrained optimization methods the ISPOR Short Course, “Introduction to Constrained Optimization Methods for Health Care Research”, is recommended.
Prerequisite: Basic understanding of approaches applied in government affairs and healthcare policy making.
Course Description:
Various stakeholders are involved in the funding, decision making, policy-making and delivery of effective healthcare. Each of these areas requires different perspectives and constraints that can’t be addressed with the conventional cost-effectiveness analysis. Increasingly, alternative methodological frameworks are required for informing different stakeholders regarding healthcare and how to inform decisions considering known constraints including budget. This course will discuss fiscal health modeling, which reflects the government perspective on population health and investments in medical technologies. Specifically, how government can benefit from investments in healthcare based on future changes in tax revenue and reduced transfer costs attributed to changes in health status. The course will also cover constrained optimization modeling, which considers that decision making is often made under specific constraints including budget, logistics, compliance, among other features. Therefore, to optimize outcomes, methods must be applied that consider the links between maximizing effects and constraints identified. The course outline will follow the recently completed work of the ISPOR Task Force on Economic Analysis of Vaccination Programs. Participants who wish to gain hands-on experience must bring their personal laptops with Microsoft Excel for Windows installed.
Sunday, 11 November 2018 - Full Day
Bayesian Analysis - Overview and Applications Register Now
 
Sunday, 11 November 2018
8:00 - 17:00
Room: TBD
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.
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, 11 November 2018 - Morning Session
Cost-Effectiveness Analysis Alongside Clinical Trials Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Economic Methods
Level: Intermediate Familiarity with economic evaluations will be helpful.
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.
Using DICE Simulation for Health Economic Analyses Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Modeling Methods
Level: Introductory This course is designed for those with some familiarity with modeling.
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 Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
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.
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.
Transferability and Relevance of Cost-Effectiveness Data between Countries Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
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.
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.

Mapping to Estimate Utility Values from Non-Preference Based Outcome Measures Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Patient Preference Methods
Level: Intermediate
Course Description:
Mapping is the term used to refer to studies which estimate health state utility values from some non-preference based outcome measures. It is a practice commonly undertaken in HTA, most typically when clinical trials have not included any preference based instrument which would permit the estimation of QALYs in a cost-utility analysis. Mapping uses a different dataset to bridge this evidence gap. This is an introductory level course that will provide instruction to participants on key issues faced either when conducting, interpreting or using the results of a mapping study. It will draw on the ISPOR Good Practice Guide on Mapping that all faculty were members of. The course will introduce the concept of mapping and highlight the types of areas where it has been used. Using real world examples we will provide an overview of the main considerations for mapping including, how to select an appropriate dataset for mapping, key aspects for undertaking the statistical analysis and producing the optimal mapping model, how to report, interpret and use results from mapping in real world cost-effectiveness studies. A mixture of formal presentations, group discussions and illustrated examples will be used with an emphasis on interactive elements between the faculty and participants.
Budget Impact Analysis I: A 6-Step Approach Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Economic Methods
Level: Intermediate This course is designed for those with some experience with pharmacoeconomic analysis.
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 Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate This course is designed for those with some experience with pharmacoeconomic analysis.
Prerequisite: Helpful for those 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 systems.
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.
Understanding Survival Modeling with Application to HTA Register Now
 
Sunday, 11 November 2018
8:00 - 12:00
Room: TBD
Track: Modeling Methods
Level: Intermediate
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, 11 November 2018 - Afternoon Session
Budget Impact Analysis II: Applications & Design Issues Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
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 ISPOR short course “Introduction to Budget Impact Analysis: A 6-Step Approach,” or equivalent knowledge, is recommended. Knowledge of Excel is highly recommended.
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.
Advanced Methods for Addressing Selection Bias in Real-World Effectiveness and Cost-Effectiveness Studies Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Observational Data Methods
Level: Intermediate
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 Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
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 Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Outcomes Research Methods
Level: Intermediate This course requires at least a basic knowledge of meta-analysis and statistics.
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 Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate
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.
Adjusting for Time-Dependent Confounding and Treatment Switching Bias in Observational Studies and Clinical Trials: Purpose, Methods, Good Practices and Acceptance in HTA Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Observational Data Methods
Level: Intermediate
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 Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
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.
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.
NEW! Value of Information (VOI) Analysis Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Modeling Methods
Level: Intermediate This course is designed for beginners in VOI analysis that have some experience with

probabilistic decision modelling.

Prerequisite: Participation in the ISPOR Short Course “Advanced Decision Modeling for Health Economic Evaluations” or equivalent knowledge, is recommended.
Course Description:
Value of Information (VOI) techniques provide the analytic framework to estimate the value of acquiring additional evidence to inform a decision problem. VOI analysis is increasingly used to inform research prioritization decisions as it allows evaluating the extent to which new evidence might improve expected benefits by reducing the level of uncertainty in the current evidence base and compares that improvement with the cost of conducting the research. The course will provide a thorough understanding of the concepts and methods used in VOI analysis for participants with a working-knowledge of model-based cost-effectiveness analysis and its role in healthcare decision making. The course is based on the recommendations of the ISPOR Value of Information Task Force Reports and will 1) provide participants with an introduction to the fundamentals of VOI; 2) explain why VOI is important to decision makers; 3) identify the types of healthcare decisions that can be supported by VOI, as well as its limitations; 4) describe how the methods should be used and how the results should be interpreted, and 5) explain how VOI can support decision making in different contexts. Participants are provided with the opportunity to engage with concrete applications of the six-step approach for VOI analyses, including identification and characterization of different sources of uncertainty, calculation of the Expected Value of Perfect Information (EVPI), Expected Value of Perfect Parameter Information (EVPPI), Expected Value of Sample Information (EVSI) and Expected Net Benefit of Sampling (ENBS) and interpretation / presentation of results. To help participants engage with the course content, the instructors will walk through each step of the VOI analyses using worked examples (e.g. on VOI of next-gen sequencing studies, immunotherapy trials, and other emerging technologies). They will guide participants through hands-on exercises in Excel and R, show available online VOI tools, and lead discussions on the topic. Participants are required to bring a laptop with Excel and/or R installed (software choice depending on their own preference).
NEW! Multi-Criteria Support Systems for Group Decision Making Register Now
 
Sunday, 11 November 2018
13:00 - 17:00
Room: TBD
Track: Use of Pharmacoeconomic / Economic / Outcomes Research Information
Level: Intermediate This intermediate-level course presumes at least an introductory familiarity with multi-criteria decision analysis (MCDA) models. It is designed to supplement (rather than as an alternative to) previous ISPOR Short-Courses that discuss MCDA at an introductory level.
Prerequisite: Participation in the ISPOR Short Course “Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications,” or equivalent knowledge, is recommended.
Course Description:
MCDA models combine multiple dimensions of value (“attributes”) into a single metric, hence allowing evaluation of healthcare interventions in comprehensive ways using specific decision-makers’ values. Using different approaches, all MCDA models have two common features: (a) elicitation of decision makers’ values, and (b) transforming the performance of candidates (on multiple dimensions of value) into common scales (“data scaling”). This course emphasizes how to accomplish these key steps when groups (vs. individuals) are the decision makers (or are advising a final single decision maker). Various MCDA models differ substantially on the number of decisions required (by decision makers) to complete the models, a complexity that is exacerbated in settings with group decision making (voting), versus individual decision making. This course will review the virtues and complications of different MDCA models and provide hands-on testing of several voting methods to combine individuals’ preference weights into a group weights. Separately, we will explore various data-scaling mechanisms used in multi-criteria models, the errors they might introduce, and examine ways to simplify these processes. Finally, we will explore methods to create decision cut-offs (maximum willingness to pay) in multi-criteria models, akin to those used in cost-effectiveness analysis (CEA) when multiple factors interact under budget constraints.
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