Please note: Separate Short Course registration is required.

The ISPOR Short Course Program is offered in conjunction with ISPOR conferences around the world as a series of 4 and 8-hour training courses, designed to enhance your knowledge and technique in 7 key Scientific Topic areas related to health economics & outcomes research.  Short courses range in skill level from Introductory to Advanced.


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11 November 2018

08:00 - 12:00

Using Dice Simulation For Health Economic Analyses

Level

Introductory

Track

Methodological & Statistical Research


  • 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. This course is designed for those with some familiarity with modeling.



11 November 2018

08:00 - 12:00

Use Of Instrumental Variables In Observational Studies Of Treatment Effects

Level

Intermediate

Track

Study Approaches


  • Description
  • 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.

    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. This course is suitable for those with some knowledge of econometrics. For those who have STATA loaded on their laptops, you are encouraged to bring your laptop.



11 November 2018

08:00 - 12:00

Transferability And Relevance Of Cost-Effectiveness Data Between Countries

Level

Experienced

Track

Economic Evaluation


  • 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. 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.

    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.



11 November 2018

08:00 - 12:00

Mapping To Estimate Utility Values From Non-Preference Based Outcome Measures

Level

Intermediate

Track

Patient-Centered Research


  • 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.



11 November 2018

08:00 - 12:00

Budget Impact Analysis I: A 6-Step Approach

Level

Intermediate

Track

Economic Evaluation


  • 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. This course is designed for those with some experience with pharmacoeconomic analysis.



11 November 2018

08:00 - 12:00

Risk Sharing / Performance-Based Arrangements For Drugs And Other Medical Products

Level

Intermediate

Track

Health Policy & Regulatory


  • Description
  • 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.

    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. This course is designed for those with some experience with health economic analysis.



11 November 2018

08:00 - 12:00

Understanding Survival Modeling With Application To HTA

Level

Intermediate

Track

Methodological & Statistical Research


  • 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.



11 November 2018

13:00 - 17:00

Budget Impact Analysis Ii: Applications & Design Issues

Level

Intermediate

Track

Economic Evaluation


  • Description
  • Participation in the ISPOR short course “Budget Impact Analysis: A 6-Step Approach,” or equivalent knowledge, is recommended. Knowledge of Excel is highly recommended.

    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. This course is designed for those who have basic knowledge of budget impact analyses and desire exposure to these analyses in Excel. Participants who wish to gain hands-on experience must bring their personal laptops with Microsoft Excel for Windows installed.



11 November 2018

13:00 - 17:00

Advanced Methods For Addressing Selection Bias In Real-World Effectiveness And Cost-Effectiveness Studies

Level

Intermediate

Track

Methodological & Statistical Research


  • 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.



11 November 2018

13:00 - 17:00

Introduction To The Economic Analysis Of Diagnostics

Level

Intermediate

Track

Economic Evaluation


  • 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.



11 November 2018

13:00 - 17:00

Network Meta-Analysis In Relative Effectiveness Research

Level

Intermediate

Track

Study Approaches


  • 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. This course requires at least a basic knowledge of meta-analysis and statistics.



11 November 2018

13:00 - 17:00

Risk-Sharing/Performance-Based Arrangements In Central & Eastern Europe: Implementation Of Managed Entry Agreements

Level

Intermediate

Track

Health Policy & Regulatory


  • 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.



11 November 2018

13:00 - 17:00

Adjusting For Time-Dependent Confounding And Treatment Switching Bias In Observational Studies And Clinical Trials: Purpose, Methods, Good Practices And Acceptance In HTA

Level

Intermediate

Track

Methodological & Statistical Research


  • 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.



11 November 2018

13:00 - 17:00

Reimbursement Systems For Pharmaceuticals In Europe

Level

Intermediate

Track

Health Policy & Regulatory


  • 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. This course is designed for individuals with intermediate experience within a single health care system wishing to broaden their appreciation of other reimbursement systems.



11 November 2018

13:00 - 17:00

Value Of Information (VOI) Analysis

Level

Intermediate

Track

Economic Evaluation


  • Description
  • Participation in the ISPOR Short Course “Advanced Decision Modeling for Health Economic Evaluations” or equivalent knowledge, is recommended.

    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. This course is designed for beginners in VOI analysis that have some experience with probabilistic decision modelling. Participants are required to bring a laptop with Excel and/or R installed (software choice depending on their own preference).



11 November 2018

13:00 - 17:00

Multi-Criteria Support Systems For Group Decision Making

Level

Intermediate

Track

Health Technology Assessment


  • Description
  • Participation in the ISPOR Short Course “Using Multi-Criteria Decision Analysis in Health Care Decision Making: Approaches & Applications,” or equivalent knowledge, is recommended.

    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. 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.



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