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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10 November 2018

08:00 - 17:00

Introduction To Health Economic Evaluations

Level

Introductory

Track

Economic Evaluation


  • 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. This course is suitable for those with little or no experience with health economics.



10 November 2018

08:00 - 12:00

Introduction To The Design & Analysis Of Observational Studies Of Treatment Effects Using Retrospective Data Sources

Level

Introductory

Track

Study Approaches


  • 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.



10 November 2018

08:00 - 12:00

Introduction To Patient-Reported Outcomes Assessment

Level

Introductory

Track

Patient-Centered Research


  • 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. This is an entry level course which assumes only a passing familiarity with patient-reported outcomes.



10 November 2018

08:00 - 12:00

Development Of Conceptual Models

Level

Introductory

Track

Methodological & Statistical Research


  • 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.



10 November 2018

08:00 - 12:00

Tools For Reproducible Real-World Data Analysis

Level

Introductory

Track

Real World Data & Information Systems


  • 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. Participants who wish to gain hands-on experience are required to bring their laptops with R and RStudio installed.



10 November 2018

08:00 - 12:00

Elements Of Pharmaceutical/Biotech Pricing

Level

Introductory

Track

Health Policy & Regulatory


  • 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. This course is designed for those with limited experience in the area of pharmaceutical pricing and will cover topics within a global context.



10 November 2018

08:00 - 12:00

Conjoint Analysis - Theory & Methods

Level

Intermediate

Track

Patient-Centered Research


  • 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. This course is designed for clinicians, policymakers, researchers, and patient advocates/researchers with some familiarity with conjoint analysis or other stated-preference methods


10 November 2018

08:00 - 12:00

Introduction To Constrained Optimization Methods For Health Care Research

Level

Introductory

Track

Methodological & Statistical Research


  • 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. Attendees should be familiar with the standard techniques of cost-effectiveness analysis.



10 November 2018

13:00 - 17:00

Introduction To Health Technology Assessment

Level

Introductory

Track

Health Technology Assessment


  • 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. This course is suitable for those with little or no experience with HTA.



10 November 2018

08:00 - 12:00

Introduction To Modeling

Level

Introductory

Track

Methodological & Statistical Research


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



10 November 2018

13:00 - 17:00

Meta-Analysis & Systematic Literature Review

Level

Intermediate

Track

Study Approaches


  • Description
  • Previous attendance at the ISPOR short course, “Statistical Methods for Pharmacoeconomics & Outcomes Research”, or equivalent knowledge, is recommended.

    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.



10 November 2018

13:00 - 17:00

Statistical Methods For Health Economics And Outcomes Research

Level

Introductory

Track

Economic Evaluation


  • 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. This course is intended for participants with little (or rusty!) statistical training.



10 November 2018

13:00 - 17:00

Use Of Propensity Scores 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 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. This course is designed for those with little experience with this methodology but some knowledge of observational databases.



10 November 2018

13:00 - 17:00

Collecting Health-State Utility Estimates For Economic Models In Clinical Studies

Level

Intermediate

Track

Patient-Centered Research


  • 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 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. This course is for those with some experience with quality of life measures in health economic evaluation.



10 November 2018

13:00 - 17:00

Pharmacoeconomic Modeling - Applications

Level

Intermediate

Track

Methodological & Statistical Research


  • Description
  • Previous attendance at, or familiarity with the topics discussed in the ISPOR short course, “Introduction to Modeling”, is required.

    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.



10 November 2018

13:00 - 17:00

Analysis Of Longitudinal Data: Fixed And Random Effects Models

Level

Intermediate

Track

Methodological & Statistical Research


  • Description
  • Participants should be familiar with linear regression.

    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.



10 November 2018

13:00 - 17:00

Using Multi-Criteria Decision Analysis In Health Care Decision Making: Approaches & Applications

Level

Introductory

Track

Health Technology Assessment


  • 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. The course is designed for those unfamiliar with MCDA, but who have a basic understanding of other evaluation methodologies.



10 November 2018

13:00 - 17:00

Alternative Economic Assessment For Expressing Healthcare Value And Informing Resource Allocation Decisions

Level

Introductory

Track

Economic Evaluation


  • Description
  • Basic understanding of approaches applied in government affairs and healthcare policy making is recommended.

    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. For more basic information regarding constrained optimization methods the ISPOR Short Course, “Introduction to Constrained Optimization Methods for Health Care Research”, is recommended. Participants who wish to gain hands-on experience must bring their personal laptops with Microsoft Excel for Windows installed.



11 November 2018

08:00 - 17:00

Bayesian Analysis - Overview And Applications

Level

Intermediate

Track

Methodological & Statistical Research


  • 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. 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. Participants are encouraged to bring their personal laptops equipped with software provided to course registrants.



11 November 2018

08:00 - 12:00

Cost-Effectiveness Analysis Alongside Clinical Trials

Level

Intermediate

Track

Economic Evaluation


  • 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. Familiarity with economic evaluations will be helpful.



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