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SHORT COURSE OVERVIEW
Short Course Program Overview Short Courses Saturday, 3 November 2012 Short Courses Sunday, 4 November 2012
SATURDAY, 3 NOVEMBER 2012 - ALL DAY COURSE 9:00-18:00
9:00-18:00
Sold out Introduction to Health Economic / Pharmacoeconomic Evaluations
Room: Roof Garden
Track: Economic Methods
Level: Introductory. This course is suitable for those with little or no experience with pharmacoeconomics.
Faculty:
Lieven Annemans, PhD, MMan, MSc

Lieven Annemans, PhD, MMan, MSc, Professor of Health Economics, ICHER (Interuniversity Center for Health Economics Research), Ghent University - Brussels University, Ghent, Belgium

Course Description:

This course is designed to teach clinicians and new researchers how to incorporate pharmacoeconomics into study design and data analysis. Participants will first review the basic principles and concepts of health economic evaluations, then discuss how to collect and calculate the costs of different alternatives, determine the economic impact of clinical outcomes, and how to identify, track and assign costs to different types of health care resources used. Different pharmacoeconomic models and techniques will be demonstrated, including cost-minimization, cost-effectiveness, cost-benefit, cost-utility and budget impact analysis. Decision analysis, sensitivity analysis, and discounting will all be demonstrated and practiced.


SATURDAY, 3 NOVEMBER 2012 - MORNING COURSES 9:00-13:00
9:00-13:00
Introduction to Retrospective Database Analysis
Room: Hall 10
Track: Observational Data Methods
Level: Introductory.
Faculty:
Bradley C. Martin, PharmD, PhD

Bradley C. Martin, PhD, RPh, PharmD, Professor and 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 analytic techniques and specific best practices to improve causal inference in studies using retrospective databases. Specific topics to be covered include: measurement of exposure and outcome, causal graphs, the use of stratification analysis before multivariable modeling, multivariable regression including Cox proportional hazards survival analysis, propensity scoring, instrumental variable, and structural modeling techniques including marginal structural models.


 
Introduction to Patient-Reported Outcomes Assessment: Instrument Development & Evaluation
Room: Hall 8
Track: Patient-Reported Outcomes / Preference-Based Methods
Level: Introductory. This is an entry level course which assumes only a passing familiarity with patient-reported outcomes.
Faculty:
Andrew Lloyd, DPhil Andrew Lloyd, DPhil, Vice President (Practice Lead), Oxford Outcomes, Oxford, UK
Sarah Acaster, MSc Sarah Acaster, MSc, Director, Patient Reported Outcomes, Oxford Outcomes, Oxford, UK
Annabel Nixon, PhD Annabel Nixon, PhD,Director, Patient Reported Outcomes, Oxford Outcomes, Oxford, UK
Course Description:

Patient-reported outcomes (PROs) are widely used to evaluate the impact of health technologies, practice innovations or changes in health policy from the patients' perspective. This course is designed to familiarize people with the range and scope of what PROs are used for, how they are developed and evaluated, and how PRO data can be used to support licensing and reimbursement applications. The course content will describe the scope and range of what patient-reported outcomes measure. This includes generic and disease-specific measures of health-related quality of life (HRQL) as well as measures of patient preference, systems, functioning, utility, and treatment satisfaction. We will describe the steps that researchers generally go through in order to develop and test a new PRO. This will include qualitative work, item generation and testing and then validation. Finally, in the last hour, we will frame this in terms of what the FDA and EMEA expect to see when PROs form an important part of a licensing submission. In addition, we will describe the approach of bodies such as NICE and how they review PRO data and use it to guide reimbursement decisions.


 
Introduction to Modeling
Room: Hall 7
Track: Modeling Methods
Level: Introductory. This course is designed for those with some familiarity with modeling techniques.
Faculty:

Uwe Siebert, MD, MPH, MSc, ScD, Professor and Chair, Department of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University of Health Sciences, Medical Informatics and Technology, Hall/Innsbruck, Austria, & Adjunct Professor of Health Policy and Management, Center of Health Decision Science, Harvard School of Public Health, Boston, MA, USA

Course Description:

This course gives a brief overview on different decision-analytic model types and provides an introduction to Markov modeling techniques and their practical application in economic evaluation and outcomes research. We present analytic approaches including deterministic cohort simulation and Monte Carlo simulation and we give some technical instructions for modelers. We discuss the concepts of variability, uncertainty, probabilistic sensitivity analysis (PSA), and cost-effectiveness acceptability curves (CEAC). We review the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health Care Evaluations and explore, when and how modeling should be used in economic evaluation and which are suitable model types.


 
Sold out Statistical Methods for Pharmacoeconomics & Outcomes Research
Room: Hall 6
Track: Economic Methods
Level: Introductory. This course is intended for participants with little (or rusty!) statistical training.
Faculty:
Neil Hawkins, PhD, CStat Neil Hawkins, PhD, CStat, Research Fellow, University of York & Director of Health Outcomes, Oxford Outcomes, Oxford, UK
Lindsay Govan, PhD Lindsay Govan, PhD, Research Associate, Health Economics and Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
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. We will begin by introducing the concept of random variables and will then proceed to discuss the foundations of statistical estimation and testing of hypotheses. We will go on to discuss the importance of correlation 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.


 
Cost-Effectiveness Analysis alongside Clinical Trials
Room: Hall 4/5
Track: Economic Methods
Level: Introductory. Familiarity with economic evaluations will be helpful.
Faculty:
Scott D. Ramsey, MD, PhD Scott D. Ramsey, MD, PhD, Member, Fred Hutchinson Cancer Research Center and Professor, Department of Medicine, University of Washington, Seattle, WA, USA
Richard J. Willke, PhD Richard J. Willke, PhD, Head, Global Health Economics & Outcomes Research, Global Market Access, Primary Care Business Unit, Pfizer Inc., Peapack, NJ, USA
Course Description:

The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. This course will present the design, conduct, and reporting of cost-effectiveness analyses alongside clinical trials based on, in part, the Good Research Practices for Cost-Effectiveness Analysis alongside Clinical Trials: The ISPOR RCT-CEA Task Force Report. Trial design, selecting data elements (measures of cost and outcomes), database design and management, analysis, and reporting of results will be presented. Trials designed to evaluate effectiveness (rather than efficacy) as well as clinical outcome measures will be discussed. How to obtain health resource use and health state utilities directly from study subjects and economic data collection fully integrated into the study will also be discussed. Analyses guided by an analysis plan and hypotheses, an incremental analysis using an intention to treat approach, characterization of uncertainty, and standards for reporting results will be presented. Various case studies will be employed to guide participants through the elements listed above.


 
Elements of Pharmaceutical/Biotech Pricing
Room: Hall 9
Track: Use of Pharmacoeconomics / Economic / Outcomes Research Information
Level: Introductory. This course is designed for those with limited experience in the area of pharmaceutical pricing and will cover topics within a global context.
Faculty:
Jack M. Mycka Jack M. Mycka, Global President and CEO, MME LLC, Montclair, NJ, USA
Renato Dellamano, PhD Renato Dellamano, PhD, President, MME Europe & ValueVector (Value Added Business Strategies), Milan, Italy
Course Description: This course will give participants a basic understanding of the key terminology and issues involved in pharmaceutical pricing decisions. It will cover the tools to build and document product value including issues, information and processes employed (including pricing research), the role of pharmacoeconomics and the differences in payment systems that help to shape pricing decisions. These tools will be further explored through a series of interactive exercises.

SATURDAY, 3 NOVEMBER 2012 - AFTERNOON COURSES 14:00-18:00
14:00-18:00
Introduction to Health Technology Assessment (HTA)
Room: Hall 4/5
Track: Use of Pharmacoeconomics / Economic / Outcomes Research Information
Level: Introductory. This course is suitable for those with little or no experience with HTA.
Faculty:

Uwe Siebert, MD, MPH, MSc, ScD, Professor and Chair, Department of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University of Health Sciences, Medical Informatics and Technology, Hall/Innsbruck, Austria, and Adjunct Professor of Health Policy and Management, Center of Health Decision Science, Harvard School of Public Health, Boston, MA, USA

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 disciplines 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 HTA examples of 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 decision making.


 
Sold out Meta-Analysis & Systematic Literature Review
Room: Hall 9
Track: Outcomes Research
Level:

Intermediate. The short course “Statistical Methods for Pharmacoeconomics & Outcomes Research” is recommended as a precursor to this course.

Prerequisite:

The short course “Statistical Methods for Pharmacoeconomics & Outcomes Research” is recommended as a precursor to this course.

Faculty:
Neil Hawkins, PhD, CStat, Research Fellow, University of York and Director of Health Outcomes, Oxford Outcomes, Oxford, UK
Olivia Wu, PhD, MSc Olivia Wu, PhD, MSc, Reader, Public Health and Health Policy, University of Glasgow, Glasgow, UK
Course Description: Meta-analysis may be defined as the statistical analysis of data from multiple studies for the purpose of synthesizing and summarizing results, as well as for quantitatively evaluating sources of heterogeneity and bias. A systematic literature review often includes meta-analysis and involves an explicit, detailed description of how a review was conducted. This course highlights and expounds upon four key areas: 1) impetus for meta-analysis and systematic reviews; 2) basic steps to perform a quantitative systematic review; 3) statistical methods of combining data; and 4) an introduction to methods for indirect comparisons. The material includes practical examples from the published literature relevant to pharmacoeconomic and PRO research. This course is designed for those with little experience with meta-analysis and includes interactive exercises.

 
New! Propensity Scores and Observational Studies of Treatment Effect
Room: Hall 7
Track: Observational Data Methods
Level: Intermediate. This course is designed for those with little experience with this methodology but some knowledge of observational databases.
Prerequisite: Previous attendance at the short course “Introduction to Analysis of Retrospective Database Studies” - or equivalent knowledge - is recommended.
Faculty:
John Seeger, PharmD, DrPH

John Seeger, PharmD, DrPH, Lecturer in Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Harvard Medical School/Brigham and Women's Hospital, Boston, MA, USA

Course Description:

In observational research, issues of bias and confounding relate to study design and analysis in the setting of non-random treatment assignment where compared subjects might differ substantially with respect to comorbidities. No control over the treatment assignment and the lack of balance in the covariates between the treatment and control groups can produce confounded estimates of treatment effect. We will explain how propensity scores can be used to mitigate confounding through standard observational approaches (restriction, stratification, modeling, 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) and issues surrounding validation will also be discussed.


 
Sold out Introduction to Patient Preference Methods Used for QALYs
Room: Hall 6
Track: Patient-Reported Outcomes / Preference-Based Methods
Level: Introductory/intermediate. This course is for those with some experience with quality of life measures in health economic evaluation.
Faculty:
Jan Busschbach, PhD Jan Busschbach, PhD, Interim Director, Department of Medical Psychology & Psychotherapy, Erasmus MC, Rotterdam, The Netherlands   
Course Description:

During this course, faculty will evaluate the relevant aspects of validity and sensitivity of utility (QALY) assessments, review indirect utility measurement (EQ-5D, HUI and SF-36), direct utility measurement (standard gamble, time trade-off, and visual analogue scale) and disease-specific utility measurement. Utility measurement, however, is not only about mastering these techniques; it is about using them in such a way that health care decision-makers can apply the results, for instance in QALY-analyses. For this purpose, one needs to be aware of shortcomings of the available utility measures and potential solutions. Furthermore, one should be aware of the decision-making context and the way results are interpreted. To equip participants with expertise in the field of utility measurement, the most important issues will be discussed. For instance, we will consider potential insensitivity of generic instruments for particular disease-specific problems and discuss to what extent adaptation of generic- or disease-specific quality of life instruments may offer a solution. This will be demonstrated with practical exercises. Also, the issue of "whose values count: patient values or values from the general public?" will be discussed. Finally, we turn to the interpretation in the context of resource allocation.


 
Sold out Pharmacoeconomic Modeling - Applications
Room: Hall 10
Track: Modeling Methods
Level: Intermediate.
Prerequisite: Attendance at (or familiarity with the topics discussed in) the short course “Introduction to Modeling” is required.
Faculty:
Mark S. Roberts, MD, MPP Mark S. Roberts, MD, MPP, Professor and Chair, Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA
Shelby L. Corman, PharmD, MS, BCPS

Shelby Corman, PharmD, MS, BCPS, Senior Clinical Outcomes Scientist, Pharmerit International, Bethesda, MD, USA

Course Description:

During this course, students will have hands-on experience in constructing and analyzing a decision analysis tree using TreeAge Pro software including Markov models and one-way, two-way and probabilistic sensitivity analysis. Instructors will provide a series of short lecture-based sessions followed by model-building exercises in 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 laptops equipped with software as provided when registering for the course.


 
Short Course Program Overview Short Courses Saturday, 3 November 2012 Short Courses Sunday, 4 November 2012

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