Pharmacoeconomics
Pharmacoeconomics for Decision-makers - Full Day Course (8:00am-5:00pm)

Faculty: Lorne Basskin PharmD, Clinical Coordinator, Pharmacy Services, North Shore Medical Center, Miami, FL, USA and President, Trinka Publications, Cooper City, FL, USA
 
Course description: This course is designed to teach clinicians and new researchers how to incorporate pharmacoeconomics into study design and data analysis. Participants will learn 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. The development of economic protocols and data collection sheets will be discussed. Different pharmacoeconomic models and techniques will be demonstrated and practiced in lectures and case studies. These include cost-minimization, cost-of-illness, cost-effectiveness, cost-benefit, and cost-utility analysis. Decision analysis, sensitivity analysis, and discounting, will all be demonstrated and practiced. Participants will also learn to compare and evaluate interventions such as drugs, devices and clinical services. This course is suitable for those with little or no experience with pharmacoeconomics.
 

Modeling
Bayesian Analysis: Overview - Morning Course (8:00am-12:00pm)

Faculty: Bryan Luce MBA, PhD, Founder and Senior Research Leader, The MEDTAP Institute at United BioSource Corporation, Bethesda, MD, USA ; Christopher S. Hollenbeak PhD, Surgery and Health Evaluation Sciences, Penn State College of Medicine, Hershey, PA, USA;

Course Description: This course is designed to provide an overview of the Bayesian approach and its applications to health economics and outcomes research. The course will cover basic elements of Bayesian statistics, contrasting briefly with classical (frequentist) statistics and introduce available statistical packages. This course is designed for those with a limited understanding of Bayesian statistical concepts.
 

Modeling
Bayesian Analysis: Applications - Afternoon Course (1:00pm-5:00pm)

Faculty: Bryan Luce MBA, PhD, Founder and Senior Research Leader, The MEDTAP Institute at United BioSource Corporation, Bethesda, MD, USA ; Christopher S. Hollenbeak PhD, Surgery and Health Evaluation Sciences, Penn State College of Medicine, Hershey, PA, USA; David Vanness PhD, Assistant Professor of Population Health Sciences, University of Wisconsin Medical School, Madison, WI, USA;

Course Description: This course will focus on the Bayesian “informative prior.” Several example vignettes of how a Bayesian analysis can be used within outcomes modeling problems will be presented. Participants will learn how a Bayesian approach is different and why it is useful for their work and what tools are available to them. This course is designed for those with a limited understanding of Bayesian statistical concepts.
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Quality of Life/Patient-reported Outcomes
Introduction to Quality of Life/Patient-Reported Outcomes - Afternoon Course (1:00pm-5:00pm)

Faculty: Steven Erickson PharmD, RPh, Associate Professor, University of Michigan, Ann Arbor, MI, USA

Course Description: Basic concepts of health-related quality of life, patient satisfaction, work performance in clinical trial and health services research will be presented. Participants will be asked to identify PRO domains and sub-domains from an anonymous patient interview. The advantages and disadvantages of different types of questionnaires will be provided, with examples provided for each type (an exhaustive list of questionnaires will NOT be provided). Finally, the practical methods and issues to consider when choosing or developing an instrument for a clinical study will be discussed, including cross-cultural issues. Participants will be asked to choose a questionnaire for a hypothetical study and develop a questionnaire based on a patient interview. This course is suitable for those with little or no experience with quality of life or patient-reported outcomes measurement.
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Decision Analysis
Introduction To Decision Analysis - Afternoon Courses (1:00pm-5:00pm)

Faculty: Mark Roberts MD, MPP, FACP, Associate Professor and Chief, Section of Decision Sciences and Clinical Systems Modeling University of Pittsburgh School of medicine, Pittsburgh, PA, USA

Course description: Decision analysis is a tool that uses an explicit, quantitative structure to describe and analyze complex health care decisions. This course will provide an introduction to the principles and practice of decision analysis. Upon completion of the course, participants will be able to evaluate the appropriateness of decision analysis in different settings, construct simple decision trees, understand the basic mechanics of tree evaluation and sensitivity analysis, and acquire skill in the interpretation of a published decision analysis. Extension of basic techniques, such as cost-effectiveness analysis and the assessment of patient preferences will be briefly discussed. Pen and paper exercises will be used to illustrate these principles. This course is suitable for those with little experience with decision analysis
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Economic Analysis
Financial Impact / Cost of Illness - Afternoon Course (1:00pm-5:00pm)

Faculty: Josephine Mauskopf PhD, Global Head, Health Economics and Outcomes Strategy, RTI Health Solutions, Research Triangle Park, NC, USA; C. Daniel Mullins PhD, Professor and Chair of Pharmaceutical Health Services Research, University of Maryland, School of Pharmacy, Baltimore, MD, USA

Course Description: This will describe methods to determine the cost-of-illness of a health condition using a “top-down” or “bottom-up” approach. Participants will also learn how to estimate the impact of new healthcare technologies on disease-specific costs from different decision-maker perspectives. Actuarial methods using straight-line projections and nonlinear trends will be described. Both static and dynamic methods for estimating the budget impact of adding a new drug to a health plan formulary will also be presented. This course is designed for those with some experience with pharmacoeconomic analysis.