ISPOR's Short Course Program Is Now Virtual

The renowned ISPOR Short Course Program is now being offered virtually. The program is designed to enhance knowledge and techniques in core health economics and outcomes research (HEOR) topics as well as emerging trends in the field. Taught by expert faculty, short courses topics are offered across 7 topical tracks and range in skill level from introductory to experienced.

Upcoming Virtual Short Courses

Expand your HEOR knowledge from the safety and comfort of your home or office. ISPOR's expert short course faculty are presenting the same curriculum that has historically been offered at ISPOR in-person events through an interactive virtual experience. The courses are not recorded so attendance in the live-broadcast is important. These hand-picked virtual courses, along with their electronic course books, provide a solid foundation in essential methodologies and emerging issues.

 

27-28 July 2021: Advanced Decision Modeling for Health Economic Evaluations

LEVEL - Advanced
TRACK - Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Tuesday 27 July, 2021 | Course runs 2 consecutive days, 2 hours per day
9:00AM-11:00AM (EDT) Eastern Daylight Time
14:00-16:00 (UTC/GMT) Coordinated Universal Time
15:00-17:00 (CEST) Central European Summer Time

Wednesday 28 July, 2021 | Course runs 2 consecutive days, 2 hours per day
9:00AM-11:00AM (EDT) Eastern Daylight Time
14:00-16:00 (UTC/GMT) Coordinated Universal Time
15:00-17:00 (CEST) Central European Summer Time

Basic Schedule:
Class Time: 2 hours daily

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DESCRIPTION

During this course, the key aspects and new developments of decision modeling for economic analysis will be considered. How models can be made probabilistic to capture parameter uncertainty (including rationale, choosing parameter distributions, and types of uncertainty) will be covered. How to analyze and present the results of probabilistic models, how the results of probabilistic decision modeling should be interpreted, and how decisions should be made (including decisions with uncertainty and expected value of perfect information [EVPI]) will be presented. Specific examples using Excel programming will be used to illustrate concepts. Participants should have an understanding of decision analysis.

PREREQUISITE: As a more advanced course, you should be familiar with decision trees and basic Markov modelling and have some familiarity with regression modelling and survival analysis..

 




FACULTY MEMBERS

Mark Sculpher, PhD, MSc
Professor
University of York, Centre for Health Economics
Heslington, York, UK

Andrew Briggs, DPhil
Professor of Health Economics
London School of Hygiene & Tropical Medicine
London, UK


 

2-5 August 2021: Introduction to Health Economics and Outcomes Research

LEVEL - Introductory
TRACK - Economic Evaluation 
LENGTH: 8 Hours | Course runs 4 consecutive days, 2 hours each day

Monday, 2 August, 2021 | Course runs 4 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC/GMT) Coordinated Universal Time
14:00-16:00 (CEST) Central European Summer Time

Tuesday, 3 August, 2021 | Course runs 4 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC/GMT) Coordinated Universal Time
14:00-16:00 (CEST) Central European Summer Time

Wednesday, 4 August, 2021 | Course runs 4 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC/GMT) Coordinated Universal Time
14:00-16:00 (CEST) Central European Summer Time

Thursday, 5 August, 2021 | Course runs 4 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC/GMT) Coordinated Universal Time
14:00-16:00 (CEST) Central European Summer Time

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

DESCRIPTION
This course is designed to teach clinicians and new researchers how to incorporate health economics 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 healthcare resources used. Different health economic 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. This course is suitable for those with little or no experience with health economics.


 




FACULTY MEMBERS

Lorne E. Basskin, PharmD
Adjunct Professor
School of Pharmacy
University of Charleston
Charleston, WV, USA


 

11-12 August 2021: Applied Cost-Effectiveness Modeling with R

LEVEL - Intermediate
TRACK - Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Wednesday, 11 August 2021 | Course runs 2 consecutive days, 2 hours per day
7:00 AM-9:00AM Pacific Daylight Time (PDT)
10:00 AM-12:00PM Eastern Daylight Time (EDT)
2:00PM-4:00PM UTC/GMT Time
3:00PM-5:00PM British Standard Time (BST)
4:00PM-6:00PM Central European Standard Time (CEST)

Thursday, 12 August 2021 | Course runs 2 consecutive days, 2 hours per day
7:00 AM-9:00AM Pacific Daylight Time (PDT)
10:00 AM-12:00PM Eastern Daylight Time (EDT)
2:00PM-4:00PM UTC/GMT Time
3:00PM-5:00PM British Standard Time (BST)
4:00PM-6:00PM Central European Standard Time (CEST)

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

 

DESCRIPTION

Historically, economic models for cost-effectiveness analyses have been developed with specialized commercial software (such as TreeAge) or more commonly with spreadsheet software (almost always Microsoft Excel). But more recently there has been increasing interest in using R and other programming languages for cost-effectiveness analysis which can offer advantages regarding the integration of input parameter estimation and model simulation, the evaluation of structural uncertainty, and the quantification of decision uncertainty, among others.1-2 Programming languages such as R also facilitate reproducibility of model-based cost-effectiveness analysis which is more relevant than ever given recent calls for increased transparancy.3-5 Yet, these tools are still relatively new, but there is an increased interest in learning opportunities, including in the ISPOR community (as demonstrated by attendance at the workshops on R and decision modeling at ISPOR Barcelona 2018 and ISPOR New Orleans 2019). Furthermore, R-based economic modeling tutorials have recently been published.6-7

In this short course, participants will learn how to use R to develop a number of different types of economic models to perform cost-effectiveness analysis. Economic models will include time-homogeneous and time-inhomogeneous Markov cohort models, partitioned survival models, and semi-Markov individual patient simulations. The underlying assumptions of each model type will be summarized and the implementation in R will be presented in an accessible manner. Participants will be asked to modify the models in R (eg, adding health states, use of alternative time-to-event distributions) and run analyses (eg, cost-effectiveness analysis, probabilistic sensitivity analysis, evaluating structural uncertainty, and value of information analysis). To make this interactive aspect of the course as efficient as possible, all participants will have access to the GitHub repository prior to the course. It will contain R code to run the economic models; R Markdown files to explain and reproduce the analyses covered in the course; and an illustrative R Shiny web application for one of the economic models to illustrate how R code can be used to create a web-based user interface.

FACULTY MEMBERS
Jeroen P. Jansen, PhD 
Chief Scientist
PRECISIONheor
Oakland, CA, USA
and
Associate Professor
Clinical Pharmacy, University of California
San Francisco, CA, USA

Devin Incerti



 

31 August 2021: Developing Decision-Grade Real-World Evidence

LEVEL: Intermediate
TRACK: Real World Data & Information Systems 
LENGTH: 4 Hours | Course runs 1 day

Tuesday, 31 August 2021 | Course runs 1 day
9:00AM-1:30PM EDT
1:00PM-5:30PM UTC/GMT
3:00PM-7:30PM CEST

Basic Schedule:
Class Time: 2 hours of content | 30 minute break | 2 hours of content

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DESCRIPTION

In this course, participants will be guided through a hands-on analysis of real-world data (RWD) to develop decision-grade real-world evidence (RWE) that could be used to support an indication expansion. The first section of the course focuses on what makes RWE “decision-grade.” We will review the most recent RWE frameworks and guidelines set by regulatory agencies and professional organizations, and we will examine case studies in which these guidelines were used in regulatory and HTA approval. The second half of the course is an active workshop where participants will use principles from the first half of the course to execute a decision-grade RWE study. Participants will be guided step-by-step in using a software platform that will enable them to work within a longitudinal US insurance claims database with anonymized patients. After the study has been executed, we will discuss how these results could be communicated to decision makers. Participants should come with a laptop with Google Chrome installed.

PREREQUISITE: Students are expected to be familiar with relevant concepts and methodologies for analyzing real-world data, but this course does not require specific programming skills.

FACULTY MEMBERS
Sebastian Schneeweiss, MD, ScD
Professor of Medicine and Epidemiology
Harvard Medical School and Brigham & Women’s Hospital
Boston, MA, USA

Jeremy Rassen, ScD
President & Chief Science Officer
Aetion, Inc.
New York, NY, USA

Ashley Jaksa, MPH
VP Science/Sr. Scientist
Aetion, Inc.
Boston, MA, USA

 



 

27-28 September 2021: Causal Inference and Causal Diagrams in Big, Real-World Observational Data and Pragmatic Trials

LEVEL: Advanced
TRACK: Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Monday, 27 September 2021 | Course runs 2 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC) Coordinated Universal Time 
14:00-16:00 (CEST) Central European Summer Time

Tuesday, 28 September 2021 | Course runs 2 consecutive days, 2 hours per day
8:00AM-10:00AM (EDT) Eastern Daylight Time
12:00-14:00 (UTC) Coordinated Universal Time 
14:00-16:00 (CEST) Central European Summer Time

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

DESCRIPTION
Innovative causal inference methods are needed for the design and analysis of big real-world observational data and pragmatic trials. This course  will provide an introduction to the principles of causation in comparative effectiveness research, the use of causal diagrams (directed acyclic graphs; DAGs) and focus on causal inference methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-formula, marginal structural models with inverse probability of treatment weighting, and structural nested models with g-estimation). The “target trial” concept and a counterfactual approach with “replicates” will be used to apply causal methods to big real-world datasets with case examples from oncology, cardiovascular disease, HIV, nutrition and obstetrics. The course will consist of lectures, exercises drawn from the published literature and interactive discussion. The intended audience includes researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method.


FACULTY MEMBERS

Uwe Siebert, MD, MPH, MSc, ScD
Professor & Chair
UMIT - University for Health Sciences
Medical Informatics and Technology
Innsbruck, Austria and
Harvard Chan School of Public Health
Harvard University
Boston, MA, USA

Doug E. Faries, PhD
Research Fellow, Global Statistical Sciences
Eli Lilly and Company
Indianapolis, IN, USA

Felicitas Kühne, MSc
Senior Scientist, Program Causal Inference
UMIT - University for Health Sciences
Medical Informatics and Technology
Innsbruck, Austria



 

 

6-7 October 2021: Risk-Sharing/Performance-Based Arrangements for Drugs and Other Medical Products

LEVEL: Intermediate
TRACK: Health Policy & Regulatory 
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Wednesday, 6 October 2021 | Course runs 2 consecutive days, 2 hours per day
10:00AM-12:00PM (EDT) Eastern Daylight Time
14:00-16:00 (UTC) Coordinated Universal Time
16:00-18:00 (CEST) Central European Summer Time

Thursday, 7 October 2021 | Course runs 2 consecutive days, 2 hours per day
10:00AM-12:00PM (EDT) Eastern Daylight Time
14:00-16:00 (UTC) Coordinated Universal Time
16:00-18:00 (CEST) Central European Summer Time

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

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.

FACULTY MEMBERS

Louis P Garrison, PhD
Professor Emeritus
The Comparative Health Outcomes, Policy, and Economics Institute Department of Pharmacy
University of Washington
Seattle, WA, USA

Adrian Towse, MA, MPhil
Director Emeritus & Senior Research Fellow
Office of Health Economics
London, UK

Josh J Carlson, MPH, PhD
Associate Professor
Pharmaceutical Outcomes Research & Policy Program Department of Pharmacy
University of Washington
Seattle, WA, USA

 



 

3-4 November 2021: Selecting Rapid Review Methods for Health Technology Assessment

LEVEL: Intermediate
TRACK: Health Technology Assessment 
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Wednesday, 3 November 2021 | Course runs 2 consecutive days, 2 hours per day
10:00AM-12:00PM EDT
2:00PM-4:00PM UTC/GMT
3:00PM-5:00PM CET

Thursday, 4 November 2021 | Course runs 2 consecutive days, 2 hours per day
10:00AM-12:00PM EDT
2:00PM-4:00PM UTC/GMT
3:00PM-5:00PM CET

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

DESCRIPTION

Rapid reviews are of increasing importance for Health Technology Assessment (HTA) and other commissioners of evidence synthesis, due to the need for timely assessment of new technologies. Rapid review methods need to be chosen to fit the specific needs and challenges of each review. Collaboration between commissioners (the person or group requesting the rapid review) and those undertaking the rapid review is essential, to ensure that the rapid review methods chosen can address the requirements of the review within the time frame, and that the limitations of the rapid review methods employed are agreed and reported on. However, whilst there are many rapid review methods available, there is little guidance on the selection of suitable rapid review approaches and methods.

This short course is aimed at both commissioners of systematic reviews and those who undertake them and aims to enable review teams and commissioners to have a clear understanding of possible approaches to undertaking a rapid review, as well as improving their skills in selecting appropriate rapid review methods.

PREREQUISITE: Previous attendance at the short course “introduction to HTA,” or equivalent knowledge, is required.

FACULTY MEMBERS

Marrissa Martyn-St James, MSc, PhD
Systematic Reviewer
ScHARR, University of Sheffield
Sheffield, UK

Ruth Wong, MRes, MSc, PhD
Information Specialist
ScHARR, University of Sheffield
Sheffield, UK

Abdullah Pandor, MSc
Senior Research Fellow
ScHARR, University of Sheffield
Sheffield, UK

Katy Cooper, PhD
Senior Research Fellow
ScHARR, University of Sheffield
Sheffield, UK

 



 

 

10 November 2021: Use of Propensity Scores in Observational Studies of Treatment Effects 

LEVEL: Intermediate
TRACK: Study Approaches
LENGTH: 4 Hours | Course runs 1 day

Wednesday, 10 November | Course runs 1 day
9:00AM-1:30PM EDT
1:00PM-5:30PM UTC/GMT
2:00PM-6:30PM CEST

Basic Schedule:
Class Time: 2 hours of content | 30 minute break | 2 hours of content

 

Click for time zone conversion

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. 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 the Design & Analysis of Observational Studies of Treatment Effects Using Retrospective Data Sources,” or equivalent knowledge, is recommended.


FACULTY MEMBERS

John Seeger, PharmD, DrPH
Chief Science Officer, Epidemiology
Optum
Boston, MA, USA

Jeremy Rassen, ScD
President & Chief Science Officer
Aetion, Inc.
New York, NY, USA

 

December 6, 8, and 9, 2021: Budget Impact Analysis II: Applications and Design Issues 

LEVEL: Intermediate
TRACK: Study Approaches
LENGTH: 4 Hours | Course runs 3 days

Monday, Wednesday, and Thursday, December 6, 8, and 9, 2021 | Course runs 3-days*

Day 1: 
10:00AM-12:00PM Eastern Standard Time (EST)
3:00PM-5:00PM Coordinated Universal Time (UTC)
4:00PM-6:00PM Central European Time (CET)

Day 2 Homework Support (Optional):
10:00AM-11:00AM Eastern Standard Time (EST)
3:00PM-4:00PM Coordinated Universal Time (UTC)
4:00PM-5:00PM Central European Time (CET)

Day 3:
10:00AM-12:00PM Eastern Standard Time (EST)
3:00PM-5:00PM Coordinated Universal Time (UTC)
4:00PM-6:00PM Central European Time (CET)

Basic Schedule:

Class Time: DAY 1: 2 hours content + Homework
DAY 2: 1 hour "Office Hours" Homework Support (optional)
DAY 3: 2 hours of content

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DESCRIPTION
"This course covers the concrete application of the 6-step approach for developing budget impact analyses and provides 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, simplicity versus accuracy and face validity, and how budget impact analyses are used by payers and other decision makers. Technical topics will include static versus dynamic budget impact models, considerations for device and diagnostic technologies, and realistic features such as patient copayments and use of generics. The instructors will walk through 2 different budget impact analyses programmed in Excel (one static and one dynamic) and work with participants during hands-on exercises to enhance these models. 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.

PREREQUISITE: Participation in the ISPOR short course, “Budget Impact Analysis I: A 6-Step Approach,” or equivalent knowledge, is recommended.  Working knowledge of Microsoft Excel is required. "



FACULTY MEMBERS

Stephanie Earnshaw, PhD, MS
Senior Vice President, Health Economics
RTI Health Solutions
Research Triangle Park, NC, USA

Anita J. Brogan, PhD, MSc

Head, Decision Analytic Modeling, Health Economics
RTI Health Solutions
Manchester, UK

Thor-Henrik Brodtkorb, PhD

Senior Director, Health Economics
RTI Health Solutions
Ljungskile, Sweden

Ashley E. Davis, PhD, MSc

Director, Health Economics
RTI Health Solutions
Research Triangle Park, NC, USA

 

15-16 December 2021: Going Beyond the Standard: Exploring Advanced Survival Modeling Techniques for Immuno-Oncology  

LEVEL: Intermediate
TRACK: Methodological & Statistical Research
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day

Wednesday, 15 December 2021 | Course runs 2 consecutive days, 2 hours per day
3:00PM-5:00PM UTC/GMT
4:00PM-6:00PM CET
10:00AM-12:00PM EST

Thursday, 16 December 2021 | Course runs 2 consecutive days, 2 hours per day
3:00PM-5:00PM UTC/GMT
4:00PM-6:00PM CET
10:00AM-12:00PM EST

Basic Schedule:

Class Time: 2 hours daily

Click for time zone conversion

DESCRIPTION
Survival modeling techniques are commonly used to extrapolate clinical trial outcomes like overall survival to a time horizon that is appropriate for health economic evaluations. Standard parametric distributions, such as the exponential and Weibull, have been the de-facto standard for conducting such extrapolations but, with the advent of novel potentially curative therapies, these standard parametric distributions fail to capture the underlying survival trend. Newer techniques like response based landmark models, parametric mixture models, mixture cure models and Bayesian model averaging provide novel ways to capture these more complex survival patterns. The purpose of this course is to enable participants to identify which methods are most appropriate in a specific context, considering underlying structural assumptions, and discuss how modeling choices propagate into health economic evaluations. To gain a more in-depth understanding of the impact of the choice for a specific method, participants will practice with several of the survival modeling techniques in hands-on exercises.



FACULTY MEMBERS

Elisabeth Fenwick, MSc, PhD
Senior Director, Modeling & Meta Analysis
Open Health
Oxford, UK

Sven Klijn, MSc
Director Economic & Predictive Modeling WWHEOR, HEME/CAR T
Bristol Myers Squibb
Randstad, Netherlands

Elleke Peterse, PhD
Associate Research Consultant
Open Health
Rotterdam, Netherlands


Registration Rates for ISPOR Short Courses

8 Hour | 2 Day or 4 Day  Short CourseNon-member
Rate
Member Rate
Standard $680$510
Clinical Practitioners$510$385
Full-Time Government and Academia$475$360
Patient Representative$340$225
Full-Time Students (must provide current enrollment docs)$200$160
  
4 Hour | 1 or 2 Day Short CourseNon-memberMember Rate
Standard$340$255
Clinical Practitioners$255$190
Full-Time Government and Academia
$240$180
Patient Representative$170$130
Full-Time Students (must provide current enrollment docs)$100$80

The cancellation date for short courses is 2 weeks before the course. All cancellation requests must be made in writing and emailed to ISPOR Registration. A $50.00 cancellation fee applies. After the 2 week period no refund can be provided.

Additional Short Course Program Details

Short Course Tracks

ISPOR short courses are offered across the following topical tracks:

  • Economic Evaluation
  • Methodological & Statistical Research
  • Study Approaches
  • Real World Data & Information Systems
  • Patient-Centered Research
  • Health Policy & Regulatory
  • Health Technology Assessment

Short Course Core Curriculum

ISPOR short course core curriculum is defined as essential curriculum for professional success in the HEOR field; courses/topic areas that are offered at all conferences and the building blocks of a fundamental curriculum that can be applied to future educational programs/offerings.

  • Economic Evaluation
    • Introduction to Health Economics and Outcomes Research
    • Statistical Methods for Health Economics and Outcomes Research
    • Budget Impact Analysis I – A 6-Step Approach
  • Methodology & Statistical Methods
    • Introduction to Modeling Methods
  • Study Approaches
    • Introduction to the Design & Database Analysis of Observational Studies of Treatment Effects
    • Meta-analysis & Systematic Literature Review
    • Network Meta-Analysis
  • Patient-Centered Research
    • Introduction to Patient-Reported Outcomes
    • Utility Measures
  • Health Policy & Regulatory
    • Elements of Pharmaceutical/Biotech Pricing
    • Risk-Sharing/Performance-Based Arrangements for Drugs and Other Medical Products
    • Global Payers/US Payers
  • Health Technology Assessment
    • Introduction to Health Technology Assessment

 

Need More Information or Have Questions?

Contact us for more information on ISPOR education and training.

Contact Us

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. 

The course runs 2 days for 2 hrs/day.



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