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.

 

24-25 May 2021: Tools for Reproducible Real-World Data Analysis

LEVEL - Intermediate
TRACK - Real World Data & Information Systems
LENGTH - 4 Hours | Course runs 2 consecutive days, 2 hours each day

Monday, 24 May | 2 hours of content
9:00AM-11:00AM (EDT) Eastern Daylight  Time
13:00-15:00 (UTC) Coordinated Universal Time
15:00 -17:00 (CEST) Central European Standard Time

Tuesday, 25 May | 2 hours of content
9:00AM-11:00AM (EDT) Eastern Daylight  Time
13:00-15:00 (UTC) Coordinated Universal Time
15:00-17:00 (CEST) Central European Standard Time

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

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


 

 


FACULTY MEMBERS

Blythe Adamson, PhD, MP
Principal Quantitative Scientist
Flatiron Health
New York, NY, USA

Rachael Sorg, MPH;
Senior Quantitative Scientist
Flatiron Health
New York, NY, USA

Joshua Kraut, MS
Senior Data Insights Engineer
Flatiron Health
Seattle, WA, USA

 

2-3 June 2021: A Health Economics Approach to US Value Assessment Frameworks 

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

Wednesday, 2 June | 2 hours of content
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, 3 June | 2 hours of content
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

This short course will focus on the recent ISPOR Special Task Force Report, “A Health Economics Approach to US Value Frameworks.” It will begin with an overview of recent US value assessment frameworks, with emphasis on the importance of perspective and decision context in the construction and use of value frameworks. It will then review how a health economics approach from a societal or health plan perspective leads to use of cost-effectiveness analysis (CEA) to help guide efficient resource allocation.

There will be in-depth discussion of how measuring some aspects of the value of health benefits could augment the standard cost-per-quality-adjusted-life-year metric for CEA. Elements such as value of insurance, value of “hope,” real option value, severity of illness, and several others, have the potential to better capture how patients and/or society value the benefits of some treatments; each one is based on some research findings and some case examples will be shown.

The course will then review how budget considerations, cost-effectiveness thresholds, and opportunity costs enter CEA-based decision-making. Next faculty will review broader approaches to cost-benefit aggregation and value-based decision-making, including extended CEA, augmented CEA (introduced by this Report), and multi-criteria decision analysis (MCDA), with an overview of issues and new approaches to MCDA. It then discusses the strengths and weaknesses of recent US value assessment frameworks from this health economic perspective and closes with a review of the high-level recommendations of this Special Task Force.

FACULTY MEMBERS

Richard J Willke, PhD
Chief Science Officer
ISPOR
Lawrenceville, NJ, USA

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

Charles E Phelps, MBA, PhD
University Professor and Provost Emeritus
University of Rochester
Rochester, NY, USA

 

8-9 June 2021: Statistical Methods for Health Economics & Outcomes Research

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

Tuesday, 8 June | 2 hours of content
9:00AM-11:00AM (EDT) Eastern Daylight  Time
13:00-15:00 (UTC) Coordinated Universal Time
15:00 -17:00 (CEST) Central European Summer Time

Wednesday, 9 June | 2 hours of content
10:00AM-12:00PM (EDT) Eastern Daylight  Time
13:00-15:00 (UTC) Coordinated Universal Time
15:00-17:00 (CEST) Central European Summer Time

Basic Schedule:
Class Time: 2 hours daily

Click for time zone conversion

DESCRIPTION

This course will provide an introduction to statistical concepts with an emphasis on the use of techniques commonly employed in health economics and outcomes research. Faculty will begin by defining statistics, then introducing the concept of random variables and probability before proceeding to discuss the foundations of statistical inference (estimation and the testing of hypotheses). This is followed by bootstrapping, statistics in cost-effectiveness analysis and generalized linear modelling (for cost and utility outcomes). 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.

FACULTY MEMBERS

Jim Lewsey, PhD
Reader in Medical Statistics
University of Glasgow
Glasgow, UK

Gerd K Rosenkranz, PhD
Professor, Applied Mathematics, Probability Theory, Statistics
Center for Medical Statistics, Informatics and Intelligent Systems
Medical University of Vienna
Vienna, Austria

 

17 June 2021: Health Economic Modeling in R: A Hands-on Introduction

LEVEL - Introductory
TRACK - Economic Evaluation
LENGTH - 4 Hours + 30 Minute Mid-Course Break

PREREQUISITE: Familiarity with R coding is not required for attendance, however it would be beneficial and background material can be provided to those with little R experience.

Thursday, 17 June, 2021
8:00AM-12:30PM (EDT) Eastern Daylight  Time
13:00-17:30 (UTC) Coordinated Universal Time
14:00 -18:30 (CEST) Central European Summer Time


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

Click for time zone conversion

DESCRIPTION

This highly practical course will outline the computational and transparency advantages of R over Microsoft Excel for use in health economic modelling. This short course explores the use of R for health economic modelling in the context of health economics and outcomes research (HEOR). The faculty will guide the participants through practical examples of health economics and outcomes research (HEOR). The faculty will also lead participants through practical examples of health economic modelling including, using R for decision trees and Markov models from deterministic analysis through to sensitivity analysis and EVPI. All sessions will interchange between descriptive lectures and hands-on exercises. Participants will be provided with materials following the course, including model examples and information on where to go for further learning. This course is designed for those familiar with the modelling techniques and concepts of decision tree models, probabilistic sensitivity analysis, and discrete time cohort Markov models. This course is designed for those with some familiarity with modelling techniques, but familiarity with R coding is not required.

Attendees will require a laptop with RStudio (v1.1.0 or higher) and R (v3.5.0 or higher) downloaded and installed

Prerequisite:
Familiarity with R coding is not required for attendance, however it would be beneficial and background material can be provided to those with little R experience.
FACULTY MEMBERS

Felicity Lamrock, PhD
Lecturer in Data Analytics
Mathematical Science Research Centre
Queen’s University Belfast
Belfast, Northern Ireland

Gianluca Baio, PhD
Professor of Statistics & Health Economics
Department of Statistical Science
University College London
London, UK

Rose Hart, PhD
Senior Health Economist
BresMed
Sheffield, UK

Howard Thom, PhD, MSc
Lecturer in Health Economics
Lecturer in Health Economics Bristol Medical School (PHS)
University of Bristol
Bristol, UK

 

29-30 June 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 per day

Tuesday, 29 June | 2 hours of content
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
 
Wednesday, 30 June | 2 hours of content
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

 

 

13-14 July 2021: Introduction to Machine Learning Methods

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

PREREQUISITE: Familiarity with R coding is not required for attendance, however it would be beneficial and background material can be provided to those with little R experience.

Tuesday 13 July, 2021 | 2 hours of content
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

Wednesday 14 July, 2021 | 2 hours of content
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

Healthcare data are often available to payers and health care systems in real time, but are massive, high dimensional, and complex. Machine learning merges statistics, computer science, artificial intelligence, and information theory and offers powerful computational tools to enhance the extraction of useful information from complex healthcare data, build highly interpretable models, and make accurate predictions. This course gives an overview of basic machine learning concepts and provides an introduction to a few commonly used machine learning techniques and their practical applications in healthcare and pharmaceutical outcomes research. Participants will be introduced to foundational principles and concepts of statistical machine learning, then be provided with several specific machine learning techniques and their applications in health and pharmaceutical outcomes research. Different machine learning approaches using R will be demonstrated including tree-based methods, penalized regression, and neural networks analysis, as well as techniques for dimension reduction/feature selection. Participants will have hands-on practical experiences with machine learning and gain experience interpreting and evaluating the results and prediction performance that comes from machine learning modeling.

Distinguishing prediction modeling from research on real-world data meant for causal inference in pharmacoepidemiology will be also presented and discussed. This is an entry-level course but is designed for those with some familiarity with traditional statistical modeling techniques (eg, linear regression, logistic regression).

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

The course runs 2 days for 2 hrs/day.



FACULTY MEMBERS
Wei-Hsuan Jenny Lo-Ciganic, MSPharm, MS, PhD
Assistant Professor, Department of Pharmaceutical 
Outcomes and Policy, University of Florida
Gainesville, FL, USA

Hao Helen Zhang, PhD
Professor, Department of Mathematics
University of Arizona
Tucson, AZ, USA

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

 

20-21 July 2021: Introduction to Health Technology Assessment

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

Tuesday 20 July, 2021 | 2 hours of content
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

Wednesday 21 July, 2021 | 2 hours of content
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

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, Massachusetts, USA

Petra Schnell-Inderst, MPH, PhD, Dipl. Biol
Senior Scientist
UMIT - University for Health Sciences
Medical Informatics and Technology
Innsbruck, Austria

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.




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

Your browser is out-of-date

ISPOR recommends that you update your browser for more security, speed and the best experience on ispor.org. Update my browser now

×