July 24-25: Automated Health Economic Analysis using R Shiny- Virtual
July 24, 2024 - July 25, 2024
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Automated Health Economic Analysis using R Shiny- Virtual
LEVEL: Introductory
TRACK: Health Technology Assessment
LENGTH: 4 Hours | Course runs 2 consecutive days, 2 hours each day
Wednesday, 24 July 2024 | Course runs 2 consecutive days, 2 hours per day
10:00AM–12:00PM Eastern Daylight Time (EDT)
14:00PM–16:00PM Coordinated Universal Time (UTC)
16:00PM–18:00PM Central European Summer Time (CEST)
Thursday, 25 July 2024 | Course runs 2 consecutive days, 2 hours per day
10:00AM–12:00PM Eastern Daylight Time (EDT)
14:00PM–16:00PM Coordinated Universal Time (UTC)
16:00PM–18:00PM Central European Summer Time (CEST)
DESCRIPTION
Health technology assessment relies on health economic analysis through decision analytic modeling. While Microsoft Excel is commonly used for cost-effectiveness analyses, there's a growing trend towards the adoption of open-source R software. R's flexibility allows for advanced analytics like machine learning, as well as transparency and computational feasibility. In this course, we will explore how R Shiny can greatly enhance health economic analysis with automated model calibration, diagnosis, and sensitivity evaluation through user-friendly interfaces.
The course is divided into 3 parts, each addressing crucial aspects of health economic analysis using R Shiny. In the first segment, participants will be introduced to a spectrum of R Shiny applications for health economic analysis, ranging from basic to advanced features and leveraging machine learning as well as user-friendly I/O interfaces.
In the second part, we will discuss practical considerations, such as translating Excel models and those from other languages/software. Attendees will gain valuable insights into statistical modeling, accelerate computations with scalable and parallel algorithms, and perform model check/validation using auto-trained machine learning algorithms.
Finally, participants will unlock the full potential of R Shiny for automated health economic analysis by replicating a previously developed R Shiny case study. Through this practical example, they will further solidify their understanding and ability to utilize R Shiny effectively for health economic analysis. Whether you are an early-career researcher or an established professional, this course will empower you to simplify and automate your economic models using R Shiny. Participants who wish to gain hands-on experience will need a laptop with R and RStudio downloaded and installed. The general R and shiny core structure will be made available to participants.
PREREQUISITE: This workshop is designed for researchers with foundational knowledge or some experience in health economic analysis.
Faculty
Vakaramoko Diaby, PhD, MSc
Director, Health Economics and Value Evidence Partnership
Global Value and Real-World Evidence,
Otsuka Pharmaceutical Development & Commercialization Inc
Princeton, NJ, USA
Zhen Zhang, PhD
Director, Head of Statistics in MRWDA
Medical and Real-World Data Analytics
Otsuka Pharmaceutical Development & Commercialization Inc
Princeton, NJ, USA
Akshay Vashist, PhD
Executive Director
Medical and Real-World Data Analytics
Otsuka Pharmaceutical Development & Commercialization Inc
Princeton, NJ, USA
Basic Schedule:
4 Hours | Course runs 2 consecutive days, 2 hours each day
ISPOR short courses are designed to enhance knowledge and techniques in core health economics and outcomes research (HEOR) topics as well as emerging trends in the field. Short courses offer 4 or 8 hours of premium scientific education and an electronic course book. Active attendee participation combined with our expert faculty creates an immersive and impactful learning experience. Short courses are not recorded and are only available during the live course presentation.