In this webinar, experts provide an overview of causal inference, along with step-by-step guidance to designing these studies using real-world healthcare data.

Causal inference is used to answer cause and effect research questions and yield estimates of effect. Causal study design considerations and statistical methods address the effects of confounding variables and other potential biases and allow researchers to answer questions such as, “Does treatment A produce better patient outcomes compared to Treatment B?”

Causal study interpretations have traditionally been restricted to randomized controlled trials; however, causal inference applied to observational healthcare data is growing in importance, driven by the need for generalizable and rapidly delivered real-world evidence to inform regulatory, payer, and patient/provider decision making. The application of causal inference methods leads to stronger and more powerful evidence. When these techniques are applied to observational data, the results generated are both from and for the real world.

Along with an overview of causal inference and guidance to designing these studies using real-world healthcare data, presenters walk through several real-world case studies, including the PCORI-funded BESTMED study and a collaborative study with a prominent pharmacy payer.

Key Topics Include:

  • The underlying need for explicit consideration of causal study design principles
  • How to design causal inference studies using real-world data
  • Real-world case study examples and success stories
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Resources

Presenters

Principal Scientist
Scientific Affairs
HealthCore, Inc.

Dr. Michael Grabner has over ten years of experience conducting health economics and outcomes research using a variety of study designs, data sources, and statistical methods. At HealthCore, he is responsible for developing research solutions for clients in the life science and payer spaces, ensuring that study goals are realistic and delivered on time, and for the dissemination of research findings.

Director of Informatics Research
Division of Endocrinology
Brigham and Women's Hospital

Dr. Alexander Turchin is Director of Informatics Research and Director of Quality in Diabetes at the Division of Endocrinology at Brigham and Women's Hospital and Associate Professor of Medicine at Harvard Medical School. His research focus is on studying outcomes of patients with cardiometabolic conditions using advanced real world evidence data analytics.

Associate Research Director
HEOR/Pharmacy Economics
HealthCore, Inc.

Shivani Pandya, MS, has experience developing and executing research studies that utilize large integrated claims databases and a wide spectrum of study designs across numerous therapeutic areas. At HealthCore, she specializes in supporting pharmacy payers develop and adjudicate value-based contracts for pharmaceutical products.

Production Partner

Carelon Research

Carelon Research (formerly HealthCore), a wholly owned, independently operating subsidiary of Elevance Health, is a healthcare research company committed to improving the future of healthcare with trusted insights powered by evidence. We work with life sciences, government, academia, Elevance Health, and collaborators on a broad range of research solutions focused on generating relevant information needed to help improve health outcomes, lives, and communities.

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