A Primer on Using Real-world Data in the U.S. to Support Observational Research and Value Demonstration
Healthcare data collected in non-experimental settings - typically during the normal course of care - are known as “real world data†(RWD), in contrast to data collected in the conduct of randomized clinical trials (RCTs), where conditions are well-controlled. In order to support decision-making, healthcare stakeholders are increasingly demanding real world evidence (RWE) derived from these data, particularly around:
• Understanding prescribing patterns
• Determining medication adherence and utilization
• Quantifying medical resource use and associated stakeholder costs
• Assessing comparative safety and effectiveness
• Performing real-time pharmacovigilance
With a myriad but confusing array of RWD options, the evidentiary landscape has become an arms race in which sponsors seek to develop meaningful RWE faster and more efficiently than the competition. It is now more critical than ever for sponsors and their partners to know how to leverage RWD throughout the full life-cycle of product development in order to stay ahead of competitors.
In this webinar, you will become familiar with:
• The continuum of healthcare evidence
• RWE throughout the product development life-cycle
• Strengths and limitations of available RWD sources
• A pragmatic decision-analytic framework for RWE development
• Resources for best practices
If you are seeking to leverage RWE for your product’s needs and to better understand sources of RWD, please register for this webinar.
Presented by
Peter M. Wahl, ScD, MLA, MS,
Director, Epidemiology
Dr. Wahl is a pharmacoepidemiologist specializing in complex study design and analytic methods, with expertise in the full spectrum of primary and secondary health care data. He directs epidemiological study design and advanced analytics in Covance Market Access Services, and devises strategic advice for clients in the development and synthesis of real world evidence.
For the past 20 years, Dr. Wahl has held management, consulting, and research positions in for-profit and academic institutions including Aetion, the Division of Pharmacoepidemiology & Pharmacoeconomics in the Department of Medicine at the Brigham & Women's Hospital and Harvard Medical School, HealthCore, the Center for Clinical Epidemiology and Biostatistics at the University of Pennsylvania School of Medicine, CareScience, and the Division of Cardiothoracic Surgery at the Hospital of the University of Pennsylvania.
Dr. Wahl received his ScD in Epidemiology from the Harvard Chan School of Public Health, his MS from the University of Pennsylvania School of Medicine, and his MLA from the University of Pennsylvania. He received his training in Pharmacoepidemiology in the Division of Pharmacoepidemiology and Pharmacoeconomics at the Brigham and Women's Hospital and Harvard Medical School. Dr. Wahl also holds a BA in Economics from Cornell University.
Kathryn Plante Anastassopoulos,
Principal
Kathryn Plante Anastassopoulos specializes in directing the collection and analysis of data for pharmacoeconomic, outcomes, and market research studies. She has over 14 years of experience in data collection and analysis of clinical trial data, outcomes data, medical resource use data, billing data, and survey data for both regulatory and non-regulatory studies. She has experience in the development of protocols, case report forms, statistical analysis plans, Web-based surveys, and study reports and also has experience managing the day-to-day operations of sites involved in prospective outcomes studies. She has consulted on both drugs and devices in a number of therapeutic areas including, cardiology, gastroenterology, oncology, diabetes, and pain management.
Prior to joining Covance, Ms. Anastassopoulos was employed as a consultant at Price Waterhouse, where she developed financial forecasting models. Previously, she was an analyst at Statistics Collaborative, where she performed analyses of data collected during all phases of clinical trials.
Ms. Anastassopoulos received a Master's in Statistical Science from George Mason University and B.S.'s in Finance and Statistics from the University of Vermont.
