Considering Individual Treatment Effects When Conducting Research

One of the topics that will be addressed during the Institute of Medicine (IOM) meeting on April 25-26 is how to identify individual treatment effects, or heterogeneity, when conducting research. This issue is especially important because health care providers, patients and payers are often faced with making treatment and coverage decisions using research based on population averages rather than on individual treatment effects.

One of the topics that will be addressed during the Institute of Medicine (IOM) meeting on April 25-26 is how to identify individual treatment effects, or heterogeneity, when conducting research. This issue is especially important because health care providers, patients and payers are often faced with making treatment and coverage decisions using research based on population averages rather than on individual treatment effects. What’s best for the average patient might not be best for the individual patient, and not getting the treatment right the first time could have severe consequences, especially for life-threatening conditions.

In this brief video, Dr. Darius Lakdawalla, Director of Research at the Leonard D. Schaefer Center for Health Policy and Economics at the University of Southern California, discusses the concept of heterogeneity in simpler terms—what it is and why it must be taken into consideration when conducting and analyzing comparative effectiveness research.

NPC Chief Science Officer Dr. Robert Dubois further debunks the myth of the "average" patient and explains why individual treatment effects matter. He says that researchers must consider the potential causes of heterogeneity; payers must consider how to handle it when making coverage decisions; and patients must consider how they can utilize these studies in making treatment decisions.

To learn more about individual treatment effects, check out videos, presentations and summaries from NPC’s conference, the Myth of Average: Why Individual Patient Differences Matter.