Institute for Clinical Research and Health Policy Studies

Medical care is delivered one-patient-at-a-time.  But the evidence for practicing is derived by aggregating many patients—typically thousands or tens of thousands of patients--into groups.  This group-derived evidence would be highly informative for medical practice if all patients were identical.  The dissimilarity of individual patients, however, potentially undermines clinical research as a scientific basis for the practice of medicine.

The Predictive Analytics and Comparative Effectiveness (PACE) Center seeks to better understand and address the limitations of using group-derived evidence as the basis for decision making in individual patients.  Our approach is based on the close integration of clinical and statistical reasoning. Our goal is to provide clinicians and patients with evidence better tailored to their particular circumstances; we have expertise in clinical medicine, risk modeling, individual patient meta-analysis, and observational comparative effectiveness studies.

David Kent, MD, CM, MSc
Director and Professor of Medicine

Christine Lundquist
Research Assistant

Jennifer Lutz, MA
Program Coordinator

Jason Nelson, MPH
Statistician

Jessica Paulus, ScD
Epidemiologist and Assistant Professor of Medicine

Robin Ruthazer, MPH
Statistician and Assistant Professor of Medicine

Saeid Shahraz, MD, PhD
Assistant Professor of Medicine

Benjamin S. Wessler, MD
Instructor

“Detecting Treatment-Effect Heterogeneity” A Learning Health System Activity IOM Roundtable on Value & Science-driven Health Care, Washington DC, April 25-26, 2013.  

“Getting it Right the First Time: Can We Predict Who is Likely to Respond?” The Myth of Average: Why Individual Patient Differences Matter Conference. Omni Shoreham Hotel, Washington DC, Nov 30, 2012.