One of PCORI’s goals is to improve the methods that researchers use for patient-centered outcomes research. PCORI funds methods projects like this one to better understand and advance the use of research methods that improve the strength and quality of comparative effectiveness research.
This research project is in progress. PCORI will post the research findings on this page within 90 days after the results are final.
What is the project about?
Researchers create clinical prediction models, or CPMs, to help doctors predict a patient’s risks. A risk is how likely it is that a patient will experience an event such as disease, adverse effect, or death. CPMs make predictions using data that are generally easy to collect, such as lab test results.
However, little research has been done on how well a CPM’s predicted risk of an event matches what a patient actually experiences. If doctors don’t know how accurately a CPM predicts risk, they can’t use the CPM to help patients decide on treatments.
This study is looking at different CPMs related to heart disease to understand how well they predict patient risks and how they can be improved.
How can this project help improve research methods?
Information from this study can help researchers improve the development, testing, and updating of CPMs, to ensure the CPMs provide accurate predictions of patients’ risks.
What is the research team doing?
The research team is reviewing existing research about how accurate CPMs are in predicting patient risks related to heart disease. The team is also testing a group of CPMs using clinical data that are readily available. The research team wants to find out how accurately the CPMs predict risks in different populations. Finally, the team is looking at ways to improve CPMs so that they make more accurate risk predictions.
The research team is hoping to learn more about when heart disease CPMs do and don’t work well. The team is working with researchers, doctors, and other people who are interested in heart disease CPMs to create a website to share information about which CPMs make the most accurate predictions.
Research methods at a glance
- Bray Patrick-Lake MFS, Director, Stakeholder Engagement, CTTI; Director, Patient Engagement, Duke CTSA; Co-chair, NIH Advisory Committee, Director Working Group, Precision Medicine Initiative
Other Stakeholder Partners
- Gary S. Collins, PhD, Deputy Director, Centre for Statistics in Medicine, University of Oxford
- William H. Crown, PhD, Chief Scientific Officer, OptumLabs
- John K. Cuddeback, MD, PhD, Chief Medical Informatics Officer, Anceta Data Warehouse, AMGA
- Dana G. Safran, ScD, Senior Vice President, Performance Measurement and Improvement BCBS of MA
- John A. Spertus, MD, MPH, Chief Medical Officer/Director, Health Outcomes Sciences LLC; Cardiologist, Professor of Medicine, Mid Amerca Heart Institute, U of Missouri-Kansas City; Deputy Editor, Circ Cardiovasc Qual Outcomes
- James E. Udelson, MD, Chief of Cardiology, Tufts Medical Center; Professor of Medicine, Radiology, Tufts University School of Medicine