There is a national desire to implement real-world evidence (RWE) within regulatory and clinical pathways as a step toward personalized medicine, improved care, and more efficient care. This will accelerate use of routinely collected data to refine care pathways. By influencing what is approved, reimbursed, and selected for care, RWE will adjust the standard of care. But, adjusting the standard of care can have unintended and dangerous consequences. Bad data allowed into a patient?s electronic health record (EHR) has the potential to hurt one patient. Bad data allowed into regulatory or reimbursement pathways can harm a nation. RWE is often used to support trial recruitment, trial design, and marketing insight. As it is increasingly used to make clinical assertions, there is reason to believe that current approaches may benefit from greater rigor.
Cl aims data often have accuracy below 50%. EHR problem lists often have accuracy below 60%. It is believed that low sensitivity incorporates skew since sicker patients with more touch points in the health system have more complete documentation. This program seeks to study data quality in the context of a potential drug launch. Leaders in the space intend to study data quality while testing a novel and highly rigorous approach to RWE. To achieve the goal of understanding how data quality influences RWE assertions, the proposed project includes innovations in phenotyping, gold standard, accuracy measurement, and enhanced privacy and security. This effort comes at a critical time, as regulators, payers, and providers are increasingly incorporating RWE insights into their decision-making processes. By studying data quality and demonstrating safe approaches to RWE, the country can move forward on solid footing.

Public Health Relevance

This proposal tests advanced approaches to phenotyping to support high accuracy real-world evidence (RWE) generation. As regulators and payers increasingly integrate RWE into decision-making pathways, foundational research in data quality promotes application of RWE that can safely enhance the standard of care.

Agency
National Institute of Health (NIH)
Institute
Food and Drug Administration (FDA)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01FD007172-01
Application #
10180783
Study Section
Special Emphasis Panel (ZFD1)
Program Officer
Lauda, Mark
Project Start
2020-09-01
Project End
2023-08-31
Budget Start
2020-09-01
Budget End
2021-08-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Verantos, Inc.
Department
Type
DUNS #
081201871
City
Menlo Park
State
CA
Country
United States
Zip Code
94025