The Johnson & Johnson Office of the Chief Medical Officer (OCMO) believes in the collective power of real-world observational data to complement clinical trial findings, and in sharing our insights widely to accelerate important research and policy developments and improve health outcomes for people everywhere.
We actively collaborate, make our tools publicly available and welcome other researchers to build upon our knowledge. We also publish our findings widely and openly support and facilitate the registration of studies.
To leverage the power of big data and analytics, we launched an open science collaborative with Columbia University called the Observational Health Data Sciences and Informatics (OHDSI). OHDSI is a multi-stakeholder and multidisciplinary open community of researchers working together to generate reliable evidence from observational data to promote better health decisions and better care. All findings, methods, analysis code and related software tools are open-source to advance public health.
The OHDSI community comprises 100+ databases representing more than 2 billion people in 20+ countries and has developed several open-source tools for data analysis and visualization.
Pioneering a new generation of high-quality and reliable observational healthcare science
Johnson & Johnson continues to break new ground in using real-world evidence (RWE) to analyze large data sets in order to improve patient care. Using open-source tools through our OHDSI collaboration, in 2019, researchers including scientists from Johnson & Johnson’s Epidemiology team published a paper in The Lancet that presented an analysis of large-scale observational data on hypertension therapy. This analysis, which included nearly 5 million patients across nine observational databases in four countries, was significant. It uncovered new insights into safety and efficacy differences between classes of hypertension medicines with real insights that can advance clinical practice.
Additionally, the findings presented a new paradigm for conducting large-scale observational healthcare science while addressing common biases of observational research. Legend moves away from the traditional paradigm of one researcher answering one question about one product to garner one outcome against one database, to teams of investigators collaborating to address more questions using multiple data sources to garner multiple insights.
We are also working hand in hand with regulators, trade groups and other partners to support the development of patient-centric research practices and policies. For example, in Asia, we established the China Real-World Healthcare Data Collaboration (CRHEDO), a collaborative effort with databases from eight major tertiary hospitals covering more than 18 million individuals, significantly enhancing possibilities for faster, more targeted policy and medical decisions.
Advancing and innovating how RWE is used in medical devices
Building on our work with the National Evaluation System for Health Technologies Coordinating Center (NESTcc), Johnson & Johnson is participating in five test cases to lead the industry in gauging the feasibility of using RWE for medical device safety evaluation and regulatory decision-making. NEST has a network of at least 13 Network Collaborator healthcare systems, whose electronic health record databases and other sources of real-world data which are being assessed. The NESTcc test cases allow us to work with the U.S. FDA in assessing RWE data quality, completeness and reliability for FDA submissions and to work with leading academic institutions on medical device studies (e.g., Mayo Clini, Yale New Haven, Duke Clinical Research Institute, Mercy Health, Lahey Hospital, Weill-Cornell Hospital, Vanderbilt University) and the U.S. FDA to advance the use of RWE to benefit patients.