The renewed funding will support efforts to lead and conduct research of national scope over the next four years, increasing capacity for observational studies, retrospective studies, clinical trials, machine learning and more. Additionally, the funding will foster new collaborations and enable investigators to securely pool patient data, upholding the highest level of patient confidentiality, to support research on a specific topic. With this support, researchers can investigate patient-centered ways to understand and treat conditions including depression, diabetes, breast cancer, heart disease and Alzheimer’s disease.
INSIGHT CRN is one of the largest urban clinical networks in the nation, bringing together eight academic centers in New York City and its metropolitan area, as well as Houston, Texas. Led by a team at Weill Cornell Medicine, INSIGHT’s data contributing collaborators include Columbia University Irving Medical Center, Montefiore Health System, Mount Sinai Health System, NewYork-Presbyterian, NYU Langone Health, Houston Methodist and most recently Stony Brook Medicine, which will add approximately 1.3 million patient records to the database.
Together, these eight health systems contribute health care visit data including medical history, laboratory results and diagnoses to INSIGHT’s central database. The clinical data captured in the electronic health records is often linked to claims data from commercial and governmental entities. The database also links to important non-medical, social measures that influence health, such as food insecurity, housing, income level and education level.
“This robust and accessible data set supports patient-centered research to advance health equity by continuing to improve health outcomes for diverse populations,” said Dr. Rainu Kaushal, INSIGHT principal investigator, senior associate dean of clinical research and chair of the Department of Population Health Sciences. “Looking back on the past 10 years of INSIGHT, we are incredibly grateful for PCORI’s ongoing support, for our collaborators and their incredible commitment, and for the many researchers who have turned our real-world data into research results that advance health outcomes for New Yorkers and beyond.”
Dr. Kaushal co-leads INSIGHT with Dr. Mark G. Weiner, professor of clinical population health sciences and medicine, and Dr. Thomas R. Campion, Jr., chief research informatics officer and professor of research in population health sciences, both from Weill Cornell Medicine.
Initially established in 2013 with a $7 million grant, INSIGHT is one of eight CRNs across the country that comprise PCORnet®, the National Patient-Centered Clinical Research Network, with support from the independent, non-profit research funding organization PCORI. In the first phase, Weill Cornell Medicine and its consortium collaborators set up the network’s secure, cloud-based system and a governance body. Patients serving on that governance body contribute recruitment strategies, research questions, study designs and dissemination of results to communities. Since 2013, INSIGHT has been renewed three times and has generated over $100 million in research funding.
Patient and community engagement remains at the forefront of the network’s work, Dr. Kaushal said. Using the Accelerator Model, a multi-stakeholder engagement strategy that fosters co-learning between investigators, patients and other stakeholders, INSIGHT harnesses collective expertise and embeds the patient perspective into research. Ultimately, this method for engagement creates shared vision across scientific and non-scientific communities.
During Phase 3, Drs. Kaushal, Weiner and Campion utilized INSIGHT to co-lead the “RECOVER PCORnet Adult Initiative to Use Real World and Electronic Health Record (EHR) Data to Study Post-Acute SARS CoV-2 Syndrome (PASC),” a nationwide consortium of more than 40 health care institutions analyzing EHR data to detect, predict, treat and prevent Long COVID. Results of Phase 3 studies included identifying four major subtypes of long COVID and finding the risk of long COVID varies in different populations.
In Phase 3, the project team shared research opportunities and disseminated findings through nearly 100 publications, national presentations and media coverage, including NBC News, Today and PBS.
The newly funded Phase 4 will support four key areas including: engagement, data, dissemination, and governance and research readiness. The network will enhance dissemination by introducing real-time dashboards, code-sharing repositories and presentations showcasing the range of INSIGHT and PCORnet capabilities. Also in Phase 4, INSIGHT will continue to strengthen data quality, enhance the PCORnet® Common Data Model—a method of organizing data into a standard structure to enhance usability—and pursue innovative data sources, including claims, patient-reported outcomes and non-medical measures of health. These enhancements are designed to increase the network’s capacity for large-scale national studies and help shape new technologies, therapies, care models and policies that drive social change.
INSIGHT is collaborating with other CRNs to share best practices and ensure that PCORnet collective data capabilities drive impactful research.
“We're excited for the next four years of INSIGHT, to continue to work with our researchers locally and across our national network, PCORnet, to leverage our ever-expanding novel database of real-world data to keep answering the questions that matter most to patients,” Dr. Kaushal said.
The network increasingly supports development and testing of advanced artificial intelligence models aimed at improving prediction, prevention and treatment of complex health conditions. From target trial emulation to extrapolating critical information from clinical notes, INSIGHT’s vast real-world dataset allows artificial intelligence and machine learning experts to conduct complex analyses that traditional methods are unable to support, informing both clinical and public health decision-making.
This article originally appeared in the WCM Newsroom.