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February 26, 2016

The Rockefeller Investigators Collaborate with other New York City CTSAs and Clinical Directors Network to Build and Use the New York City Clinical Data Research Network (NYC-CDRN)
By Rhonda Kost and Jonathan Tobin

The Rockefeller University and Clinical Directors Network (CDN) are both participating in an exciting novel program to create an accessible, sustainable, scalable clinical data network that will enable patient-centered research, support a national patient-centered outcomes research network, and facilitate the development of learning healthcare systems.
The New York City Clinical Data Research Network (NYC-CDRN), funded by the Patient-Centered Outcomes Research Institute (PCORI) as part of PCORnet, is designed to link the approximately 4.4 million electronic health records (EHR) of all patients cared for at the major New York academic medical centers, and in Federally Qualified Community Health Centers affiliated with CDN to form a searchable clinical data resource.

The collaboration, led by Dr. Rainu Kaushal of Weill Cornell Medical Center, is made up of over 22 organizations, including seven independent health systems (CDN, Columbia, Einstein/ Montefiore, Mount Sinai, New York- Presbyterian, NYU Langone, and Weill Cornell), as well as the New York Genome Center, The Rockefeller University, and other partners. The NYC-CDRN aligns patient, researcher and institutional requirements within a rigorous regulatory context that includes: 1. a central IRB, Biomedical Research Alliance of New York (BRANY), 2. robust organization and governance, and 3. patient privacy and data security protections. The NYC-CDRN seeks to engage patients and front-line clinicians in all phases of research protocols and to embed research into practice at the point of care.

A description of the progress made under Phase I of the NYC-CDRN was recently published, including a focus on two common conditions, diabetes and overweight/obesity, and one rare disease, cystic fibrosis
The NYC-CDRN recently received Phase II funding to complete the integration of the health records of approximately 4.5 million unique individuals (many of whom receive care across multiple institutions) from the NYC area and is poised to provide a platform for city-wide and nation-wide population health research, patient-centered clinical trials, observational studies, and precision medicine.

The Rockefeller University has been part of the NYC-CDRN collaboration since its inception. Dr. Jonathan N. Tobin, Community Engagement Core Co-Director of the Rockefeller University Center for Clinical and Translational Science (CCTS) and President/CEO of CDN, a primary care practice-based research network (PBRN) of Federally Qualified Health Centers (FQHCs) co-chairs the Research Committee of the NYC-CDRN. Dr. Rhonda G. Kost, Co-Director of the Community Engagement Core, is an active member of the Privacy and Security and Patient Engagement Committees of the NYC-CDRN Dr. Kost also serves as liaison to The Rockefeller University IRB and the Advisory Committee for Clinical and Translational Science in providing updates regarding NYC-CDRN policy, procedures and protocols. Dr. Barry Coller, Rockefeller Physician-in-Chief, serves along with Dr. Tobin on the NYC-CDRN Senior Advisory Council, which is charged with setting the vision and mission of the NYC-CDRN.

As part of its Phase II initiatives, the NYC-CDRN recently began to accept research requests from investigators and to host demonstration projects to query the health record database. Currently, NYC-CDRN conducts two main types of data queries: 1. De-identified queries of the database using a “computable phenotype” to identify potentially eligible patients for analysis, thus providing individual level data that cannot be connected back to a specific patient; 2. Distributed queries, which have the potential to use de-identifiable data to characterize a cohort, and then to connect to the patients’ physicians to explore the possibility of contacting the patients to obtain their participation in prospective observational and experimental research, including clinical trials.

Rockefeller investigators are on the forefront of testing these algorithms and taking advantage of the wealth of opportunities represented by the database, and several “early adopters” have already begun to work with the NYC-CDRN. These include the PCORI-funded patient-centered comparative effectiveness research study of Home-Based Interventions to Prevent CA-MRSA Infection Recurrence study (“CAMP2”). The project, which is being conducted by Drs. Tobin, Kost and Tomasz is designed to define the patterns of MRSA drug resistant infections and infection recurrence in NYC in parallel with a clinical trial of home visits for decolonization and decontamination to prevent recurrence of the MRSA infection.  In addition, Dr. Ana Emiliano, a former Rockefeller University Clinical Scholar and current member of Rockefeller Early Phase Physician Scientist Program leadstwo NYC-CDRN research projects related to obesity, which is a priority condition for all CDRNs. In one CCTS-funded pilot project grant, she is querying the NYC-CDRN related to her work with bariatric surgery patients cared for by collaborating community physicians in Brooklyn at the NYU Lutheran Family Health Center, one of the CDN member Community Health Centers. The second is a nation-wide PCORI-funded project that is engaging five other CDRNs, in addition to the NYC-CDRN, to examine the impact of bariatric surgery on patient metabolism. Dr. Emiliano is the NYC-CDRN scientific lead investigator in conjunction with a community-based bariatric surgeon, Dr. Rabih Nemr, who practices at the NYU Lutheran Family Health Center. Other investigators are also starting to explore the potential of the NYC-CDRN, including Clinical Scholar Dr. Christina Pressl who plans to query the NYC-CDRN for neurologic diagnoses that might serve as surrogate markers of unrecognized facial prosopagnosia, a disorder characterized by the inability to recognize faces, which will help to build the capacity to identify rare disorders that may be under-diagnosed in practice.

The studies cited above will establish an initial approach to conducting “Big Data” analysis of de-identified EHR data to characterize the prevalence and correlates of the conditions under study. Subsequent studies will build on these efforts by engaging clinicians and their patients in designing and carrying out prospective observational and intervention studies to improve clinical outcomes for patients with these conditions, while increasing our knowledge about the biological mechanisms underlying the conditions and the therapeutic interventions.