Results Summary

PCORI funded the development of PCORnet®, the National Patient-Centered Clinical Research Network, to make it easier and more efficient to conduct research. PCORnet is made up of Partner Networks that harness the power of large amounts of health data and patient partnerships.

Clinical Data Research Networks (CDRNs) are one type of network supported by PCORI. CDRNs consist of two or more healthcare systems, including hospitals, integrated delivery systems, and federally qualified health centers. Each CDRN transforms data gathered from routine patient care across its participating health systems to a consistent format, the Common Data Model (CDM), to enable rapid response to research-related questions.

PCORI funded New York City Clinical Data Research Network’s (NYC-CDRN) participation in PCORnet from 2015 to 2019. This report outlines NYC-CDRN’s achievements in building its research infrastructure capacity to

  1. Create ways to involve patients, healthcare providers, health plans, and health systems in the research process and decision making about the network
  2. Continue building the PCORnet CDM to add new types of data, ensure data quality, answer questions and requests, link to data outside the network, and keep data secure and private
  3. Create an efficient infrastructure to carry out clinical trials
  4. Create rules and guidance to protect people who take part in research studies, keep participants’ information confidential, and examine the risks of proposed studies
  5. Work with PCORnet partners and partners outside the network to do research studies, build information systems, and share knowledge and practices
  6. Create a plan to fund the network after PCORI funding ends

Network at a glance

NYC-CDRN brought together seven health systems in and around New York City to collect data for 12 million unique patients. Led by Weill Medical College of Cornell University, the network includes Albert Einstein College of Medicine at Montefiore, Columbia University Irving Medical Center, Icahn School of Medicine at Mount Sinai, New York-Presbyterian, New York University School of Medicine, and the Hospital for Special Surgery.

TitleNew York City Clinical Data Research Network (NYC-CDRN)
Network designClinical Data Research Network (CDRN)
Lead partnerWeill Medical College of Cornell University
Other partnersAlbert Einstein College of Medicine at Montefiore
Columbia University Irving Medical Center
Icahn School of Medicine at Mount Sinai
New York-Presbyterian
New York University School of Medicine
The Hospital for Special Surgery
Participants471 federally qualified health centers, safety net clinics, primary care practices, and hospice centers staffed by 37,000 providers
Population12 million patients who received care in New York City

How does the network operate?

NYC-CDRN created a group made up of representatives from each partner organization to supervise network activities. The network also had several committees that oversaw specific tasks, such as research, working with patients and healthcare providers, finance, the network’s future, patient privacy, and data technology. An advisory council helped make sure that the network’s research matched with what the partner organizations wanted to accomplish. A research group with people from different backgrounds reviewed proposed studies and offered their recommendations to the supervising group.

The network developed two standard agreements that covered how the partners should interact and how they should share data. Partners adopted the agreements to be part of the network. An outside research organization reviewed each study to make sure it protected the rights and privacy of participants.

The network partners created ways to store patient data securely. Approved researchers followed strict security rules for using network data. These data could not be used to identify patients. The supervising group regularly reviewed the network’s data storage to make sure it adhered to these rules.

How did the network involve patients and other partners?

Patient advocates worked on many committees, including the group that supervised network activities. In these roles, they helped make sure that patients’ perspectives and experiences were reflected in network policies and research. NYC-CDRN created groups for patients and caregivers to support the network in reaching out to community members about healthcare research. The network created similar groups for healthcare providers. NYC-CDRN also developed Accelerator Teams to come up with ideas and put plans in place to maximize how communities could be involved in NYC-CDRN research. These teams were made up of diverse groups of people, including patients, who had different types of roles in the healthcare system.

NYC-CDRN used several methods to increase involvement in research for communities that often do not participate in research. When a healthcare site started enrolling people in a NYC-CDRN study, a special group would be present to help any person who was interested in a study to understand the process. Some patients and clinicians on Accelerator Teams reached out to community members and providers to talk about the value of having patient perspectives in research studies. NYC-CDRN worked with nonprofit organizations and places of worship in the communities to encourage people to become involved in healthcare studies. The network also created a research lab in a bus that visited communities to help people learn about clinical research.

Who is in the network?

As of May 29, 2019, NYC-CDRN had data on 12 million unique patients who received care at one or more of the participating network partners. Data came from electronic health records, Medicare, Medicaid, and insurance companies. Using the Common Data Model format, the network linked patient data across different sources while protecting patients’ identities. NYC-CDRN has linked patient records for 1 million people with Medicare insurance and 200,000 people with Medicaid insurance. Data are available starting from 2007.

Population (as of 05/29/19)

Race/ethnicity

  • 44% other
  • 41% white
  • 15% black
  • 8% Hispanic

Sex

  • 59% female
  • 41% male

Age

  • 19% 20 years or younger
  • 30% 21–44 years
  • 30% 45–64 years
  • 13% 65–74 years
  • 8% 75+ years

How is the network supporting research?

While a Partner Network in PCORnet, NYC-CDRN participated in 100 studies. The network worked with other CDRNs on other research studies and on ways to improve the quality of data.

How does the network support future research?

CDRNs follow PCORI standards to make sure their networks continue after PCORI’s funding ends. CDRNs format their data to the CDM and involve patients and healthcare providers in planning and carrying out research studies. CDRNs also take part in research with other networks in PCORnet and build relationships outside of PCORnet. NYC-CDRN is now known as INSIGHT Clinical Research Network (INSIGHT CRN).

Glossary

Clinical Data Research Networks (CDRN): CDRNs are networks that originate in healthcare systems, such as hospitals, health plans, or practice-based networks, and securely collect health information during the routine course of patient care.

Common Data Model (CDM): A CDM establishes a standard way of defining and formatting data.

Institutional Review Board (IRB): A group that follows federal regulations, state laws, and institutional policy to review, monitor, and approve research in order to protect the ethical rights and privacy of the subjects involved.

PCORnet: PCORnet is a network of networks that brings together patients, clinicians, researchers, and healthcare systems to share information and participate in research.

Phase 1 Award | CRN 2020 Award | Phase 3 Award

Project Information

Rainu Kaushal, MD, MPH
Joan & Sanford I. Weill Medical College of Cornell University
$9,619,122
New York City Clinical Data Research Network

Key Dates

May 2019
2015
2019

Study Registration Information

Tags

Has Results
State State The state where the project originates, or where the primary institution or organization is located. View Glossary
Last updated: April 18, 2024