# Rapidly Disseminating Scientific Advances about Northwell Health COVID-19+ Clinical Care to Impact Health and Welfare of Persons across the Life Course in the United States

> **NIH NIH R24** · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · 2020 · $830,694

## Abstract

This is an application under PA-18-935: Urgent Competitive Revision to Existing NIH Grants activated
under Notice of Special Interest (NOSI): NIA Availability of Administrative Supplements and Revision
Supplements on Coronavirus Disease 2019 (COVID-19) to revise our currently active R24: R24AG064191.
The original purpose of the R24 Roybal Coordinating Center is to provide strategic leadership, efficient
coordination, inspired support, and creative dissemination for the Edward R. Roybal Centers. We propose a
competitive revision to this existing grant to meet immediate dissemination needs to help address the specific
public health crisis by the Northwell Health COVID-19 Research Consortium. It is entitled “Rapidly
Disseminating Scientific Advances about Northwell Health COVID-19+ Clinical Care to Impact Health and
Welfare of Persons across the Life Course in the United States.” We propose to do so under NOT-AG-20-022.
 We have created an IRB-approved registry data (“data mart”) on all COVID-19 suspected patients. The
data mart includes all clinical, outcome, laboratory, socio-demographic, and geographic characteristics of
persons presenting under suspicion for, being tested for, or diagnosed with COVID19. Specifically, it includes
information needed to answer vital and urgent public health questions about how to detect, test, and manage
patients with this disease. For example, it includes data from thousands of patients on mechanical ventilation
status, use of hydroxychloroquine, chronic use of angiotensin-converting enzyme (ACE) inhibitors or
angiotensin II receptor blockers, compassionate injection of serum donated from recovered COVID-19+
patients, as well as many other variables. Northwell is the healthcare system with the largest volume of
COVID-19 patients in the country. As of April 3, 2020, we had a total of 5700 COVID-19+ confirmed patients
(mean age, 62.4 years; 39.7% female; 20.1% Hispanic; 23.7% African American). Northwell Health is the
largest academic health system in New York, with approximately 4,844 hospital beds and 672 ICU beds,
serving approximately 11 million persons in Long Island, Westchester, and New York City.
 Because the pandemic is predicted to extend several seasons, we are requesting 2 years of support, to
ensure that the long-term, as well as short-term, consequences of this pandemic can be fully and transparently
reported. This is critical, because the social, economic, institutional, and policy environments addressing the
COVID-19 pandemic may differentially impact the health and welfare of people across the life course and in
vulnerable social and medical groups, such as those with Alzheimers or other related dementias. We have the
data, resources, leadership will, and commitment to accomplish this mission. It would be highly impactful to
rapidly address the research dissemination and productivity of the Northwell healthcare system to ensure that
other healthcare systems can benefit from what we have learned and c...

## Key facts

- **NIH application ID:** 10145874
- **Project number:** 3R24AG064191-02S2
- **Recipient organization:** FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH
- **Principal Investigator:** Karina W. Davidson
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $830,694
- **Award type:** 3
- **Project period:** 2019-09-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10145874

## Citation

> US National Institutes of Health, RePORTER application 10145874, Rapidly Disseminating Scientific Advances about Northwell Health COVID-19+ Clinical Care to Impact Health and Welfare of Persons across the Life Course in the United States (3R24AG064191-02S2). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10145874. Licensed CC0.

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