# Four State Disability and Health Data Analysis Collaboration

> **NIH ALLCDC U48** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2022 · $239,991

## Abstract

ABSTRACT
Since 2010, clinical medicine has benefited from a rapid surge of clinical research on chronic diseases using
data from electronic health records (EHRs). EHRs are appealing because they can offer large sample sizes,
timely information, and a wealth of clinical, diagnostic, and laboratory information. However, while millions of
patient records are included in large EHR databases, there is poor understanding about the completeness,
validity and reliability of information that can be extracted from EHR records on patient populations, and data
from EHR networks are not population-representative, constraining their utility for population health
surveillance. In this proposal, we propose to leverage our longstanding expertise in developing EHR
surveillance indicators, work we have done in partnership with the NYC Health department, and expand the
partnership to include the New York State Department of Health and investigators from the NYU
Comprehensive Cancer Center. Our goal is to design and test the feasibility of a model surveillance report that
includes performance measures and quality of cancer prevention and control in ambulatory care. Indicators will
be developed using rules-based testing approaches, and then validated using well-established chart review
methods to assess sensitivity and specificity.. We offer: (1) access to a very large EHR network that actively
uses the same OMOP CDM employed by the entire PCORNet distributed research network (11 sites) across
the country, providing opportunities for future scalability; (2) access to EHR data covering a large proportion of
residents living in a large metropolitan area, including high proportions of underinsured, low income,
racially/ethnically diverse patients; and (3) an investigation team with extensive prior experience analyzing
OMOP CDM electronic health databases and performing population health surveillance. Conducting this study
in the diverse, urban environment of NYC offers potential to characterize disparities in at-risk populations

## Key facts

- **NIH application ID:** 10685367
- **Project number:** 6U48DP006396-04M001
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Terry T-K Huang
- **Activity code:** U48 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2022
- **Award amount:** $239,991
- **Award type:** 6
- **Project period:** 2019-09-30 → 2024-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10685367

## Citation

> US National Institutes of Health, RePORTER application 10685367, Four State Disability and Health Data Analysis Collaboration (6U48DP006396-04M001). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10685367. Licensed CC0.

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