# Data Analytics Core

> **NIH NIH P30** · NORTHWESTERN UNIVERSITY · 2024 · $269,613

## Abstract

ABSTRACT
An essential resource for the Northwestern OAIC, the Data Analytics Core
(Analytics Core) will 1) provide high quality, timely and specialized
expertise on research design & analytic methods to `Pepper Scholar' junior
faculty trainees and other affiliated investigators; and 2) develop new
methods for determining older adults' health status and care complexity
to better inform clinical decision making and primary care services.
Our Analytics Core will include both quantitative and qualitative support in order
to provide OAIC investigators a comprehensive suite of tools for research aimed
at primary care innovations in caring for older adults with multiple chronic
conditions (MCC). The framework for delivering research support will be drawn
from the Northwestern University Clinical and Translational Sciences Institute (NUCATS) and it's Biostatistics
Collaboration Center. We will model two NUCATS programs: Mentors, and Vouchers. Analytics Core mentors
will build robust scientific teams by matching Pepper Scholars with specially selected faculty who have relevant
methodological expertise (quantitative and qualitative; e.g. biostatisticians, health economists, interpretivism/
phenomenology experts). Vouchers will provide OAIC investigators with right-sized, quantitative and qualitative
expertise to fund data analysis and programming support on innovative projects related to our OAIC mission to
address MCC in primary care. The specific aims and Development Projects (DPs) of the Analytics Core are to:
Aim 1 Enhance research on older adults with MCC by providing individualized, relevant, and robust
 quantitative and qualitative methodological support.
Aim 2 Advance research on older adults with MCC by developing analytic methodology optimized for
 examining populations who have multiple and complex morbidities.
DP1 will adjudicate accurate diagnosis states for older adults with MCC using multiple sources of data, including
structured and unstructured content from electronic health records (EHRs) and patient self-report. Models will
be developed to estimate a patient's `true condition'. DP2 will leverage data available with the EHR to develop
an accurate estimate of an older patient's `care complexity', quantifying the impact of MCC on older adults' risk
of functional decline. Our Core will also support other Resource Core (Design, Measurement) DPs and Eps.

## Key facts

- **NIH application ID:** 10892967
- **Project number:** 5P30AG059988-05
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Leah J Welty
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $269,613
- **Award type:** 5
- **Project period:** 2020-08-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10892967

## Citation

> US National Institutes of Health, RePORTER application 10892967, Data Analytics Core (5P30AG059988-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10892967. Licensed CC0.

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