# Research Design, Data, and Analytics Core

> **NIH NIH P30** · UNIVERSITY OF CHICAGO · 2023 · $137,863

## Abstract

PROJECT SUMMARY – Research Design, Data, and Analytics Core
Quantitative analysis methods are essential for almost all forms of diabetes translational research. Along with
traditional biostatistics, it has become essential to include methods from the social sciences (e.g., economics,
sociology, decision sciences) in order to evaluate observational data and quasi-experimental studies, to assess
outcomes such as health care costs and health care utilization, and to fully understand the long-term population
level impact of novel interventions and policies. Diabetes translation research can also extend into specialized
data sources such as health insurance claims data and electronic health records. At the Chicago Center for
Diabetes Translation Research (CDTR), our close proximity and active collaboration with investigators based in
social science departments as well as research institutes and laboratories of the University of Chicago and
Northwestern University helps to ensure that our research methods have a solid theoretical foundation and a
close link to innovations. The Research Design, Data, and Analytics (RDDA) Core has a strong history of
accomplishments that have helped to advance quantitative methods in cost-effectiveness analysis, decision
analysis, quality of life assessment, personalized medicine, and informatics.
The RDDA Core provides support to numerous new and established investigators affiliated with the CCDTR as
well as external diabetes investigators across the U.S. Many of our ongoing studies are the byproduct of cross-
fertilization of investigators from different disciplines that leads to innovative studies of diabetes prevention and
care. For this renewal, the RDDA Core will continue to provide cutting-edge analytic support for a wide range of
projects in diabetes translation research ranging from clinical and pragmatic trials to cost-effectiveness analysis
to natural experiments. This support is available in terms of technical expertise and material resources for
analysis such as data storage and computational processing capacity, software, and simulation models. Ongoing
methodological areas of support include Biostatistical Analysis, Economic Analysis (Diabetes Simulation
Modeling and Business Case Analysis), Health Care Claims Analysis, Social Network Analysis, and Agent-
Based Modeling. New methodological areas of support will include Informatics and Natural Experiments.
The aims of the RDDA Core are: 1) To provide cutting edge quantitative analysis support for a wide range of
diabetes translation research focused on improving the care and outcomes of vulnerable populations in resource-
constrained settings; 2) To facilitate access to and support for analysis of specialized data sources such as
national health insurance claims and electronic health records; 3) To strengthen and forge new partnerships,
connections, and collaborations with leading methodologists and investigators of the CCDTR. The innovations
and support of ...

## Key facts

- **NIH application ID:** 10683191
- **Project number:** 5P30DK092949-13
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** ELBERT S. HUANG
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $137,863
- **Award type:** 5
- **Project period:** 2011-09-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10683191

## Citation

> US National Institutes of Health, RePORTER application 10683191, Research Design, Data, and Analytics Core (5P30DK092949-13). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10683191. Licensed CC0.

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