# Data Capture and Integration Core

> **NIH NIH P30** · UNIVERSITY OF ALABAMA AT BIRMINGHAM · 2020 · $234,967

## Abstract

Project Summary
Recent technological advances have remarkably expanded the capacity for researchers to collect and
efficiently analyze data from disparate sources and outside traditional healthcare delivery settings. However,
barriers still exist for the conduct and translation of research to the point of care where they are maximally
beneficial. These include (1) the costly and laborious nature of building new and adaptive software tools to
match pace with the evolving landscape of research data types and sources, (2) availability and access to
informatics personnel skilled in data extraction from electronic medical records (EMRs) and newer digital data
types (e.g., biosensors); (3) lack of facile access to sizeable, secure, HIPAA-compliant research data storage;
(4) access to analytic software tools capable of analyzing Big Data, including both traditional statistical tools
(e.g., SAS, R, Stata) and more automated methods (e.g., machine learning, deep learning); and (5) lack of a
uniform processes and platforms to integrate research data into the electronic medical record where it can aid
in clinical decision making in a workflow-friendly fashion at the point of care. The proposed Data Capture and
Integration (DCI) Core of Building and InnovatinG: Digital heAlth Technology and Analytics (BIGDATA) Core
Center for Clinical Research (CCCR) seeks to overcome these barriers in collaboration with the BIGDATA
Administrative and Methodologic Cores by facilitating complex clinical and methodologic research into
rheumatologic, musculoskeletal, and skin diseases through the following specific aims: Aim 1. To expand the
range of data sources available to musculoskeletal, rheumatologic and skin disease researchers and to make
research data capture simpler, faster and less costly. Aim 2. To provide investigators with a defined
collaborative process that enhances patient centeredness, data capture, data security and data analysis within
their research. Aim 3. Establish both a platform and a process to translate research findings to the point of
care. Through the BIGDATA Design and Analysis Studios (DAS), a joint DCI and Methodologic Core endeavor,
our experts will work directly with investigators on their research plan(s) and connect them with appropriate
core resources. Finally, to ensure the patient centeredness of our efforts, user base research will be enhanced
through Community Engagement Studios (CES), a qualitative methods driven process connecting researchers
and their intended audience (“community experts”) to generate direct feedback on their proposed projects.
In partnership with the BIGDATA Administrative and Methodologic Cores, and through a highly integrated &
coordinated process the DCI Core will provide the users across the rheumatologic, musculoskeletal, and skin
disease spectrum access to the needed expertise, software & intellectual tools required to meet the needs of
patients, translate findings into clinical care, and ultimately fulfill t...

## Key facts

- **NIH application ID:** 9851528
- **Project number:** 1P30AR072583-01A1
- **Recipient organization:** UNIVERSITY OF ALABAMA AT BIRMINGHAM
- **Principal Investigator:** James H Willig
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $234,967
- **Award type:** 1
- **Project period:** 2020-09-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9851528

## Citation

> US National Institutes of Health, RePORTER application 9851528, Data Capture and Integration Core (1P30AR072583-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9851528. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*