The Department of Research Information Technology (RIT) advances biomedical research in the health sciences by providing necessary technology and data services, allowing researchers to focus on their research. Our products and services support all aspects of basic, clinical, and translational research. We provide research informatics, data collection via electronic data capture, user experience and design for static and interactive applications, custom software development, data science and engineering, and development of innovative multi-modal solutions to execute transformative research. We support all research lifecycle phases, providing resources and guidance from the proposal phase through closeout and study data retention.
An Epic data model to facilitate discovery from clinical data in IHIS.
A consortium database comprising de-identified data across participating Epic health systems.
The i2b2 web-based query tool supports cohort discovery from both Ohio State health system data and the SHRINE network.
LifeScale is a linked dataset joining data from the OSUWMC, Cancer Center, Dentistry, Optometry and Nationwide Children's Hospital. The LifeScale dataset is made available via the Health Services Data Lake.
Drawing from EHRs for millions of Americans along with health plan data, PCORnet allows access to a nationwide network of participating institutions who share data accessed through a rigorously curated query process and organized according to a common data model.
The SHRINE network is a consortium of participating academic medical centers. It includes a real-time platform allowing researchers to explore and validate feasibility for clinical studies across the NCATS Clinical and Translational Science Award (CTSA) consortium, from their desktops. The ACT Network (SHRINE) helps researchers design and complete clinical studies, and is secure, HIPAA-compliant and IRB-approved. The ACT Network leverages SHRINE, or the Shared Health Research Information Network, to support multi-site research projects by enabling study feasibility/cohort discovery at partnered institutions.
The SDC is a shared resource for Ohio State researchers that stores and synthesizes large-scale clinical datasets on an easy to use analytic platform to facilitate outcomes research. The SDC aims to reduce the costs associated with data licensing, the time and effort associated with data acquisition, and both the effort and risk of error involved in processing and preparing data for analysis. The SDC streamlines research on secondary datasets to allow researchers to focus on discovery.
The SDC houses large-scale clinical datasets including but not limited to:
• Truven Marketscan
• The Healthcare Cost and Utilization Project (HCUP)
• Centers for Medicare & Medicaid Services (CMS) Claims
PARTNER is an IRB-approved with a focus on the general medical population. PARTNER asks patients to join Ohio State in discovery and provides a framework for broad engagement with the patient population to allow data collection to function more efficiently and effectively. Studies that leverage PARTNER can share data collected on the platform via pre-approved shared protocols. Results can support both exploratory and confirmatory research, improving our collective understanding of the patient experience. The PARTNER protocol includes broad consent for the use of clinical data for research (excluding Cancer), a protocol that supports biobanking of NIH-identified rare diseases not otherwise banked at Ohio State, shared data across studies to allow patient data collected in one study to be used in other studies. Current partners included via the NSF IUCRC process are Indiana University Health, Penn State University, the University of Florida, the University of Alabama at Birmingham, the Medical University of South Carolina, and the University of California, and San Francisco.
All resources fall under or were developed by Research IT.
Computational High-Performance System (CHiPS). CHiPs is a collaborative effort between the Office of Research and Wexner Medical Center IT (WMC-IT) to invest resources in scalable, sustainable, high-performance computing. The CHiPS infrastructure is under development to facilitate the efficient repurposing of legacy infrastructure supporting the medical center to create computational clusters to facilitate research requiring high-performance computing. Currently, we are testing a proof-of-concept computational cluster with the capacity of about 175 concurrent processors.
Research IT consults on the development of data management plans for research projects.
We provide services along the full data science continuum, ranging from data acquisition, cleaning and management, to analysis, to developing and deploying interactive visualization and reportingtools.
Research IT manages REDCap for research at Ohio State, and provides services spanning design and development,
Research IT supports physical and software product design.
Research IT supports research data storage for biomedical science research according to best practices in compliance and preservation.
Our department provides software development to achieve novel solutions to advance health research, spanning standalone solutions as well as tools integrated into existing software and data infrastructure.
The College of Medicine has made an initial investment in high performance research storage capacity through the purchase of an 800 TB Hewlett Packard storage device. Termed the Storage Array for Large-Scale Analytics (SALSA), this investment provides a large-scale working storage solution that is compliant with personal health information (PHI) requirements. It provides the fast, massive storage required for efficient data manipulation.
FHIR is a technology standard for communication across disparate health IT applications through an application programming interface (API), a kind of “lingua franca” for software. The FHIRStarter guide provides guidance on the use of FHIR to access IHIS for research.
An EDC tool hosted on Forte's OnCore platform.
SCARLET: The Scalable Analytics Registry for Rapid Learning and Translational Science (SCARLET) is a secure, web-based application that leverages REDCap and Integrated Health Information Systems (IHIS) for data capture, merging research data sourced from the former with clinical data sourced from the latter. The software takes specific data points from the REDCap database and extracts IHIS data from the Information Warehouse; it then integrates this data into a standard Observational Medical Outcomes Partnership (OMOP) ontology. SCARLET’s front end involves a query portal that can provide search queries across a wider variety of databases.
TrainingGear is a flexible database program designed to maintain information on trainees (students, postdocs, residents, fellows) and to track their accomplishments during training and afterward. Trainee-mentor relationships are maintained. Accomplishments are automatically pulled from public databases, such as PubMed, NIH RePORTER, and xTrain. The program generates reports in formats suitable for submission as tables in T32 and T15 applications, and novel reports, such as network diagrams, are envisioned to be developed. TrainingGear is a powerful tool for tracking trainees at all levels, and the generation of tables for training grant applications should simplify/relieve the major headaches in the submission process and in preparing progress reports.