Data Science

UT Southwestern fosters a rich collaboration among biostatisticians, epidemiologists, bioinformaticians, computer scientists, and database experts that supports clinical research projects.

Data Sources

Researchers can query both internal data from UTSW’s electronic health records (EHR) and external data from our partner institutions (Parkland, Children’s Health, and Texas Health Resources) as well as large national data sources.

Self-service EHR Data

Epic SlicerDicer
SlicerDicer is a self-service reporting tool that allows researchers access to de-identified EHR data for all patients in Epic. Epic users can access SlicerDicer via the Epic Reports Menu or via the search field in the upper right corner of the interface to:
- Get real-time patient counts and information about current UTSW patients.
- See demographics and create multiple queries within one session.
- Search specific clinics to assess study feasibility.
(Request Epic SlicerDicer access via kathleen.esselink@utsouthwestern.edu.)
Informatics for Integrating Biology and the Bedside (i2b2)
The i2b2 Clinical Research Data Warehouse (CRDW) is a data repository for health information on the current UT Southwestern patient population. Access for UTSW faculty and research staff allows researchers to:
- Search the CRDW at UTSW.
- Obtain patient counts based on criteria selected (ICD-9 or ICD-10, demographics, labs, medications, etc.).
- See demographic breakdowns.
- Refine a patient set and then request de-identified or identified data (with IRB approval) from the CRDW.
(Request i2b2 access via kathleen.esselink@utsouthwestern.edu.)
TriNetX: The Global Health Research Network
TriNetX is a clinical data network that also provides real-world data. Researchers can perform system data queries on UTSW data or on data from the national TriNetX database. Highlights include:
- Free access to local and national data
- The ability to ingest data (PHI, LDS, de-identified) from any data source (i2b2, Epic, OMOP, etc.)
- A network that is constantly refreshed and growing
(Request TriNetX access via kathleen.esselink@utsouthwestern.edu.)

Full-service EHR Request

Clinical Data Exchange Network (ClinDEN)

Clinical Data Exchange Network (ClinDEN) provides a template for user data requests via the CRDW. To start an EHR data request, submit a service request in ClinDEN. A Research and Academic Systems (RAS) data request administrator will then contact you to assist.

ClinDEN Access: Log in with your UTSW ID or create an account by completing the ClinDEN registration form.

Additional Databases

UTSW data researchers also have access to a growing number of national databases including, but not limited to:

Merative MarketScan (formerly IBM MarketScan)

Merative MarketScan Research Database is available for approved, internally funded, or unfunded projects. Merative MarketScan provides one of the longest-running and largest collections of proprietary de-identified claims data for privately and publicly insured people in the U.S. Data contributors are health plans, payers, and self-insured employers. Insights from this integrated, patient-level data can help demonstrate the clinical and commercial value of treatments.

Please complete a data-use request form for access to MarketScan.
OMOP

The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) enables the capture of patient information in an identical way across departments, institutions, and research partners worldwide. Currently, more than 800 million patients worldwide have part of their data in the common OMOP model. The transformation of clinical and administrative data into a common model allows organizations to use common analytic tools designed for the common format and exchange research questions against the OMOP data with other organizations. This allows research of a much larger population than any one organization is capable of.

In 2022, UT Southwestern embarked on the OMOP transformation process and joined the ODHSI network. Once this transformation is complete, access to the network will become available through the Informatics Coordinating Office.
Optum

Optum’s longitudinal EHR repository includes patient care data from more than 700 hospitals and 7,000 clinics in the United States. The data is certified as de-identified by an independent statistical expert following HIPAA statistical de-identification rules and managed according to Optum.

Database Support

Selecting a Database

The Office of Clinical Research can provide guidance on data sources and other resources for conducting data queries. Please ocr@utsouthwestern.edu.
Searching EHR

Within the Clinical and Translational Science Award (CTSA) Program is the Informatics Core, driving digital transformation at UT Southwestern and its hub partners with data fluidity at the center. To ease access to data for researchers and clinicians who are advancing translational research, efforts are underway in collaboration with the Clinical Informatics Center to construct a better connected health ecosystem, alleviating the daunting task of accessing data and modifying electronic health record (EHR) functionality to specific researcher needs.
Building EHR Queries
The Research and Academic Systems (RAS) Division provides infrastructure and software support for all academic departments at UTSW, including clinical research. They provide consulting services to assist investigators and study teams in multiple areas such as database design, query tools, software customization and deployment, project management, hardware infrastructure, and backup services.
- Research Applications and Software (Velos, REDCap, eIRB, eAgreements, COI-SMART, Forte Eval, Influuent PURE (SciVal Experts), Study Finder, Florence eRegulatory Management System, and various application interfaces that integrate these systems)
- Research Informatics Services
- Research IT Consulting

Clinical Informatics

Clinical Informatics Center
Leveraging research experience in biomedical informatics and data, social, and clinical sciences, the Clinical Informatics Center (CIC) at UT Southwestern is a leader in developing, implementing, and evaluating effective clinical informatics solutions for health care providers and patients, as well as in educating future clinical informaticians.

Research collaboration with the CIC endeavors to leverage data repositories from translational and clinical information systems, combined with national databases and registries, to address important problems in clinical research and health care delivery.

Our data scientists provide rich resources to assist investigators in their research, aiding in:
- Identifying unmet medical needs
- Determining trends in incidence and treatment outcomes in multiple disease modalities
- Identifying potential study cohorts during clinical trial design
- Facilitating feasibility analyses
- Back-testing hypotheses with historic data mined from electronic medical records (EMR)
- Facilitating prospective and retrospective data collection and analysis

Analytics

UTSW Biostatistics and Data Science Core
The Biostatistics and Data Science Core (BDSC) aims to provide statistical and data science support for UTSW research projects. The BDSC team consists of experienced biostatisticians and data scientists with capacity of handling and analyzing biomedical research, clinical, and population health data. Services provided by BDSC include data processing, curation, integration, analysis, and management. Service can be requested in the form of hourly, fee-based projects or fixed FTE contracts. Service types include:
- Coordination: Guide users to find appropriate quantitative collaborative resources on campus for their projects.
- Study design and grant application assistance: Provide statistical considerations for various research studies.
- Data analysis support:
  - Data pre-processing and preparation for analysis-ready format.
  - Perform data analysis, statistical modeling, and machine learning for various types of biomedical, clinical, and population health data.
  - Prepare tables and figures for scientific meetings, papers, and grant applications.
- Database development and data management: Support for investigators with problems concerning data acquisition, management, and analysis, including developing secured databases for clinical research.
Data Science Shared Resource (Simmons Cancer Center)

The goal of the Data Science Shared Resource (DSSR) at the Simmons Cancer Center is to provide comprehensive informatics, data analytics, data integration, and data management support for Simmons Cancer Center members. In addition, DSSR has developed a series of data commons and web portals for various types of cancers.
Study Design and Statistical Support (CTSA)

The Biostatistics, Epidemiology, and Research Design (BERD) Program, with support of the UT Southwestern CTSA Program, provides researchers with high-quality advice on study design (including sample size estimations and power calculations), and state-of-the-art analytic methods to maximize interpretability, reliability, and generalizability of data generated by our clinical and translational research projects. It also provides critical methodologies guidance and expertise to clinical and translational investigators at all phases of their research projects, regardless of their level of training.
Biostatistics Shared Resource (Simmons Cancer Center)

The goal of the Biostatistics Shared Resource (BSR) at the Simmons Cancer Center is to provide the infrastructure and methodological expertise to all Simmons Cancer Center investigators through both collaboration, direct services, and investigator training.
Quantitative Biomedical Research Center (QBRC)
The mission of the Quantitative Biomedical Research Center (QBRC) is to develop an open, collaborative, and cross-disciplinary research center to organize quantitative biomedical research projects at any scale. There are three key functions of the QBRC:
- Quantitative biomedical research: involves the development of novel computational algorithms and statistical methodology to solve emerging biomedical questions, with a special emphasis on facilitating the realization of precision health in the era of big data. By focusing on quantitative research grants, publications, and long-term collaborative projects, QBRC will provide a solid foundation for quantitative research and foster the career development of quantitative researchers at UTSW.
- Quantitative education: mentoring students and post-doctoral fellows in quantitative research, designing and teaching quantitative courses, and being actively involved in developing the graduate program in bioinformatics.